Method for determining polluting and / or sound emissions and / or road safety parameters on a porti

专利摘要:
The present invention relates to a method for determining physical parameters (Phy) of polluting and / or sound emissions and / or road safety of a fleet of vehicles (P1) on a portion of road. The method implements the following steps: a) The positions (posGPS), speeds (vGPS) and altitudes (altGPS) of vehicles on the road section are measured (MES) to determine (DET1) a speed profile (pv) ; b) At least one physical characteristic (Tab) is determined (DET2) the portion of the road for each of the vehicles of the fleet, as a function of the characteristics (PAR) of these vehicles and of the speed profile (pv) determined in step a); c) We apply (APP) the park to the physical characteristics determined in the previous step to obtain a distribution (Rep) of the physical characteristics on the park; d) We determine (DET3) the physical parameter (Phy) on the part of the portion of the road network by means of the distribution (Rep) of the physical characteristics obtained in step c). Figure 1 to publish
公开号:FR3104306A1
申请号:FR1913993
申请日:2019-12-09
公开日:2021-06-11
发明作者:Giovanni DE NUNZIO；Guillaume Sabiron；Laurent Thibault
申请人:IFP Energies Nouvelles IFPEN；
IPC主号:

专利说明:

[0001] The invention relates to the characterization of polluting and / or sound emissions and / or road safety parameters of a portion of the road network.
[0002] According to the World Health Organization (WHO), around 18,000 deaths per day are attributable to poor air quality, raising the estimate to around 6.5 million deaths per year. Air pollution also represents a major financial stake: a senatorial commission of inquiry estimates that the total cost of air pollution is between 68 and 97 billion euros per year for France, in an assessment made in July 2015, integrating both the health damage of pollution but also its consequences on buildings, ecosystems and agriculture.
[0003] The transport sector is still one of the most important sources of pollutants, despite the many measures put in place by the public authorities and technological advances in the field. Transport, all modes combined, is responsible for around 50% of global nitrogen oxide (NOx) emissions and around 10% of PM2.5 particle emissions (by PM2.5, we mean polluting particles, PM for "Particulate Matter" in English, the diameter of which is less than 2.5 μm). Road transport alone represents a considerable part of this contribution due to transport, with 58% of NOx and 73% of PM2.5 particles.
[0004] These emissions are mainly due to three factors: tailpipe emissions, abrasion emissions, evaporative emissions. While heavy goods vehicles are the main emitters of pollutants, it is private vehicles, which are more prevalent in densely populated urban areas, which have the greatest impact on citizens' exposure to poor air quality.
[0005] The measures put in place at the local level to manage the use of transport (such as better transport planning and measures to encourage modal shift), as well as the gradual renewal of the vehicle fleet, have helped to limit gas emissions. the exhaust of road transport in cities and urban agglomerations. Globally, road transport activity has increased by a quarter over the past decade, but NOx and particulate matter emissions have increased by 5% and decreased by 6% respectively. Despite these improvements, pollution levels still exceed WHO thresholds in many cities.
[0006] At present, the services in charge of the operational application of travel policies do not have the tools to enable them to know the impacts of road developments in terms of polluting emissions, noise and road safety. Decision-making such as modifying the maximum authorized speed, installing a traffic light intersection or even a retarder have a direct and significant impact on the speed and acceleration of vehicles, and therefore on their polluting emissions. and their noise. To date, these impacts are not known and are therefore not taken into account by the cities.
[0007] This lack of knowledge is closely linked to the difficulty of collecting real representative data allowing a study of these impacts. Today, new digital technologies offer the possibility of solving this problem. It is indeed possible to collect much more simply a large volume of real mobility data (recordings, for example of the GPS type "Global Positioning System", the daily journeys of thousands of private drivers, also called FCD or "Floating Car Data". ).
[0008] The literature shows that it is now possible to characterize polluting emissions (L. Thibault, P. Degeilh, O. Lepreux, L. Voise, G. Alix, G. Corde, “A new GPS-based method to estimate real driving emissions ”, in IEEE 19th International Conference on Intelligent Transportation Systems, 2016), noise (C. Asensio, JM López, R. Pagán, I. Pavón, and M. Ausejo,“ GPS-based speed collection method for road traffic noise mapping, ”Transp. Res. Part D Transp. Environ., vol. 14, no. 5, pp. 360–366, 2009) and ground grip (R. Vaiana et al.,“ Driving behavior and traffic safety: an acceleration-based safety evaluation procedure for smartphones, ”Mod. Appl. Sci., vol. 8, no. 1, p. 88, 2014) from GPS signals.
[0009] We know in particular the “Comprehensive Modal Emission Model” (CMEM) (M. Barth, “The Comprehensive Modal Emission Model (CMEM) for Predicting Light-Duty Vehicle Emissions,” in Transportation Planning and Air Quality IV : Persistent Problems and Promising Solutions, 2000, pp. 126–137), the Passenger car and Heavy duty Emission Model (PHEM) (S. Hausberger, M. Rexeis, M. Zallinger, and R. Luz, “PHEM User guide for version 10, ”TUG / FVT Rep., pp. 1–57, 2010) and the Virginia Tech Microscopic energy and emission model (VT-Micro) (H. Rakha, K. Ahn, and A. Trani,“ Development of VT -Micro model for estimating hot stabilized light duty vehicle and truck emissions, ”Transp. Res. Part D Transp. Environ., Vol. 9, no. 1, pp. 49–74, 2004).
[0010] However, these few existing air quality monitoring tools do not make it possible to accurately estimate the share of polluting or noise emissions or the impact on road safety in real use, nor to precisely determine their location. in the space. In fact, in these methods, the estimation of pollutant emissions is based on an average speed over road segments of several kilometers, as in the COPERT methodology (“COmputer Program to calculate Emissions from Road Transports” for “Computer program to calculate road transport emissions ”, program funded by the European Environment Agency http://emisia.com/products/copert). These methods therefore do not take into account the acceleration / deceleration phases existing on these segments, although these phases generate strong polluting and / or sound emissions and they can have an impact on road safety, in particular through a lack of grip of the vehicle on the ground.
[0011] In addition, the technological specificities of vehicles are not properly taken into account, especially for recent diesel vehicles, which causes major errors.
[0012] Consequently, it is difficult for cities to make the right decisions in terms of road infrastructure development without having specific tools available to assess these impacts in terms of pollution, noise and / or road safety. .
[0013] Given the inexistence of these tools, some communities directly carry out modifications to the infrastructure or regulations of the road network and possibly carry out an a posteriori study of polluting emissions, noise and / or risks in terms of road safety.
[0014] When performed, this a posteriori study is in some cases quantitative and in other cases only qualitative.
[0015] When it is quantitative, measurements of polluting / noise emissions and / or road safety risks are then carried out around the modifications. However, these measures remain very local and do not make it possible to define the impact precisely on the portion of the road network and in particular do not make it possible to assess local variations. In addition, these measures are expensive. They represent a significant cost for communities.
[0016] When it is qualitative, the study is limited to an approach based in particular on the opinions of users and residents. This approach is therefore subjective and unreliable.
[0017] Regardless of how you conduct the ex post study, making infrastructure changes is very expensive. However, carrying out the infrastructure and possibly the a posteriori study represents a significant cost for the communities. If the study shows that the infrastructure has not improved or even deteriorated the situation, it may be necessary to make a further modification. The costs incurred can therefore be very significant during these trials and errors before obtaining a satisfactory solution. In addition, the studies carried out are not precise and rarely make it possible to assess the impact of the modifications made on several criteria (pollution, noise and road safety, for example).
[0018] In order to avoid the creation of unnecessary infrastructures or regulations and imprecise and incomplete studies, it is therefore necessary to be able to precisely determine the polluting and noise emissions and the risks to road safety of the portion of the network. road, particularly when there are changes to infrastructure or regulations on these portions, without having to physically carry out the changes beforehand.
[0019] To meet these challenges, the invention relates to a method for determining the physical parameters of polluting and / or sound emissions and / or road safety of a fleet of vehicles on a portion of the road network. The method implements at least one means of measuring positions, speeds and / or altitudes on the portion of the road network. In addition, it implements the following steps, preferably by computer means:
[0020] a) At least the positions, speeds and / or altitudes are measured by the measuring means on the road network portion and a speed profile is determined on the road network portion; b) at least one physical characteristic is determined on at least part of the portion of the road network for each of the vehicles of the fleet, as a function of the characteristics of these vehicles and of the speed profile determined in step a); c) The park is applied to the physical characteristics determined in the previous step to obtain a distribution of the physical characteristics on the park; d) The physical parameter is determined on the part of the portion of the road network by means of the distribution of the physical characteristics obtained in step c).
[0021] The invention relates to a method for determining the physical parameters of polluting and / or sound emissions and / or road safety of a predefined fleet of predetermined vehicles on a portion of the road network, the method implementing at least one means of measurement of positions, speeds and altitudes on said portion of the road network. In addition, the method implements the following steps: a) At least the positions, speeds and / or altitudes are measured by said at least one measuring means on said portion of the road network and a speed profile is determined on said portion of the road network; b) at least one physical characteristic is determined on at least part of said portion of the road network for each of said predetermined vehicles of said predefined fleet, as a function of the characteristics of said predetermined vehicles and of the determined speed profile; c) said predefined pool is applied to said physical characteristics determined in the previous step to obtain a distribution of said physical characteristics over said predefined pool; d) said physical parameter is determined on at least said part of said portion of the road network by means of said distribution of said physical characteristics obtained in step c).
[0022] Preferably, a spatial aggregation of the measured positions is carried out.
[0023] Advantageously, the spatial aggregation comprises a correction of the measured positions to correspond to positions of said portion of the road network.
[0024] According to one implementation of the invention, said portion of the road network is divided into segments of predetermined length and steps b), c) and d) are carried out on each of said segments of predetermined length.
[0025] According to a preferred implementation of the invention, in step d), said physical parameter is determined on at least said portion of the road network by aggregating said distribution of said physical characteristics obtained in step c).
[0026] Preferably, when said aggregation of the distribution of said physical characteristics is carried out, said physical parameter is taken equal to the value of said distribution of said physical characteristics corresponding to a determined quantile, preferably the predetermined quantile being the sixtieth percentile
[0027] Advantageously, said physical parameter comprises the quantity of NOx emitted, the quantity of PM2.5 particles emitted, the quantity of greenhouse gases emitted, the sound level emitted and / or a variable representative of the impact on road safety on said part of said portion of the road network, preferably the variable representative of the impact on road safety being the adhesion to said part of the portion of the road network.
[0028] According to one embodiment of the invention, said physical characteristics include the quantity of NOx emitted, the quantity of PM2.5 particles emitted, the quantity of greenhouse gas emitted, the sound level emitted and / or a variable representative of the impact on road safety of each predetermined vehicle on said part of said portion of the road network, preferably the variable representative of the impact on road safety being the adhesion of said predetermined vehicle to said part of portion of the road network.
[0029] Advantageously, the characteristics of the predetermined vehicles include the mass of the vehicles, the type of engine and the type of after-treatment of the flue gases.
[0030] In a variant of the method of the invention, a traffic flow is applied, said traffic flow preferably comprising the flow of vehicles on said portion of the road network, depending on the day and time considered.
[0031] According to one embodiment of the invention, said physical parameter is displayed on a road map, preferably by means of a smart phone, a computer, a digital tablet or a computer system.
[0032] Preferably, said physical parameter is displayed on a road map for a configuration chosen by the user, said configuration possibly comprising said physical parameter to be displayed, the predefined fleet of predetermined vehicles, the level of sensitivity of said physical parameter, the predetermined quantile and / or traffic flow.
[0033] In a variant of the invention, a confidence parameter of said physical parameter is determined.
[0034] In a preferred embodiment of the invention, during step b), for each predetermined vehicle, at least one characteristic of the predetermined vehicle relating to the design of said vehicle is acquired and the following are constructed for said vehicle: i) a model of said vehicle which relates at least the speed profile to the torque and speed of said engine by means of at least one predetermined vehicle characteristic; ii) a model of said engine which relates said torque and said speed of said engine to pollutant and / or sound emissions at the output of said engine by means of at least one predetermined characteristic of the vehicle; and iii) a model of said post-treatment system which links said pollutant and / or sound emissions at the outlet of said engine by means of pollutant and / or sound emissions at the outlet of said after-treatment system by means of at least one characteristic the predetermined vehicle; and determining said torque and said speed of said engine by means of said vehicle model and said speed profile; the pollutant and / or sound emissions at the output of said engine are determined by means of said engine model and said torque and said speed of said engine; and the vehicle's pollutant and / or sound emissions are determined by means of said model of the post-treatment system and said pollutant and / or sound emissions at the output of said engine, said physical characteristics being the pollutant and / or sound emissions at the output of the post-processing system.
[0035] The invention also relates to a computer program product downloadable from a communication network and / or recorded on a medium readable by a computer and / or executable by a processor or a server, comprising program code instructions for the implementation. of the method according to one of the preceding characteristics, when said program is executed on a computer, a portable telephone or a computer device.
[0036] The invention also relates to the use of the method according to one of the characteristics described above to modify the road infrastructure, extend the public transport network and / or modify the road traffic control measures.
[0037] List of Figures
[0038] Other characteristics and advantages of the device and / or of the product according to the invention will become apparent on reading the following description of non-limiting examples of embodiments, with reference to the appended figures and described below.
[0040] Figure 1 shows the steps of the method according to one embodiment of the invention.
[0042] FIG. 2 illustrates an example of a histogram of the distribution of physical characteristics according to the invention.
[0044] Figure 3 shows the steps for determining the physical parameters of polluting emissions according to the invention.
[0046] FIG. 4 represents a first example of visualization of NOx emissions on a portion of the road network on the road map, using the method according to the invention.
[0048] FIG. 5 represents a second example of visualization of NOx emissions on a portion of the road network on the road map, from the method according to the invention, this second example being distinguished from the example of FIG. 4 by the addition of a second traffic light.
[0050] FIG. 6 represents an example of visualization of NOx emissions on a portion of the road network on the road map, identical to FIGS. 4 and 5, from the COPERT method of the prior art.
[0052] FIG. 7 illustrates an embodiment of step b) of the method according to the invention.
[0053] The invention relates to a method for determining the physical parameters of polluting and / or sound emissions and / or road safety of a predefined fleet of predetermined vehicles on a portion of the road network. The physical parameter can be for example:
[0054] For polluting emissions: the quantity of fine particles emitted (PM2.5 for example), the quantity of NOx emitted, the quantity of greenhouse gases emitted (CO ₂ for example), etc. For noise emissions: the estimated noise level in dB (Decibel), etc. Where For road safety: the grip of vehicles on the ground to assess the impact on road safety, etc.
[0055] The object of this method is to determine at least one of these physical parameters on a portion of the road network, current or with a view to a modification, for example, addition of a traffic light, addition of a roundabout , modification of the maximum speed, addition of a retarder, or removal of a development on the road network.
[0056] The predefined fleet may be the current fleet of vehicles crossing the portion of the road network. It can be defined by the user based on recording histories and / or prior knowledge of the vehicle fleet in the area in question. The predefined fleet can also be a future fleet, with a view to the application of future legislation (prohibition on certain categories of vehicles, for example the oldest and / or the most polluting, traffic authorization restricted to electric vehicles, for example) .
[0057] The predetermined vehicles are the vehicles used in the predefined fleet. They therefore depend on the fleet considered and can be determined by the user of the process. Thus, the predefined fleet is a distribution in number or in percentage of vehicles, of each predetermined vehicle, circulating on the portion of the road network.
[0058] The method implements at least one means of measuring positions, speeds and / or altitudes on the portion of the road network. Preferably, the measuring means can in particular be a GPS ("Global Positioning System") geolocation system on board a vehicle or that of a smart phone. This measuring means makes it possible to measure at least the positions, speeds and altitudes of a vehicle on the portion of the road network. These measured data then constitute a history of data of journeys made, called FCD data (from the English "floating car data"). Preferably, it is preferable to carry out several measurements of positions, speeds and altitudes on the same portion of the road network, so as to make the measured data more reliable. Preferably, to give an order of magnitude, at least one hundred trip measurements are made, each trip measuring the position, speed and altitude along the portion of the road network, so as to have reliable data.
[0059] In addition, the method implements the following steps, preferably by computer means:
[0060] At least the positions, speeds and / or altitudes are measured by the measuring means on the portion of the road network, preferably using several vehicles traveling on the portion of the road network, and a speed profile is determined on the portion of the network. road. Each position, speed and altitude measurement corresponds to a vehicle journey made on the portion of the road network, the journeys are made at different times (by different times, we mean that the starting time on the starting point and / or the time of arrival at the point of arrival are different or at least that on the portion of the road network, for two different journeys, there is at least one crossing point crossed at two different instants) and for the same one or more different vehicles. Using different vehicles makes it possible to diversify the data and therefore make the speed profile more reliable.
[0061] The speed profile can for example be determined by the average of the speeds measured at each point of the portion of the road network. The speed profile makes it possible to take into account the acceleration and deceleration phases on the portion of the road network, which improves the accuracy of pollutant and noise emissions and road safety.
[0062] The speed profile defines the speed of the vehicles at each position of the portion of the road network, the position being able to be defined for example by latitude and longitude.
[0063] It is also possible to determine the variations in slope of the portion of the road network, from the measured altitudes, for example, by determining at each point of the portion of the road network, the average altitude of the measured altitudes. Taking into account variations in slope makes it possible to further improve this precision, in particular when the vehicle is on an uphill slope, the pollutant and noise emissions are greater than a portion of the road without a slope or when the vehicle is on a downward slope. , the risks of loss of grip are increased and therefore road safety is reduced. b) At least one physical characteristic is determined on at least part of the portion of the road network for each of the predetermined vehicles of the fleet, as a function of the characteristics of the predetermined vehicles, of the determined speed profile and possibly of the determined slope variations. By part of road network portion, it is meant that the road network portion can be divided into one or more zones. Thus, it is possible to determine the physical characteristic over a short area, for example by quantifying it, which makes it possible to increase the spatial precision of pollution or noise emissions and / or road safety. By physical characteristic is meant the quantity of polluting emissions, for example NOx, PM2.5 particles, greenhouse gases such as CO ₂ , the noise level emitted and / or road safety risks such as that the level of road adhesion of each vehicle predetermined on the portion of the portion of the road network concerned. c) The fleet is applied (or assigned) to the physical parameter determined in the previous step to obtain a distribution of the physical characteristics over the predefined fleet, the fleet defining the number (or percentage) of each predetermined vehicle. By applying the fleet, we give a distribution of each physical characteristic representative of the number of each of the predetermined vehicles in the predefined fleet. Thus, with each predetermined vehicle is associated a value of the physical characteristic and a distribution (for example a percentage representative of the number of each predetermined vehicle in the predefined fleet) associated with this value of each physical characteristic. A distribution (also called distribution) of the different physical characteristics (each of the values depending on the predetermined vehicles) is obtained as a function of the predefined fleet of predetermined vehicles. d) The physical parameter is determined on the part of the portion of the road network by means of the distribution of the physical characteristics obtained in step c). For example, the physical parameter can be determined as being the average or the sixtieth percentile of the distribution of characteristics over the predefined stock.
[0064] As a result, it is possible to determine the emissions of NOx, greenhouse gases such as CO ₂ , PM2.5 type particles, the noise level, the grip of the vehicle on the ground on the portion of the road network. We can thus understand the impact of a modification of the vehicle fleet by prohibiting or not the circulation of certain vehicles. We can also assess the impact of a modification of the road infrastructure (addition of a traffic light, modification of the regulation of maximum authorized speeds, addition of a roundabout, a retarder, etc.) on each physical parameter. These objective characteristics make it possible to avoid the physical realization of these infrastructure improvements or these modifications of road regulations with a posteriori analyzes and measurements to evaluate the experience feedback, once the improvements have been carried out. Indeed, on the one hand, these developments are very expensive for the communities (town halls, departments, regions) and on the other hand, the analyzes to evaluate these modifications are also expensive because they require the installation of means of measurement during rather long periods of time and post-processing of the recorded data. In addition, the physical parameters determined by the method of the invention are objective data whereas currently, the data, for lack of means allowing quantified analyzes, are often subjective data of the users of the road sections and / or of the residents. . The method according to the invention therefore makes it possible to save costs linked to the physical construction of the infrastructure or road development and to the analyzes of the modifications carried out. In addition, it enables objective data to be determined for criteria such as pollutant emissions, noise emissions and road safety. In addition, by means of a multicriteria analysis, it allows an aiter to the choice of modification of the infrastructure or the development of the road network. By infrastructure, we mean any physical element such as a traffic light, a crossroads, a roundabout, an acceleration / deceleration lane, the addition or removal of lanes, etc. By development, we mean any modification of regulation or traffic, for example, modification of the maximum speed, synchronization or not of the two signaling.
[0065] The aggregated physical parameter obtained corresponds to a physical parameter representative of the polluting and / or sound emission and / or road safety on the portion of the road network. For example, it can be considered as an average or the sixtieth percentile of the distribution of the physical characteristics of the predefined fleet over the portion of the road network.
[0066] Preferably, the measurements of positions, speeds and altitudes can be carried out at an acquisition frequency of between 0.1 and 1000 Hz. Thus, the acquisition frequency is sufficient to allow precise location in space and avoid management. too much of these acquisition data. This acquisition frequency can in particular be obtained by GPS or certain applications such as Geco Air ^TM (IFP Energies nouvelles, France).
[0067] Even more preferably, the acquisition frequency can be between 0.5 and 10 Hz. This configuration offers a good compromise between spatial precision and speed of calculations.
[0068] Preferably, it is possible to carry out a spatial aggregation of the measured positions, for example by correcting the measured positions to correspond to positions of the portion of the road network. Indeed, the imprecision of the measurements made by FCD and / or GPS can lead to obtaining data from positions not located on the portion of the road network concerned. The correction makes it possible to reduce these inaccuracies by artificially reducing the positions to the portion of the road network.
[0069] According to a preferred embodiment of the invention, the portion of the road network can be divided into segments of predetermined length, the predetermined length being able to be defined by the user of the method or by the end customer, for example, city administrations. , departments and / or regions. This division into segments increases the precision of the physical parameters (and physical characteristics), in particular their spatial precision. It therefore makes it possible to estimate more precisely a local increase or reduction of a physical parameter (and of a physical characteristic). The lower the predetermined length, the better the precision, in particular spatial precision.
[0070] Steps b), c) and d) can then be carried out on each of the segments of predetermined length, each of these segments then representing a part of the portion of the road network. Thus, the physical characteristics and consequently the physical parameter can be determined on each segment. It is thus possible to more precisely evaluate the local variations of these parameters. The precision is therefore improved.
[0071] According to an advantageous implementation of the invention, in step d), the physical parameter can be determined on at least part of the portion of the road network by aggregating the distribution of physical characteristics obtained in step c). In fact, step c) makes it possible to obtain a distribution of the physical characteristics of the predefined fleet of predetermined vehicles on the portion of the road network. An aggregation step makes it possible to switch from the distributed physical characteristics to a physical parameter which may preferably be a scalar, this scalar possibly corresponding to an objective value representative of the part of the road network portion. Alternatively, the physical parameter could represent a spatial distribution or a set of values, for example, the set of values could include a first scalar representing a determined quantile and a second scalar representing the standard deviation. This physical parameter thus characterizes the part of the road network section, in an objective, robust and precise manner, in terms of pollution emissions, noise emissions and / or road safety.
[0072] Preferably, the aggregation of the distribution of physical characteristics can be achieved by taking the physical parameter equal to the value of the distribution of physical characteristics corresponding to a predetermined quantile. In other words, by aggregating the distribution of the physical characteristics of step c), the aggregated physical parameter is the value of the distribution obtained in step c) for which the determined quantile of the values of the distribution is less than said value: the set of values of the distribution lower than the aggregated physical parameter represents the predetermined quantile.
[0073] Preferably, the predetermined quantile can be the sixtieth percentile. Thus, 60% of the values of the distribution of physical characteristics obtained in step c) are lower than the aggregate physical parameter.
[0074] Quantiles are the values that divide a dataset into intervals that contain the same number of data. The quantiles of a variable are the values that the variable takes for distribution values under the considered quantile. For example, we denote by q -quantiles the set of quantiles of multiples of the fraction ¹ ⁄ _q . There are, in total ( q –1) q -quantiles. The p -th q -quantile of a variable X is therefore defined as the value x _{( p / q )} such that the values less than x _{( p / q )} represent a fraction p / q of the distribution of X. In d 'other terms, for example, the distribution of a value of the variable X less than the p-th quantile x _{( p / q )} equal to p / q is:
[0075]
[0076] P being the distribution function of the variable X.
[0077] Percentiles (also called percentiles) are the quantiles of multiples of the hundredth. Thus, the sixtieth percentile percentile represents the set of values of the variable X such that they represent 60% of the distribution of X. In other words, the distribution of the sixtieth percentile can be written:
[0078]
[0079] Advantageously, the physical parameter can comprise the quantity of pollutants emitted (of NOX and / or of polluting particles of the PM2.5 type for example), the quantity of greenhouse gas emitted, the sound level emitted and / or a variable representative of the impact on road safety (also called the road safety parameter), preferably the variable representative of the impact on road safety being adherence to said part of a portion of the road network. Thus, the physical parameter is an objective datum representative of the pollution emitted, of the noise and / or of road safety resulting from the portion of the road network, in particular by its infrastructures and fittings, and from the predetermined fleet of vehicles.
[0080] According to one configuration of the invention, the characteristics of the predetermined vehicles may include the mass of the vehicles, the type of engine and the type of aftertreatment of the burnt gases. Thus, these characteristics make it possible to precisely define the pollutant and noise emissions and the adhesion to the road for each predetermined type of vehicle. Thus, the accuracy of the physical characteristics of each predetermined vehicle is improved. Consequently, the physical parameters of polluting, noise and / or road safety emissions are more precise.
[0081] According to an advantageous aspect of the invention, it is possible to apply a traffic flow to the physical characteristic determined in step c), the traffic flow preferably comprising the flow of vehicles on the portion of the road network, as a function of the day. and time considered. The traffic flow makes it possible to assess the impact during the day of polluting, noise and / or road safety emissions depending on the flow of vehicles on the portion (or on part of this portion) of the road network.
[0082] The traffic flow can in particular be determined by vehicle flows on the portion of the road network by time slots, for example every ten minutes. For this, we can for example measure the traffic flow during the day, preferably over several days. Thus, we retrieve a history of the traffic and its daily variation recorded during the day.
[0083] According to another variant, the traffic flow can be determined by simulations representing a future traffic flow, for example resulting from a future development of the public transport network or future traffic regulation measures.
[0084] By applying the traffic flow at the end of phase c), one can more accurately assess the hourly variations, for example, during the day, in physical characteristics. To apply the traffic flow, each value of the distribution of the physical characteristics is multiplied by the vehicle throughput of the time slot and / or daily concerned. After applying the traffic flow, step d) aggregates the distribution obtained after applying the traffic flow. Thus, the aggregated physical parameter obtained varies over time, for example in ten minute increments. This makes it possible to assess the impact of traffic congestion during the day on polluting and noise emissions or on road safety risks.
[0085] According to one aspect of the invention, the physical parameter can be displayed on a road map, preferably by means of a smartphone, a computer, a digital tablet or a computer system. Thus, we obtain a map of the physical parameter that the user can view. This visualization makes it possible to better identify the critical areas where polluting and noise emissions or road safety risks are concentrated. This mapping is also useful for assessing the impact of changes in infrastructure or regulations on the portion (or part of that portion) of the road network.
[0086] This mapping can also make it possible to visualize simultaneously or successively the impacts of polluting emissions, noise and road safety. It therefore helps the user to choose an optimal compromise between these three criteria to modify the infrastructure and / or the regulations of at least part of the portion of the road network.
[0087] Preferably, the physical parameter can be displayed on a road map for a configuration chosen by the user. The configuration can include the physical parameter to be displayed, the predefined fleet of predetermined vehicles, the predetermined length of the segments when the portion of the road network is divided into segments, the level of sensitivity of the physical parameter (the level of sensitivity being the displayed precision, for example in increments of 200mg / km for PM2.5 emissions), the predetermined quantile and / or the traffic flow. Thus, we can see the influence of these different parameters in order to increase the precision of the results obtained in terms of value and in terms of spatial location.
[0088] According to an advantageous implementation of the invention, a confidence parameter of the physical parameter can be determined. This confidence parameter will depend in particular on the number of measurements of positions, speeds and altitudes measured in step a), these measurements being used to determine the speed profile and the variations in altitude of the portion of the road network. It may also depend on other parameters. It can be quantitative or qualitative.
[0089] This confidence setting can also be displayed on the road map.
[0090] It takes into account the reliability of the results obtained.
[0091] According to a preferred embodiment of the invention, during step b), for each predetermined vehicle, it is possible to acquire at least one characteristic of the predetermined vehicle relating to the design of each predetermined vehicle and one builds for each predetermined vehicle: i) a model of each predetermined vehicle which relates the speed profile, and preferably the slope profile, to the torque and engine speed of the predetermined vehicle by means of at least one characteristic of the predetermined vehicle (e.g. mass of the vehicle vehicle and preferably its inertia); ii) a predetermined vehicle engine model relates the torque and speed of the predetermined vehicle engine to pollutant and / or noise emissions and / or road safety risks at the engine output by means of at least one characteristic of the vehicle predetermined (for example characteristics such as the type of engine, Diesel, gasoline, electric, its displacement, its performance, etc.); and iii) a model of the after-treatment system which respectively links the pollutant and / or noise emissions and / or the road safety risks at the exit of the engine by means of the pollutant and / or noise emissions and / or the safety risks road at the output of the post-processing system by means of at least one characteristic of the predetermined vehicle (for example, the technical characteristics of the post-processing system, performance of the post-processing for example); and determining the torque and engine speed using the vehicle model and the speed profile (and preferably the slope profile); the pollutant and / or sound emissions and / or possibly the road safety risks at the output of the engine are determined by means of the engine model and the torque and speed of the engine; and the pollutant and / or sound emissions and / or the road safety risks of the vehicle are determined by means of the model of the after-treatment system and the pollutant and / or sound emissions and / or the road safety risks at the exit of the motor.
[0092] The pollutant and / or sound emissions and / or the road safety risks of the vehicle at the output of the means of the post-treatment system model correspond to the physical characteristics at the output of step b) of the method according to the invention.
[0093] As a result, the polluting and sound emissions and / or the road safety risks are characterized precisely for each predetermined vehicle by virtue of the characteristics of the vehicle, of the engine and of the after-treatment system (s). Consequently, the accuracy of the physical parameter is improved on the portion of the road network.
[0094] Determination of the polluting and / or sound emissions of each predetermined vehicle
[0095] Vehicle model
[0096] The vehicle model can for example relate the speed profile and preferably the slope profile to the torque and to the engine speed of each predetermined vehicle, by means of at least one macroscopic parameter, for example the mass of the vehicle, the power maximum and associated engine speed, maximum speed, type of transmission….
[0097] The vehicle model may combine a vehicle dynamics model and a vehicle transmission model. The vehicle dynamics model relates the speed profile and preferably the slope profile to the estimated power of the vehicle by means of at least one macroscopic parameter, for example the mass of the vehicle, the type of transmission, the dimensions of the wheels. . The vehicle's transmission model relates vehicle power to engine speed and torque, using at least one macroscopic parameter, such as transmission type, maximum power, and associated engine speed.
[0098] The vehicle dynamics model takes into account the vehicle dynamics. It can be constructed from the application of the fundamental principle of vehicle dynamics applied to its longitudinal axis, and can be written in the following form:
[0099]
[0100] with:
[0101] m: mass of the vehicle
[0102] t: time
[0103] v is the speed of the vehicle, taken from the speed profile.
[0104] F _res is the result of the friction forces undergone by the vehicle and can be expressed as a function of the speed in the form
[0105]
[0106] with a, b, c parameters of the vehicle to be identified as a function of the general characteristics of the vehicle (macroscopic parameters of the vehicle).
[0107] F _T Tractive effort of the vehicle at the wheel
[0108] F _brk Mechanical braking force
[0109] F _slope can be expressed as a function of the mass of the vehicle and the slope profile of the road:
[0110]
[0111] The angle of inclination b is an input data of the vehicle dynamics model. In fact, the inclination b can be calculated from the altitude and the distance traveled, so it depends on the slope profile.
[0112] These equations make it possible to write a formula which relates the estimated power Pe of the engine to the speed of the vehicle and other known or determinable macroscopic parameters. Indeed, we can write the equation:
[0113]
[0114] With η _trans Transmission efficiency
[0115] v: Vehicle speed
[0116] Thus, by combining the various equations, it is possible to determine a formula which relates the power of the motor to the speed profile and possibly to the slope profile, by means of known and constant macroscopic parameters.
[0117] The transmission model estimates the reduction ratio between the engine speed of rotation and the speed of the vehicle. It can be configured according to the general characteristics (macroscopic parameters) of the vehicle, in particular the mass of the vehicle, the maximum power, the type of transmission, in particular the number of gears. This transmission model only uses the vehicle speed as input, to estimate the reduction ratio:
[0118]
[0119] The function f can be obtained in particular from charts given by the manufacturer. R _MTH-v is the reduction ratio between engine speed and vehicle speed.
[0120] This reduction ratio can then be used to determine the engine speed Ne. Indeed, we can write the following relations:
[0121]
[0122] Then, the torque of the Cme engine can be determined based on the power (estimated using the vehicle dynamics model) and the engine speed:
[0123]
[0124] The function f2 can be obtained by maps given by the manufacturer.
[0125] Engine model
[0126] The engine model relates the engine speed and torque to the pollutant and / or noise emissions at the engine output (i.e. before the after-treatment system), by means of at least one macroscopic parameter . According to one implementation of the invention, to build the engine model, at least one of the following macroscopic parameters can be used: cubic capacity, type of engine, torque and power, architecture of the air loop , the vehicle homologation standard, etc.
[0127] According to one embodiment of the invention, the engine model can be constructed by combining an energy model and a model of pollutants and / or noise at the outlet of the engine. The energy model relates the torque and the engine speed to the flow rates and temperatures of the fluids used in the combustion engine (fuels, intake gases, exhaust gases, possibly recirculation of the burnt gases) by means of at least one macroscopic parameter, for example the cubic capacity, the type of engine, the maximum torque and power, the architecture of the air loop. The model of pollutants and / or noise level at the engine output links the flow rates and temperatures of fluids used in the internal combustion engine to the pollutant and / or noise emissions at the engine output, by means of at least a macroscopic parameter, for example the vehicle approval standard, the type of engine, the architecture of the air loop.
[0128] The energy model makes it possible to estimate the physical quantities on the current operating point (speed, torque). It is parameterized as a function of macroscopic parameters. The estimated physical quantities are the flow rates and temperatures of the fluids used in the combustion engine (fuels, intake gases, exhaust gases, possibly recirculation of burnt gases).
[0129] The model of pollutants and / or noise level at the output of the engine makes it possible, on the basis of information on engine speed and torque, and estimates from the energy model, to estimate the pollutant and / or noise emissions at the output of the motor. It can be configured according to the general characteristics of the vehicle and the engine: the vehicle approval standard, the type of engine, the architecture of the air loop, etc.
[0130] For example, estimating the pollutants at the engine output can be done in two steps:
[0131] estimation of quasistatic emissions using a quasistatic model, and estimation of the impact of transient phenomena using a transient model.
[0132] Alternatively, the estimation of the pollutants at the engine output can be done only in a single step using the quasi-static model.
[0133] Estimating the quasi-static emissions of an engine at an operating point at a given time amounts to considering that this engine is operating stabilized at this operating point.
[0134] Estimating the impact of transient phenomena (unstable operation) makes it possible to take into account transient phenomena, which generally generate excess polluting emissions.
[0135] Quasi-static pollutant models can be parameterized using macroscopic vehicle and engine parameters. They make it possible at any time to estimate the quasi-static polluting emissions at the engine output, from engine speed and torque estimates and from the energy model outputs. Quasi-static models can be written in the form:
[0136]
[0137] PSME _i-QS Emissions of pollutant i at the outlet of the engine for a quasi-static speed Function f3 can be of different type, depending on the type of pollutant studied.
[0138] For example, the quasi-static model of NOx can be derived from the work of Gartner, (U. Gartner, G. Hohenberg, H. Daudel and H. Oelschlegel, Development and Application of a Semi-Empirical NOx Model to Various HD Diesel Engines ), and can be written in the form:
[0139]
[0140] The coefficients a ₀ , a ₁ , a ₂ , a ₃ are obtained from experimental data. NOx _QS is the mass of NOx per unit mass of fuel; m _cyl the mass of air locked in the cylinder per cycle; m _O2 the mass of oxygen locked in the cylinder per cycle.
[0141] One of the advantages of this model is that these coefficients vary little from one engine to another. This point is demonstrated in the above-mentioned Gartner article.
[0142] The particles leaving the engine is the combination of two phenomena: formation and post-oxidation in the combustion chamber. These phenomena are in the first order influenced by the richness, the speed, the quantity of fuel, and the rate of burnt gases.
[0143] Similar models can be built for other pollutants.
[0144] When determining the impact of transient phenomena, the means described below can also be implemented. The air loop dynamics phenomena generate a difference in the BGR rates (fraction of burnt gases, linked to the recirculation of the exhaust gases) and the richness compared to the stabilized operating point, which has a strong impact on pollutants, in particular HC hydrocarbons, carbon monoxide CO and particles. The transient impact models are configured as a function of macroscopic engine parameters, in particular the characteristics of the air loop recovered (atmospheric / supercharged, high pressure EGR _{HP burnt gas recirculation / LP} EGR low pressure burnt gas recirculation ).
[0145] These models make it possible to estimate the dynamic burnt gas fractions BGR _dyn and dynamic wealth AF _ratio-dyn from the quasi-static estimates and the variation of the estimated torque:
[0146]
[0147]
[0148] A Cor _i-QS2TR correction coefficient for each pollutant can be calculated as a function of these dynamic quantities:
[0149]
[0150] These correction coefficients make it possible to estimate the polluting emissions at the engine output by taking into account the transient phenomena. For this, the pollutant emissions at the outlet of the engine can be written by a formula such as:
[0151]
[0152] PSME _i represents the emissions of pollutant i at the outlet of the engine.
[0153] Post-processing model
[0154] The post-treatment model links the pollutant and / or sound emissions at the engine outlet (i.e. before the after-treatment system) to the pollutant and / or sound emissions at the outlet of the post-treatment system. treatment, by means of at least one macroscopic parameter. According to one implementation of the invention, to construct the engine model, at least one of the following macroscopic parameters can be used: cylinder capacity, vehicle approval standard, etc.
[0155] The after-treatment model may include sub-models for each pollution control technology and / or noise reduction sub-models, which are associated depending on the architecture of the vehicle pollution control or noise reduction system. These sub-models can be configured according to macroscopic parameters of the vehicle such as the homologation standard, cylinder capacity, etc. For example, for depollution, the different depollution technologies can be:
[0156] - TWC, from the English "Three-way catalytic converters" meaning three-way catalyst,
[0157] - GPF (for gasoline engine), from the English "gasoline particle filter" meaning particulate filter for gasoline,
[0158] - DOC (for diesel engine), from the English "Diesel oxidation catalyst", meaning oxidation catalyst for Diesel,
[0159] - DPF (for diesel engine), from the English "Diesel particle filter", meaning particle filter for Diesel,
[0160] - LNT (for Diesel engine), from the English "lean Nox trap", meaning Nox trap,
[0161] - SCR (for Diesel engine), from the English "Selective catalytic reduction", meaning selective catalytic reduction.
[0162] de chaque tranche discrétisée. Selon un exemple, le modèle de post-traitement pour les émissions de polluants peut s’écrire:The post-treatment model makes it possible to estimate pollutant or sound emissions at the outlet of the post-treatment system from estimates of temperature, flow rates, and pollutant emissions at the outlet of the engine. The post-processing model can be built by discretizing the post-processing system into several slices (or layers), and by combining the efficiencyof each discretized slice. According to an example, the post-treatment model for pollutant emissions can be written:
[0163]
[0164] PSEE _i represents the emissions of pollutant i at the outlet of the post-treatment system; Conv _{i, j} the conversion efficiency of unit j of the post-treatment system for pollutant i; Check the temperature of the exhaust gases; Check the exhaust gas flow
[0165] The efficiency of the slices of the aftertreatment system can be determined from the manufacturer's maps.
[0166] Determination of the risks in terms of road safety for each predetermined vehicle.
[0167] Road safety risks tend to define the dangerousness of part of a portion of the road network.
[0168] These road safety risks can in particular be determined on the basis of road grip.
[0169] The adhesion to the road can in particular be characterized according to the slope profile and / or the speed profile, parts of the road portion, predetermined vehicles and the speeds, accelerations and decelerations on the portion of the road portion. Grip can also depend on the curves of the road.
[0170] To determine the dangerousness of a portion of a portion of the road network, the road safety parameter at the output of step b) can be determined by implementing the following steps: a displacement model is constructed for each predetermined vehicle considered from the predefined park; then a slip parameter is determined for each predetermined vehicle; then a road safety parameter (which corresponds to a physical characteristic at the end of step b)) is determined for each predetermined vehicle.
[0171] Construction of the vehicle movement model
[0172] A predetermined vehicle displacement model is called a model which relates at least one sliding parameter (of the vehicle's tires) to the position and / or altitude of the vehicle of the slope profile.
[0173] By slope profile (obtained in step a)) is meant a curve representative of the variation or of the spatial derivative of the altitude of the portion of the road network as a function of the positions (latitude and longitude for example) of the portion of road network.
[0174] The model takes into account the movement dynamics of the vehicle (speed, acceleration, etc.) to determine the slip of the vehicle, that is to say an unwanted and uncontrolled movement of the vehicle.
[0175] The predetermined vehicle movement pattern may take into account at least one, preferably all, of the following conditions: the condition of the roadway, the weather conditions, the pressure and the wear condition of the tires of the predetermined vehicle, in particular by means of mapping. This mapping can relate in particular the slip parameter to the coefficient of adhesion of the tires. Thus, the road safety parameter is made more representative of the dangerousness of the predetermined vehicle on the portion of the road network portion.
[0176] . L’angle de glissement latéral correspond à l’angle formé entre le vecteur vitesse du véhicule et l’axe longitudinal du véhicule.A vehicle tire slip parameter may be the predetermined vehicle lateral slip angle, denoted by. The lateral slip angle corresponds to the angle formed between the speed vector of the vehicle and the longitudinal axis of the vehicle.
[0177] Another parameter of the slip of the tires of the vehicle may be the rate of longitudinal slip, denoted SR. The longitudinal slip rate reflects the slip of the tire of the wheel relative to the ground. This slip rate depends in particular on the coefficient of adhesion of the tire on the ground.
[0178] According to one embodiment, it is assumed that the wheels remain in contact with flat ground. In addition, it is assumed that the suspensions are rigid, which amounts to neglecting the roll and pitch.
[0179] For example, we can determine the lateral sliding angle β at any time by a formula of the type:
[0180]
[0181] with:
[0182] i: the instant of calculation,
[0183] v _fy : the projection on the y axis of the speed of the front wheel,
[0184] v _ry : the projection on the y axis of the speed of the rear wheel, and
[0185] v _L : the projection on the longitudinal axis of the vehicle of the speed of the vehicle, the projections of the speeds being a function of said position of the vehicle.
[0186] To determine the lateral slip angle β, we can perform the following series of steps:
[0187] Calculation of the steering angle of the front wheels α
[0188] In this section, the calculation of the steering angle of the front wheels α is detailed.
[0189] The calculation of the yaw angle ψ, from the coordinates (position), can be obtained, at any time i, from the following equation:
[0190]
[0191] With (x _GPS , y _GPS ): positions of the portion of the road network taken from the speed profile and / or the slope profile.
[0192] The angular speed ω of the vehicle can be given, at each instant i, by a formula of the type:
[0193]
[0194] With T _e , the sampling frequency
[0195] du véhicule prédéterminé dans le référentiel (x,y) peuvent être données par:The projections v _x and v _y of the velocityof the predetermined vehicle in the frame of reference (x, y) can be given by:
[0196]
[0197]
[0198] dans le référentiel du châssis du véhicule peuvent être données par:The projections v _L and v _T of the velocityin the frame of reference of the vehicle can be given by:
[0199]
[0200]
[0201] The steering angle can then be calculated:
[0202]
[0203] l _r being the distance between the center of gravity and the rear wheel axle
[0204] And l _f being the distance between the center of gravity and the front wheel axle.
[0205] Calculation of the slip angle
[0206] est détaillé. La méthode choisie consiste à prendre la moyenne l’angle de glissement latéral des roues avant et arrière de chaque véhicule prédéterminé.In this section, the calculation of the lateral slip angleis detailed. The method chosen consists in taking the average the lateral slip angle of the front and rear wheels of each predetermined vehicle.
[0207] et sur l’axe des vitesses des roues avant et arrière et respectivement:To do this, we calculate the projectionsandon the axisfront and rear wheel speedsandrespectively:
[0208]
[0209]
[0210] We deduce β by an equation of the form:
[0211]
[0212] à la position du véhicule prédéterminé sur la portion du réseau routier.Thus, by combining the equations, one obtains a displacement model of each predetermined vehicle which relates the lateral slip angleat the position of the predetermined vehicle on the portion of the road network.
[0213] The slip parameter can also include the longitudinal slip rate SR, determined by the movement model of the vehicle and by a mapping function of the coefficient of adhesion μ of the vehicle and of meteorological conditions (road condition).
[0214] To characterize the coefficient of adhesion μ , the following steps can be implemented:
[0215] Calculation of the angle of the slope θ
[0216] In this section, the calculation of the slope angle θ is detailed.
[0217] The distance traveled Δd at each instant i is given by:
[0218]
[0219] The altitude variation Δh at each instant i can be calculated simply via the altitude resulting from the measurements:
[0220]
[0221] alt _GPS being the altitude at each position of the slope profile.
[0222] Consequently, the instantaneous slope slope can be obtained by:
[0223]
[0224] The angle of the slope θ can be determined, at each instant i, by an equation of the form:
[0225]
[0226] Calculation of the coefficient of adhesion μ
[0227] To calculate the coefficient of adhesion μ, we calculate the traction force at the level of the ground contact with the wheel F _driving and the normal force of gravity F _z :
[0228] ))
[0229] M _vehicle being the mass of the vehicle and g the acceleration of gravity.
[0230]
[0231] l’accélération instantanée du véhicule, et la résultante des forces de frottements qui s’appliquent sur le véhicule, cette résultante étant donnée par la relation suivante appelée «loi de route». Ce terme s’exprime directement en fonction de la vitesse et des caractéristiques du véhiculeWithinstantaneous acceleration of the vehicle, andthe resultant of the friction forces which apply to the vehicle, this resultant being given by the following relation called “road law”. This term is expressed directly according to the speed and characteristics of the vehicle.
[0232]
[0233] With
[0234] ρ _air : the density of the air,
[0235] S: the front surface of the vehicle,
[0236] C _x : the frontal aerodynamic drag coefficient of the vehicle,
[0237] k: the viscous coefficient of friction,
[0238] C _RR : the vehicle's rolling resistance coefficient, and
[0239] peut être obtenue à partir de la vitesse véhicule du profil de vitesse. Par exemple, elle peut être estimée à partir d’une équation de la forme:Instant vehicle accelerationcan be obtained from the vehicle speed of the speed profile. For example, it can be estimated from an equation of the form:
[0240]
[0241] The coefficient of adhesion μ can be deduced from this by an equation of the type:
[0242]
[0243] Thus, by combining the equations, we obtain a vehicle displacement model which relates the coefficient of adhesion to the position and the altitude of the vehicle of the slope profile, then by means of a map we deduce the rate of longitudinal slip SR.
[0244] The method according to the invention is not limited to the displacement model described here below, other models can be implemented, in particular models taking into account the width of the vehicle.
[0245] Determination of a slip parameter
[0246] et/ou le taux de glissement longitudinal SR.At least one slip parameter of the vehicle can be determined by means of the displacement model constructed previously and by means of the speed and slope profiles of step a) of the method of the invention, the slip parameter being able to include the angle lateral slidingand / or the longitudinal slip rate SR.
[0247] déterminé, on caractérise le glissement des pneumatiques par une cartographie dépendant de deux paramètres: le coefficient d’adhérenceμet l’angle de glissement déterminé . Cette cartographie peut dépendre de l’état de la chaussée, en particulier elle est très différente si la route est sèche ou humide (ce qui peut être estimé à partir de la météo), et de l’état des pneus: de leur pression et de leur usure.From the lateral sliding angledetermined, tire slip is characterized by a mapping dependent on two parameters: the grip coefficient μ and the determined slip angle. This mapping may depend on the condition of the pavement, in particular it is very different if the road is dry or wet (which can be estimated from the weather), and on the condition of the tires: their pressure and of their wear and tear.
[0248] Determination of a driving dangerousness indicator
[0249] This involves determining at least one road safety parameter from the sliding parameter (s) determined in the previous step. The road safety parameter can take the form of a value, a score ...
[0250] The road safety parameter can be determined by implementing the following steps:
[0251] at least one dangerous driving threshold (at least one threshold per parameter) is chosen for the slip parameter (s) or their derivatives; it is determined whether the sliding parameter (s) or their derivatives exceed (s) the selected threshold; the number of times and / or the frequency (temporal or kilometer) for which the slip parameter (s) or their derivatives have exceeded the chosen threshold is quantified; and the road safety parameter is deduced from the number and / or the frequency.
[0252] Indeed, the comparison of the slip parameters (or their derivatives) with thresholds makes it possible to determine whether the driver is often in limit conditions of adhesion, for which the road safety risks increase.
[0253] The road safety parameter may consist of the number or frequency of the threshold being exceeded. Alternatively, the indicator can be an average value or a score (for example out of 10) representative of the different numbers and / or frequencies calculated for each slip parameter.
[0254] Other methods of determining road safety risks could be used. These methods could in particular take into account the engine model already defined, the transmission system to the wheels of the system, and / or the braking system with a possible correction by means of post-processing (ABS type for example). Thus, for example, it is possible to add a model of the vehicle, a model of the transmission system, a model of the braking system and possibly a post-processing model.
[0255] The invention also relates to a computer program product downloadable from a communication network and / or recorded on a medium readable by a computer and / or executable by a processor or a server, comprising program code instructions for the implementation. of the method according to one of the preceding characteristics, when said program is executed on a computer, a portable telephone or a computer device. As a result, the use of the process is quick and easy.
[0256] The invention also relates to the use of the method according to one of the preceding characteristics to modify the road infrastructure, extend the public transport network and / or modify the road traffic control measures. Indeed, the method is particularly suitable for comparing the possible technical solutions and thus finding an optimal compromise with regard to polluting and sound emissions and / or road safety risks. In addition, the process avoids the costs of carrying out work and post-completion analyzes to assess the impact of the modifications. It helps anticipate the impact of such changes.
[0257] To do so, the use of the process may in particular include the following steps:
[0258] the steps of the method as described above are carried out for the portion of the existing road network to determine the physical parameters representative of polluting and / or sound emissions and / or of road safety risks;
[0259] - the steps of the process as described above are carried out with at least one modification of the infrastructure or layout (addition of a light at a given position, addition of a roundabout, limitation or increase in the number of traffic lanes the portion of the road network, for example to add a bus or tram lane, modification of the maximum speed on the portion of the road network) to determine, for each configuration (i.e. each modification of infrastructure or development and for the initial portion of the existing road network) the physical parameters representative of polluting and / or sound emissions and / or road safety risks;
[0260] - the optimal configuration is determined (for example, the configuration which makes it possible to reduce polluting emissions as much as possible or that which makes it possible to reduce noise as much as possible);
[0261] - work is carried out on the portion of the road network for the physical implementation of the optimal configuration (for example, construction of the roundabout, addition or removal of a light, addition or removal of traffic lanes, addition of signs speed limit).
[0262] Figure 1 illustrates, schematically and without limitation, an embodiment of the method according to the invention.
[0263] In this process, the following steps are carried out, preferably successively:
[0264] a) was measured MY pos _GPS positions, velocities v _GPS and _GPS altitudes alt by measuring means such as GPS on board vehicles traveling on the road network portion. These measurements can also be recorded in an FCD.
[0265] DET 1 determines a speed profile pv and a slope profile pt on the portion of the road network from these measurements. Measurements of pos positions _GPS velocities v _GPS altitudes alt _GPS are made on several trips from vehicles crossing the highway portion, preferably at least a hundred trips to have sufficient data to determine accurately and reliably profile speed pv and the slope profile pt. Indeed, if there are fewer paths available, the entire process remains feasible but the confidence parameter will be of lower quality. Indeed, with a small number of journeys, between 2 and 10 for example, the reliability of the determined speed profile could be less good, which is characterized by a poorer confidence parameter. On the other hand, from a hundred trips recorded, the speed profile is reliable and the confidence parameter is improved.
[0266] Vehicles used measures of pos positions _{GPS, GPS} v speeds and altitudes alt _GPS are preferably of different types and are not necessarily predetermined preset vehicles park. In other words, the vehicles used for these measurements can be any motor vehicle and it is preferable that the measurements are carried out from different types of vehicles, the inertia and the speed being able for example to influence the acceleration / deceleration, to have a speed profile pv and a slope profile pt representative. The speed profile thus obtained is sufficient to accurately determine the polluting and noise emissions and the road safety risks; b) DET2 is determined for each vehicle of a predefined fleet P1, each of these vehicles not necessarily being linked to the vehicles used for the measurements in step a), at least one physical characteristic representative of the polluting emissions (quantity of NOx emitted, quantity of CO ₂ emitted, quantity of PM2.5 particles for example), noise emissions (noise level) and / or risks in terms of road safety (adhesion of the vehicle to the road for example) on at least a part of said portion of road network. Each physical characteristic is determined as a function of the PAR characteristics of the vehicles taken into account from the predefined fleet P1, as well as the speed profile pv and the slope profile pt determined in step a).
[0267] The speed profile pv and the slope profile pt taken into account for these calculations are therefore always the same whatever the vehicle considered for the following steps. Although the speed profile pv considered is determined for the following steps (steps b) to d)), it could be advantageous to modify the speed profile pv, by modifying the determination of the speed profile in step a). For example, one could consider, to determine the speed profile pv, only a time slot, a particular day of the week, for example Tuesday between 7h and 9h. We could thus refine the determinations of polluting and noise emissions and / or the impact on road safety and increase their precision. The different values of the physical characteristics therefore depend on the PAR characteristics of the vehicles. At the end of step b), we therefore obtain a table Tab of physical characteristics Tab, each physical characteristic of the table Tab corresponding to a vehicle of the predefined fleet P1. c) The predefined set P1 is applied APP to the table Tab of physical characteristics determined in the previous step to obtain a distribution Rep of the physical characteristics over the predefined set P1. To do this, each of the physical characteristics of the table Tab is multiplied by the number Nb (or the percentage) of vehicles corresponding to this value in the predefined fleet P1; A distribution Rep of the distribution of the physical characteristics is thus obtained as a function of the vehicles of the predefined fleet P1 and of the number Nb (or of the percentage) of each of these vehicles in the predefined fleet P1. d) The physical parameter Phy is determined DET3 on at least part of said portion of the road network by means of the distribution Rep of the physical characteristics obtained in step c). To do this, the distribution Rep of the physical characteristics obtained in step c) is aggregated. For example, for this aggregation, the physical parameter can be taken equal to the value of the distribution Rep corresponding to the sixtieth percentile of the distribution Rep. By this aggregation operation, we go from a plurality of physical characteristics in the distribution Rep to a single scalar of the physical parameter Phy, for each criterion observed (polluting emissions, noise and / or road safety risks. In other words, at the end of step d), each part of the road network portion is characterized by at least one scalar value called a physical parameter. Preferably, each part of the road network portion is characterized by several physical parameters, each being a scalar value, the physical parameters possibly being for example the quantity of NOx emitted, the quantity of CO ₂ emitted, the quantity of PM2 particles, 5 emitted, the noise level emitted, road grip.
[0268] The method thus makes it possible to determine the physical parameters of a portion of the road network for a predefined fleet of vehicles P1.
[0269] FIG. 2 schematically and without limitation represents an example of the distribution of the physical characteristics rep_phy as a function of the dist distribution of each of these physical characteristics (for example the noise level emitted in dB). The dist distribution is directly linked to the number of vehicles of each type considered (each predetermined vehicle) in the fleet. Thus, the calculated physical characteristics can correspond to 10, 20, 30, 40, 50, 60, 70, 80 and 90. The values 10 and 50 correspond to vehicles, each representing 20% of the fleet, each of the values 30, 40 , 60, 70, 80, and 90 correspond to vehicles each representing 10% of the fleet considered. The value 20 is not shown. Thus, the sixtieth percentile will correspond to the value 50 of the rep_phy distribution of the physical characteristics. Indeed, the values less than or equal to 5 are 10, 20, 30, 40 and 50, represented respectively by 20%, 0%, 10%, 10% and 20% of the vehicles in the fleet. Thus, values less than or equal to 50 do indeed represent 60% of the fleet considered. Thus, the physical parameter which is aggregated in step d), by aggregating at the sixtieth percentile, is 50. For example, we could then consider that the noise level of the portion of road network portion is therefore equal to 50 dB for the fleet of vehicles considered.
[0270] Figure 3 illustrates spatial aggregation. In this figure, there is a road 10 materialized by the two solid black lines. This road is a two-lane road, the two lanes being separated by the line shown by the dotted line. Each of the lanes allows traffic in one direction. In other words, one of the lanes allows traffic from A to B and the other from B to A. Lane 20 allows traffic from A to B.
[0271] A position measurement was made of a path of a vehicle traveling from A to B at an acquisition frequency of 1 Hz. The measurement points correspond to the black circles. It is observed that some of these Pout points are located outside the space between the upper continuous black line and the dotted line, delimiting the channel 20. These Pout points are then aggregated, that is to say corrected to be brought back artificially in the space of the channel 20 delimited by the upper continuous black line and the dotted line. The aggregation step thus consists in correcting the measured points to bring them back into the space considered.
[0272] The arrows in phantom lines represent the corrections made on each of the Pout points and the gray rectangles represent the corrected measurement points.
[0273] FIG. 7 illustrates, in a schematic and non-limiting manner, an embodiment of step b) of the method of the invention. In this figure, the dotted lines indicate optional elements of the method.
[0274] Prior to this step b), the different models (model of vehicle MOD VEH, model of engine MOD MOT and model of post-processing MOD POT) are built. These models are built from macroscopic PAR parameters. Optionally, the macroscopic PAR parameters can be obtained from a BDD database, which lists the various vehicles in circulation. For example, the macroscopic PAR parameters can be obtained by indicating the registration number of the predetermined vehicles of the predefined fleet, the BDD database associating the plate number with the design of the vehicle (make, model, engine, etc.), and comprising the macroscopic parameters of the predetermined vehicles.
[0275] A first series of macroscopic parameters PAR1 is used for the construction of the model of the vehicle MOD VEH. This first series of macroscopic parameters PAR1 can include the following parameters: the mass of the vehicle, the maximum power and the speed of the associated engine, the maximum speed, the type of transmission (non-exhaustive list). Each of these parameters depending on each predetermined vehicle.
[0276] A second series of macroscopic parameters PAR2 is used for the construction of the model of the motor MOD MOT. This second series of PAR2 macroscopic parameters can include the following parameters: cubic capacity, type of engine, maximum torque and power, architecture of the air loop, vehicle approval standard (non-exhaustive list) . Each of these parameters depending on each predetermined vehicle.
[0277] A third series of macroscopic parameters PAR3 is used for the construction of the MOD POT postprocessing model. This third series of PAR3 macroscopic parameters can include the following parameters: cylinder capacity, vehicle approval standard (non-exhaustive list). Each of these parameters depending on each predetermined vehicle.
[0278] From the speed profile pv and the slope profile pt determined in step a) of the method, the torque and the engine speed are determined from the model of the vehicle MOD VEH, which determines the torque Cme and the speed Ne of the motor, as a function of the speed profile and preferably as a function of the slope profile. Each predetermined vehicle has a specific MOD VEH vehicle model.
[0279] It is then possible to determine the pollutant and / or sound emissions at the output of the engine, by means of the engine model MOD MOT, which determines the pollutant and / or sound emissions at the output of the PSME engine, as a function of the torque Cme and the speed Ne of the motor. The engine considered depends on each predetermined vehicle.
[0280] Then, it is possible to determine the emissions of pollutants and / or noise from the vehicle, that is to say at the output of the post-treatment system by means of the post-treatment model MOD POT, which determines the emissions of pollutants and / or sound at the output of the PSEE post-treatment system, depending on the pollutant and / or sound emissions at the output of the PSME engine. The determination of pollutant and / or sound emissions can be carried out at any time, for example at a frequency of 1 Hz. The post-treatment system considered depends on each predetermined vehicle.
[0281] It is then possible to optionally store all or part of this data. Once the pollutant and / or sound emissions of the predetermined PSEE vehicles are characterized, these can be stored STO (recorded), in particular in a database (different from the database which includes the macroscopic parameters). This STO storage can only relate to the pollutant and / or noise emissions of predetermined PSEE vehicles, but can also relate to intermediate data: the torque Cme and the engine speed Ne and / or the pollutant and / or noise emissions at the output of the engine. PSME engine. This information enables real uses and associated emissions to be monitored with good spatial and temporal resolution. This information can, for example, make it possible to assess the environmental relevance of road infrastructure at the level of a street, identify localized peaks in emissions, identify the impact of driving style on emissions, etc.
[0282] Examples
[0283] Figures 4 to 6 compare examples of determining pollutant emissions (quantity of NOx emitted) on the same portion of the road network in the Lyon metropolitan area, the portion of the road network extending over approximately 150 m.
[0284] Figures 4 and 5 show the difference before and after the addition of a traffic light on the portion of the road network considered. They represent maps of polluting emissions Em on a road map defined by longitude Lo in degrees on the x-axis and latitude La in degrees on the y-axis. Pollutant emissions are listed by a gray level between 0 and 1000 mg / km of road.
[0285] Figure 4 shows the NOx emissions determined by the method of Figure 1 according to the invention before the addition of the traffic light. The portion of the road network has a first traffic light F1, before the addition of the second traffic light.
[0286] Figure 5 shows the NOx emissions determined by the method of Figure 1 according to the invention after the addition of the traffic light F2, the traffic light F2 is located approximately 100m upstream of the traffic light F1. FIG. 5 therefore includes two traffic lights, F1 already present initially before the modification (identical to that of FIG. 4) and F2 which has been added.
[0287] The speed profiles and slopes to determine the polluting emissions of the maps shown in Figures 4 and 5 were determined using the position, speed and altitude measurements collected by the Geco air ^TM application (FCD at 1Hz).
[0288] In the context of these examples of the invention, the installation of the traffic light is positioned on a crossroads located on avenue Roger Salengro in Villeurbanne at the intersection with rue de Longchamp. The F2 light is positioned in figure 5.
[0289] The addition of this traffic light was intended to slow the speed of traffic and make the area quieter and safer for passers-by and residents.
[0290] But as can be seen in Figure 5, by comparison with Figure 4, upstream (in the direction of the black traffic arrow) of the added traffic light F2, the presence of the F2 light increases the rate of NOx emitted. , about 25%. This is mainly due to the stopping phase of the F2 traffic light, and therefore to the acceleration and deceleration phases imposed by the F2 traffic light.
[0291] Figure 6 shows an example of determining pollutant emissions from the same portion of the road network as in Figures 4 and 5, in accordance with the COPERT method of the prior art. This method is based on the average speed over long parts of the road network (at least 1 km). Thus, the presence or absence of traffic lights F1 and / or F2 has no impact on this method. This means that figure 6 corresponds both to the application of the COPERT method with a single light (the F1 light in figure 4), and to the application of the COPERT method with two lights (the F1 and F2 lights of figure 5) and even to a variant without traffic lights. According to the COPERT method, there would therefore be no difference between these different situations, the method not allowing to discretize the portions of road networks, for example the F1 traffic light and the F2 traffic light.
[0292] This method therefore does not make it possible to precisely visualize the local impact of polluting emissions, nor to precisely determine pollutant emissions in space. On the contrary, figures 4 and 5 allow local discretizations of polluting emissions, which makes it possible to precisely determine the position of the most polluted areas and to assess the impact in terms of pollution of new infrastructures or new regulations on a part. of road network.

权利要求:
Claims (15)
[0001]
Method for determining physical parameters (Phy) of polluting and / or sound and / or road safety emissions of a predefined fleet (P1) of predetermined vehicles on a portion of the road network, the method implementing at least one means for measuring positions ( _GPS pos), speeds (v _GPS ) and altitudes ( _GPS alt) on said portion of the road network, characterized in that the following steps are implemented: a) At least the positions ( _GPS pos), speeds (v _GPS ) and altitudes ( _GPS alt) are measured (MES) by said at least one measuring means on said portion of the road network and a profile of speed (pv) on said portion of road network; b) At least one physical characteristic (Tab) is determined (DET2) on at least part of said portion of the road network for each of said predetermined vehicles of said predefined fleet, as a function of the characteristics (PAR) of said predetermined vehicles and of the speed profile (pv) determined; c) said predefined pool (P1) is applied (APP) to said physical characteristics (Tab) determined in the previous step to obtain a distribution (Rep) of said physical characteristics over said predefined pool; d) said physical parameter (Phy) is determined (DET3) on at least said part of said portion of the road network by means of said distribution (Rep) of said physical characteristics obtained in step c).
[0002]
Method according to Claim 1, in which a spatial aggregation of the _{measured positions (GPS} pos) is carried out.
[0003]
A method according to claim 2, wherein the spatial aggregation comprises a correction of the _{measured positions (GPS} pos) to correspond to positions of said portion of the road network.
[0004]
Method according to one of the preceding claims, for which said portion of the road network is divided into segments of predetermined length and steps b), c) and d) are carried out on each of said segments of predetermined length.
[0005]
Method according to one of the preceding claims, for which in step d), said physical parameter (Phy) on at least said portion of the road network is determined by aggregating said distribution (Rep) of said physical characteristics obtained in step c ).
[0006]
Method according to claim 5, for which when carrying out said aggregation of the distribution (Rep, Rep_phy) of said physical characteristics, said physical parameter (Phy) is taken equal to the value of said distribution (Rep, rep_phy) of said corresponding physical characteristics at a determined quantile, preferably the predetermined quantile being the sixtieth percentile.
[0007]
Method according to one of the preceding claims, for which said physical parameter (Phy) comprises the quantity of NOx emitted (Em), the quantity of PM2.5 particles emitted, the quantity of greenhouse gas emitted, the sound level emitted and / or a variable representative of the impact on road safety on said part of said portion of the road network, preferably the variable representative of the impact on road safety being adhesion to said part of a portion of the road network.
[0008]
Method according to one of the preceding claims, in which the characteristics of the predetermined vehicles include the mass of the vehicles, the type of engine and the type of after-treatment of the flue gases.
[0009]
Method according to one of the preceding claims, for which a traffic flow is applied, said traffic flow preferably comprising the flow of vehicles on said portion of the road network, depending on the day and time considered.
[0010]
Method according to one of the preceding claims, wherein said physical parameter (Phy) is displayed on a road map, preferably by means of a smart phone, a computer, a digital tablet or a computer system.
[0011]
Method according to claim 10, for which said physical parameter (Phy) is displayed on a road map for a configuration chosen by the user, said configuration possibly comprising said physical parameter (Phy) to be displayed, the predefined fleet (P1) of vehicles predetermined, the sensitivity level of said physical parameter, the predetermined quantile and / or the traffic flow.
[0012]
Method according to one of the preceding claims, for which a confidence parameter of said physical parameter is determined.
[0013]
Method according to one of the preceding claims for which during step b), for each predetermined vehicle, at least one characteristic of the predetermined vehicle (PAR) relating to the design of said vehicle is acquired and the following are constructed for said vehicle: i) a model of said vehicle (MOD VEH) which relates at least the speed profile to the torque and speed of said engine by means of at least one predetermined vehicle characteristic (PAR); ii) a model of said engine (MOD MOT) which relates said torque and said speed of said engine to pollutant and / or sound emissions at the output of said engine by means of at least one characteristic of the predetermined vehicle (PAR); and iii) a model of said post-treatment system (MOD POT) which connects said pollutant and / or sound emissions at the outlet of said engine by means of pollutant and / or sound emissions at the outlet of said post-treatment system by means of at least one characteristic of the predetermined vehicle (PAR); and said torque (Cme) and said speed (Ne) of said engine are determined by means of said vehicle model (MOD VEH) and said speed profile (pv); the pollutant (Em) and / or sound emissions at the output of said engine (PSME) are determined by means of said engine model (MOD MOT) and of said torque (Cme) and of said speed (Ne) of said engine; and the pollutant (Em) and / or sound emissions of the vehicle (PSEE) are determined by means of said model of the post-treatment system (MOD POT) and said pollutant (Em) and / or sound emissions at the output of said engine ( PSME), said physical characteristics being the emissions of pollutants (Em) and / or sound at the output of the post-treatment system.
[0014]
Computer program product downloadable from a communication network and / or recorded on a computer readable medium and / or executable by a processor or a server, comprising program code instructions for the implementation of the method according to one of the preceding claims, when said program is executed on a computer, mobile phone or computing device.
[0015]
Use of the method according to one of claims 1 to 13 for modifying the road infrastructure, extending the public transport network and / or modifying the road traffic control measures.

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同族专利:

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公开号 | 公开日

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FR3104306B1|2022-02-18|

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US20210172750A1|2021-06-10|

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CN113034930A|2021-06-25|

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EP3836115A1|2021-06-16|

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法律状态:
2020-12-29| PLFP| Fee payment|Year of fee payment: 2 |

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2021-06-11| PLSC| Publication of the preliminary search report|Effective date: 20210611 |

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2021-12-27| PLFP| Fee payment|Year of fee payment: 3 |

优先权:

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申请号 | 申请日 | 专利标题

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FR1913993A|FR3104306B1|2019-12-09|2019-12-09|Method for determining polluting and/or sound emissions and/or road safety parameters on a portion of the road network|

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FR1913993|2019-12-09|FR1913993A| FR3104306B1|2019-12-09|2019-12-09|Method for determining polluting and/or sound emissions and/or road safety parameters on a portion of the road network|

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EP20209902.4A| EP3836115A1|2019-12-09|2020-11-25|Method for determining the polluting and/or noise emissions and/or road safety parameters on a portion of a road network|

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CN202011422996.7A| CN113034930A|2019-12-09|2020-12-08|Method for determining pollutant, noise emission and road safety parameters on road network segment|

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US17/116,754| US20210172750A1|2019-12-09|2020-12-09|Method of determining pollutant and/or noise emissions and/or road safety parameters on a road network portion|