Generation of electric vehicle traffic information

Abstract

A method for generating electric vehicle traffic information includes obtaining (200) traffic data associated with at least one segment of at least one road and determining (201) an indicator of electric vehicle traffic of the segment. The determined traffic indicator is then assigned (202) to an identifier of the segment in a database, and electric vehicle traffic information is generated (203) from the database. FIG. 2

Description

Title of the invention: Generation of electric vehicle traffic information

[0001] The present invention belongs to the field of generating motor vehicle traffic information.

[0002] It finds applications, in particular, but not exclusively, in driving assistance applications, such as applications for navigation to a destination or applications for displaying information in a vehicle interior.

[0003] The term “vehicle” means any type of vehicle such as a private, utility or heavy goods vehicle.

[0004] Autonomy is a major issue for electric vehicles, particularly when driving at high speed, on motorways or expressways.

[0005] It is particularly desired, for the comfort of the driver, to achieve a range of at least 300 kilometers for a speed of 130 kilometers per hour, km / h, with an outside temperature of 23°C.

[0006] When the range is too low, the driver must plan frequent stops to recharge his vehicle at charging stations. Recharging a battery from a state of charge of 20% to 80% can take between 15 minutes and 40 minutes, depending on the electric vehicle model and the chargers used at the charging station.

[0007] Today, most electric vehicles allow a highway range of around 250 km, but at speeds lower than 130 km / h, notably speeds between 110 km / h and 120 km / h.

[0008] The most efficient vehicles according to this criterion offer a range of 420 km at 110 km / h and at an outside temperature of 23°C.

[0009] However, to achieve the aforementioned objective of 300 km of autonomy at 130 km / h, it would be necessary to be able to achieve 450 km at 110 km / h for an outside temperature of 23°C.

[0010] In order to improve the driving comfort felt by the driver depending on the autonomy allowed by his electric vehicle, car manufacturers seek to improve one or more of the following parameters: - the efficiency of the vehicle, making it possible to limit its consumption, expressed in kilowatt hours, kWh, per 100km, in particular by improving the components and aerodynamics of the electric vehicle; - the ability to load more energy into the electric vehicle battery; and / or - the ability to recharge quickly at fast charging stations, via tools route planning or more efficient charging systems.

[0011] All these solutions lead to enriching the motor vehicle, in particular its weight, its price and its complexity, without seeking external or "off-site" solutions, linked in particular to the recharging infrastructure.

[0012] There are methods for evaluating highway traffic, based on different types of factors, including: - on inductive loop sensors, which can be embedded in a roadway at regular intervals to detect the presence of vehicles by measuring changes in an electromagnetic field as vehicles pass over the roadway. Such sensors are deployed to calculate the number of vehicles, their respective speeds and traffic density; - on surveillance cameras, installed along the highway, which allow continuous monitoring of traffic. The images acquired are analyzed to count vehicles, assess traffic density and monitor traffic conditions; - on vehicle detection sensors, of the infrared, acoustic or laser types, which can be used to detect the presence of vehicles on a road and measure their respective speeds; - on electronic toll systems, distributed along a motorway and which record the number of vehicles passing through each toll point.

[0013] Once this data is collected, it is processed by computer systems to generate real-time traffic information, such as the average speed on a highway or section, the traffic density on a highway or section, and travel times.

[0014] Real-time traffic information may be displayed on electronic traffic signs in the road infrastructure, or may be disseminated to drivers of motor vehicles via navigation applications, websites or traffic information systems. The generated traffic information is thus used to efficiently manage traffic, plan road maintenance interventions and / or prevent traffic jams.

[0015] However, such traffic information is generic and does not distinguish between vehicle types, in particular vehicle engine types.

[0016] As mentioned previously, electric vehicles have specific needs, linked in particular to their autonomy, charging times and the availability of charging stations.

[0017] Moreover, although the penetration rate of electric vehicles is relatively low in Europe to date, it is progressing year on year much faster than the number of charging stations in the electric charging infrastructure. Thus, while Although it is currently easy for an electric vehicle driver to travel a long distance without having to wait a long time at a charging station that would be used for other electric vehicles, projections indicate that charging stations will soon become congested.

[0018] There is thus a need to have information, if possible in real time, on the specific traffic of electric vehicles, in order in particular to use such information for navigation applications and / or to directly inform drivers of electric vehicles so that they adapt their route choices accordingly.

[0019] The present invention improves the situation.

[0020] To this end, a first aspect of the invention relates to a method for generating electric vehicle traffic information, the method comprising the following steps: - obtaining traffic data associated with at least one section of at least one road; - determination of an indicator of the use of the section by electric vehicles; - allocation of the determined attendance indicator to a section identifier in a database; - generation of electric vehicle traffic information from the database.

[0021] Thus, specific traffic information for electric vehicles is generated, this data being able to be used so that drivers of electric vehicles can anticipate the recharging of the vehicle. Indeed, dense traffic in electric vehicles indicates an increased risk that the electric recharging stations will be saturated, and that the waiting time to recharge the vehicle battery will be significant.

[0022] According to embodiments, traffic data can be obtained for several sections of at least one road, and, for each section, a given traffic indicator can be determined and assigned to a section identifier in the database. The generation of electric vehicle traffic information comprises the generation of map information based on the traffic indicators respectively assigned to the sections in the database.

[0023] Such mapping is particularly useful for the driver of an electric vehicle or for a navigation application, so as to optimize the entire journey of an electric vehicle based on the electric vehicle traffic information on the different sections to be covered during the journey.

[0024] According to embodiments, the traffic data associated with a section may include descriptive data of vehicles passing through a gantry during a given period, the gantry being on the section, and the indicator of use of the section by electric vehicles may be determined based on the descriptive data of vehicles passing through the gantry during a given period.

[0025] Thus, it is possible to determine in real time the traffic indicator of a section.

[0026] In addition, the descriptive vehicle data may include identifiers of vehicles crossing the gantry during the given period, the method may further include obtaining a type of motorization for each vehicle identifier obtained, and the indicator of frequency of the section by electric vehicles may be determined based on the types of motorization obtained.

[0027] Thus, it is permissible to use a simple collection device, such as a camera, to obtain vehicle descriptive data, which only allows a vehicle to be identified. The identification may be a unique identification such as a registration number, or may be a model identifier of each vehicle passing through the gantry.

[0028] According to embodiments, the indicator of use of the section by electric vehicles may comprise a rate of use of the section by electric vehicles among all the vehicles traveling on the section during a given period and / or a density of electric vehicles on the section during the given period.

[0029] Such indicators are particularly relevant because they represent the risk of waiting at a charging station.

[0030] According to embodiments, generating electric vehicle traffic information comprises comparing the traffic indicator with at least one threshold, and determining a traffic level from a predetermined set of traffic levels, based on a result of the comparison.

[0031] Thus, the traffic information generated is easily understandable by a driver, which facilitates decision-making when driving the electric vehicle, and thus enhances the safety associated with driving the electric vehicle.

[0032] In addition, the attendance indicator may be the density of electric vehicles on the section during the given period, and the attendance level may be a level of density of electric vehicles among several predefined levels of density of electric vehicles.

[0033] Thus, the attendance information is easily understandable by a driver of an electric vehicle and relevant for determining a route allowing rapid recharging of the battery of the electric vehicle.

[0034] According to embodiments, the method may further comprise implementing an electric vehicle function from the generated electric vehicle traffic information, the function being a navigation function, an information display function in a passenger compartment of the electric vehicle or a display function on an electronic traffic panel of a road infrastructure.

[0035] Thus, the generated traffic information can be used to assist in driving an electric vehicle, for example for navigation assistance.

[0036] A second aspect of the invention relates to a computer program comprising instructions for implementing the method according to the first aspect of the invention, when these instructions are executed by a processor.

[0037] A third aspect of the invention relates to a server comprising: - an interface capable of communicating with at least one collection device for obtaining traffic data associated with at least one section of at least one road; - a processor configured to determine an indicator of frequency of the section by electric vehicles and to assign the determined frequency indicator to an identifier of the section in a database, to generate electric vehicle traffic information.

[0038] Other characteristics and advantages of the invention will appear on examining the detailed description below, and the appended drawings in which:

[0039] [Fig. 1] illustrates a computer system for generating electric vehicle traffic information, according to embodiments of the invention;

[0040] [Fig.2] a method for generating electric vehicle traffic information, according to embodiments of the invention;

[0041] [Fig.3] illustrates a map representing vehicle traffic information electrical, according to embodiments of the invention;

[0042] [Fig.4] illustrates the structure of a traffic data collection server, according to embodiments of the invention.

[0043] [Fig.l] illustrates a computer system 100 for generating electric vehicle traffic information, according to embodiments of the invention.

[0044] The computer system 100 is capable of generating electric vehicle traffic information, relating to at least one section 121 of a road 120 of a road network. Preferably, the computer system 100 according to the invention is capable of generating electric vehicle traffic information for several sections of at least one road, and in particular for several sections of several roads of the road network.

[0045] The computer system 100 can in particular generate traffic information of electric vehicles for all roads in a given territory, and preferably for all roads on which vehicles are authorized to travel at a high authorized speed, in particular above 100 km / h, for example expressways and / or motorways in a given territory, the given territory being able to be an entire region or an entire country.

[0046] In the following, to simplify the description of the invention, the example of generating traffic information for electric vehicles on section 121 of road 120 shown in [Fig.l] is considered.

[0047] The term "section" means a portion of the road delimited by two longitudinal positions forming the ends of the section. For example, a section may be a portion of the road between two gantries each comprising a traffic data collection device according to the invention.

[0048] In [Fig.l], the section 121 is delimited by a first gantry 122.1 associated with a first collection device 123.1 and by a second gantry 122.2 associated with a second collection device 123.2.

[0049] The section 120 may have a length, corresponding to the distance to be covered between the first gantry 122.1 and the second gantry 122.2, which is noted D in the following.

[0050] In a given direction of travel, a vehicle traveling on road 120 crosses the first gantry 122.1 then the second gantry 122.2 after having traveled the distance D.

[0051] Thus, in the given direction of circulation, the first collection device 123.1 is capable of obtaining traffic data relating to the traffic entering the section 121.

[0052] The second collection device 123.2 is capable of obtaining traffic data relating to outgoing traffic on the section 121 and relating to incoming traffic on a following section, not shown in [Fig.l].

[0053] No restriction is attached to the collection devices 123.1 and 123.2, which may be any collection device capable of acquiring traffic data making it possible to distinguish the traffic of electric vehicles from the traffic of other types of vehicle motorization.

[0054] For example, the traffic data may be descriptive data of the vehicles passing through the gantry associated with the collection device. The descriptive data may for example be: - a model of each identified vehicle; and / or - a unique vehicle identifier such as a registration plate of each identified vehicle.

[0055] For this purpose, each collection device may comprise a camera associated with an analysis module capable of, from the images captured by the camera: - detect one or more vehicles in each analyzed image; - count the vehicle(s) in each analyzed image; - determine the descriptive data of the vehicle(s) in each analyzed image.

[0056] The descriptive data of all the vehicles identified during a given period can be transmitted to a server 110, which can be common to at least two collection devices, such as the first collection device 123.1 and the second collection device 123.2. Advantageously, the server 110 can collect the descriptive data from N collection devices, dedicated to N sections, of one or more roads in a given territory, N being greater than or equal to 1. N can be equal to several tens or even several hundreds according to the invention.

[0057] According to the invention, each collection device can be a camera arranged on the gantry associated with it.Please note that each gantry can be equipped with a camera arranged for a first direction of traffic, facing vehicles arriving on a section, and another camera arranged for a second direction of traffic, facing vehicles leaving this same section.

[0058] For the sake of simplification, in the following, only vehicles traveling on road 120 in the direction of travel from the first gantry 122.1 to the second gantry 122.2 are considered.

[0059] According to the invention, the server 110 is capable of determining an indicator of attendance of the section 121 by electric vehicles from the traffic data received from the first collection device 123.1.

[0060] The indicator of attendance of the section 121 by electric vehicles may comprise a rate of attendance of the section by electric vehicles among all the vehicles traveling on the section during a given period and / or a density of electric vehicles on the section during the given period.

[0061] For this purpose, when the traffic data received are descriptive data of the vehicles having passed through the first gantry 122.1 during a given period, the server 110 can determine the rate of use by electric vehicles among all the vehicles traveling on the section 121, in the following manner: - if the descriptive data indicates a vehicle model for each vehicle detected during the given period, the server 110 can consult a first database 130 which can store in association vehicle models with their respective engine types. The server 110 then determines the ratio between the number of vehicles whose engine type is electric, and the total number of vehicles having passed through the first gate 122.1 during the given period; - if the descriptive data indicates unique identifiers, such as registration numbers, of vehicles detected during the given period, the server 110 can consult the first database 130 which can store in association registration numbers with their respective engine types. The server 110 then determines the ratio between the number of vehicles whose engine type is electric, and the total number of vehicles having passed the first gate 122.1 during the given period

[0062] The engine type may equivalently indicate the type of fuel used by the vehicle, which may be from a predetermined set of fuel types such as gasoline, diesel, electricity, and natural gas, for example.

[0063] Thus, a first indicator of the use of section 121 by electric vehicles may be the rate of use of section 121 by electric vehicles among all the vehicles having passed through the first gate 123.1 during a given period.

[0064] Furthermore, in addition or as a variant, the server 110 can determine a second indicator of attendance of the section 121 which is a density of electric vehicles on the section 121 during the given period.

[0065] For this purpose, the server 110 can estimate the travel time of each vehicle on the section 121. Such a travel time can be estimated, for simplification, by considering that all the vehicles on the section travel at the maximum speed authorized on the section, for example 130 km / h. The travel time on the section 121 is then obtained by dividing the length D of the section 121, which can be stored in a memory of the server 110, by the maximum authorized speed.

[0066] The server 110 then determines the total density of vehicles on the section 121, for example by the following formula: 7—= Density.dictm fie ( vehicles / unit of length ) Length of the three-part section J ' o /

[0067] The traffic density specific to electric vehicles can then be obtained by multiplying the total traffic density by the rate of use of section 121 by electric vehicles, i.e. the first indicator presented previously.

[0068] After their determination, the server 110 can then assign the indicator of frequency of the section by electric vehicles, or the frequency indicators, in association with an identifier of the section 121, in a second database 140.

[0069] The second database 140 may be common to several servers similar to the server 110 described previously, each server 110 being in charge of a given road or a given set of roads, for example all the roads in a given territory. It is thus possible to centralize in the second database 140 indicators of use by electric vehicles of sections of road in a large territory, for example a region or a country.

[0070] In addition, each server 110 updates the frequency indicators in real time quentation by electric vehicles which are stored in the second database 140 in association with respective section identifiers.

[0071] The second database 140 thus makes it possible to keep up to date in real time data representing an inventory of the use of road sections by electric vehicles.

[0072] Note that the second database 140 can be integrated into the server 110, in particular when the server 110 is a centralized server capable of receiving traffic data from a large number of collection devices in a given territory.

[0073] Thus, the data stored in the database 140 allows the generation of electric vehicle traffic information. The electric vehicle traffic information thus generated can be: - communicated to one or more electric vehicles, for displaying electric vehicle traffic information, on a screen of the electric vehicle(s); - operated by an application server 160 associated with a navigation application, which can be executed in electric vehicles, on-board, or remotely via a cellular network; - communicated to electronic road infrastructure traffic signs.

[0074] Thus, the electric vehicle traffic information allows the navigation application and / or the electric vehicle driver to select, or suggest, the route: - the least dense in electric vehicles, or - which includes the fewest electric vehicles, or; - which includes the fewest electric vehicles per charging station, or - according to any other criterion allowing the risk of waiting at an electric charging station to be limited.

[0075] The traffic information may take the form of a map, as shown in particular in [Fig.3] described below.

[0076] In the following, examples of situations for which indicators of use of section 121 by electric vehicles are determined are given for illustrative purposes.

[0077] In these situations, it is considered, for simplification, that the section 121 has a length D of 2167 meters, that is to say a length such that at 130 km / h, a vehicle travels the length D of the section 121 in one minute.

[0078] In a first situation, 500 vehicles are detected, in the traffic data, as having crossed the first gate 122.1 over a first period of one minute, between 8 a.m. and 8:01 a.m. Among these 500 vehicles, the server 110 determines, from traffic data, that 75 are electric vehicles, therefore associated with a type of electric motorization in the first database 130.

[0079] The first indicator, which is the rate of use of electric vehicles among all vehicles on section 121, over the first period, is therefore 15%.

[0080] On this same section 121, at a second period of one minute between 1 Ih and 1 Ih0l, 800 vehicles are detected in the traffic data as having crossed the first gantry 122.1. Among these 800 vehicles, the server 110 determines that 300 are electric vehicles, therefore associated with a type of electric motorization in the first database 130.

[0081] The first indicator for the second period is therefore 37.5%.

[0082] Such a first indicator indicates that the traffic of electric vehicles is increasing, with a risk of charging station congestion on section 121 or after section 121.

[0083] Concerning the second indicator, as indicated previously, it can be considered, for simplification, that the vehicles travel at 130 km / h on section 121 and that, consequently, each vehicle travels section 121 in one minute, the length D being equal to 2167 meters.

[0084] It is also considered, for the sake of simplification, that each car has a length of 5 meters, which means that one lane of section 121 can accommodate 2167 / 5, or a maximum of 433 cars. Considering that section 121 comprises two lanes in the direction of travel from the first gantry 122.1 to the second gantry 122.2, the maximum capacity of the section is 866 cars.

[0085] The theoretical maximum density of section 121 is therefore 433 / 2167 or 0.20 vehicles per meter.

[0086] During the first period between 8 a.m. and 8:01 a.m., 500 vehicles having passed through the first gantry 122.1, the total traffic density is - 0.1 vehicle / meter, which represents 55% of the theoretical maximum density, and which can be assimilated to moderate density traffic. Total traffic density levels can in fact be predefined and associated with ranges of total traffic density values, for example: - between 0 and 25% of the maximum traffic density: low total traffic density level; - between 25% and 65% of the maximum traffic density: moderate traffic density level; - between 65% and 85% of the maximum traffic density: high total traffic density level; - between 85% and 100% of the maximum traffic density: total saturated traffic density level.

[0087] Such values are given for illustrative purposes only, and no restrictions are attached to these values, nor to the number of predefined total traffic density levels.

[0088] By determining the frequency rate of electric vehicles over this first period, the server 110 can estimate a density of electric vehicles, by multiplying the total traffic density by the frequency rate of electric vehicles: i.e. 0.11*15%=0.0165 vehicles per meter, which can be likened to a low density of electric vehicles. Indeed, the server 110 or any entity accessing the second database 140 can predefine levels of density of electric vehicles in association with ranges of values of density of electric vehicles, for example: - between 0 and 0.01: very low level of density of electric vehicles; - between 0.01 and 0.05 electric vehicles per meter: low level of electric vehicle density; - between 0.05 and 0.1 electric vehicles per meter: moderate or high level of electric vehicle density; - more than 0.1 electric vehicle per meter: saturated electric vehicle density level.

[0089] Such values are given for illustrative purposes only, and no restrictions are attached to these values, nor to the number of electric vehicle density levels.

[0090] An estimate of waiting time at a charging station can be determined based on such electric vehicle density levels, for example: - little or no waiting at charging stations for very low and low densities of electric vehicles; - moderate risk of waiting at charging stations for moderate or high density of electric vehicles; - significant risk of waiting at charging stations due to the saturated density of electric vehicles.

[0091] By determining such electric vehicle traffic information on several sections of several roads, and making this information accessible to a navigation application and / or directly to drivers of electric vehicles, it is permitted: - individually for the electric vehicle driver to choose a route for which the waiting time at the charging station is low or moderate; - from a global point of view, to reduce waiting times at charging stations by facilitating the distribution of electric vehicles between the different charging stations in an area.

[0092] [Fig.2] illustrates the steps of a method for generating electric vehicle traffic information, according to embodiments of the invention.

[0093] In a step 200, traffic data collected by one or more collection devices are obtained by the server 110. In the example described above, the traffic data are at least obtained from the first collection device for the section 121. Furthermore, as described above, the traffic data may be descriptive data of vehicles. In this case, step 200 may also comprise the querying of the first database 130 by the server 110, in order to obtain respective engine types of the vehicles detected and identified in the descriptive data obtained from the collection device(s).

[0094] In a step 201, the server 110 determines at least one indicator of attendance by electric vehicles, for at least one section, in particular for the section 121 in the example described previously. As described previously, the at least one indicator may comprise a first indicator which is a rate of attendance of the section by electric vehicles among all the vehicles and / or a second indicator which is a density of electric vehicles on the section.

[0095] In a step 202, the at least one indicator of attendance by electric vehicles determined for at least one section is stored in the second database 140 in association with an identifier of the section concerned.

[0096] When the server 110 receives traffic data from several collection devices, steps 200 to 202 are implemented for each set of traffic data received from a collection device. Furthermore, steps 200 to 202 may be iterated at a given frequency, so as to keep the second database 140 updated with traffic indicators determined in real time.

[0097] In a step 203, electric vehicle traffic information is generated from the data stored in the second database 140. Any entity capable of accessing the second database 140 can generate such traffic information: it may be the server 110, the application server 160, or any other entity, equipment or server, capable of accessing the second database 160.

[0098] The traffic information may include a level of density of electric vehicle traffic of a section, obtained by comparing the second indicator associated with the section with at least one predetermined threshold.

[0099] Electric vehicle traffic information may be generated after aggregating traffic indicators for several sections of several roads. The traffic information thus generated may take the form of a map, which may be used by a navigation function as described in [Fig.3] described below.

[0100] In a step 204, a function for an electric vehicle is implemented, from generated electric vehicle traffic information, the function being a navigation function, an information display function in a passenger compartment of the electric vehicle or a display function on an electronic traffic sign of a road infrastructure.

[0101] [Fig.3] illustrates electric vehicle traffic information generated by an application server 160 associated with a navigation function for electric vehicles, from data stored in the second database 140 according to the invention.

[0102] The electric vehicle traffic information may take the form of a map 300, representing a given territory, for example a country or a region.

[0103] The navigation function is adapted to receive an input entered by a user of the electric vehicle in which it is executed, the input indicating descriptive information of a destination 302, which is placed on the map 300. A starting position 301 is further placed on the map 300, corresponding to a current position of the electric vehicle, or to a starting position indicated in another input entered by the user.

[0104] The navigation function may determine two routes, comprising a first route 310 and a second route 320, each route comprising a series of road segments connecting the starting position 301 to the destination 302.

[0105] The first route 310 comprises a first section 311, a second section 312 and a third section 313. The sections 311 to 313 may be of a single route, or of several distinct routes.

[0106] The second route 320 comprises a first section 321, a second section 322 and a third section 323. The sections 321 to 323 may be of a single route, or of several distinct routes.

[0107] Each segment may be displayed as darker or lighter depending on the total traffic density level. For example, the three segments 311 to 313 of the first route 310 may indicate a high total traffic density level. The first two segments 321 and 322 indicate a moderate total traffic density level, while the third segment 323 indicates a high total traffic density level. The total traffic density levels may be determined from data stored in the second database 140, in addition to the electric vehicle ridership indicators.

[0108] Furthermore, according to the invention, the second indicator indicating a level of density of electric vehicles can be displayed, in the form of a gauge for example, for at least some of the sections of the two journeys.

[0109] Thus, on the first route 310, the first section 311 is associated with a first gauge 314.1 indicating a high level of density of electric vehicles and the second section 312 is associated with a second gauge 314.1 indicating a level moderate density of electric vehicles.

[0110] As for the second route 320, the first section 321 is associated with a first gauge 324.1 indicating a moderate level of density of electric vehicles, the second section 322 is associated with a second gauge 324.2 indicating a moderate level of density of electric vehicles, and the third section 323 is associated with a third gauge 324.3 indicating a saturated level of density of electric vehicles.

[0111] The driver can thus detect that there is a high risk of waiting at a charging station on the third section 323 of the second journey 320.

[0112] Displaying the overall density level in addition to the density level of electric vehicles allows several factors to be taken into account when choosing a route to a destination: it may in fact be desired to select the route offering the best compromise between travel time and ease of recharging the vehicle's battery without waiting too long.

[0113] [Fig.4] shows the structure of a server 110 according to embodiments of the invention.

[0114] The server 110 comprises a processor 401 configured to communicate unidirectionally or bidirectionally, via one or more buses or via a direct wired connection, with a memory 402 such as a memory of the “Random Access Memory” type, RAM, or a memory of the “Read Only Memory” type, ROM, or any other type of memory (Flash, EEPROM, etc.). Alternatively, the memory 402 comprises several memories of the aforementioned types.

[0115] The memory 402 is capable of storing, permanently or temporarily, at least some of the data used and / or resulting from the implementation of steps 200 to 202, and step 203 when it is implemented by the server 110.

[0116] According to some embodiments of the invention, the memory 402 may include the second database 140 previously described.

[0117] The processor 401 is capable of executing instructions, stored in the memory 402, for implementing the steps of the method 200 to 202, and step 203 when it is implemented by the server 110, according to the invention, described with reference to [Fig. 2]. Alternatively, the processor 401 can be replaced by a microcontroller designed and configured to carry out the aforementioned steps of the method according to the invention, described with reference to [Fig. 2].

[0118] The server 110 comprises a first interface 403 capable of obtaining traffic data from at least one collection device as previously described. Preferably, the first interface 403 is capable of obtaining traffic data from several road sections from a plurality of collection devices.

[0119] The server 110 further comprises a second interface 404 capable of communicating with the first database 130, in particular to query the first database 130 in order to obtain engine types from vehicle descriptive data.

[0120] The server 110 further comprises a third interface 405 capable of communicating with the second database 140, when the second database 140 is external to the server 110, in particular in order to store the indicators of section use by electric vehicles, in association with the identifiers of the sections concerned.

[0121] The present invention is not limited to the embodiments described above as examples; it extends to other variants.

Claims

Claims

1. Method for generating electric vehicle traffic information (150), the method comprising the following steps: - obtaining (200) traffic data associated with at least one section (121) of at least one road (120); - determining (201) a frequency indicator (314.1; 314.2; 324.1; 324.2; 324.3) of the section by electric vehicles; - assigning (202) the determined frequency indicator to an identifier of the section in a database (140); - generating (203) electric vehicle traffic information (300) from the database.

2. Method according to claim 1, wherein traffic data are obtained (200) for several sections (121) of at least one road (120), wherein, for each section, a given traffic indicator (314.1; 314.2; 324.1; 324.2; 324.3) is determined and assigned to an identifier of the section in the database (140), and wherein the generation of electric vehicle traffic information comprises the generation of map information (300) according to the traffic indicators respectively assigned to the sections in the database.

3. Method according to one of the preceding claims, in which the traffic data associated with a section comprise descriptive data of vehicles crossing a gantry (122.1; 122.2) during a given period, the gantry being on the section (121), and in which the indicator of frequentation of the section by electric vehicles is determined as a function of the descriptive data of the vehicles crossing the gantry during a given period.

4. Method according to claim 3, in which the vehicle descriptive data comprises identifiers of vehicles crossing the gantry (122.1; 122.2) during the given period, in which the method further comprises obtaining a type of motorization for each vehicle identifier obtained, in which the indicator of frequency of the section by electric vehicles is determined according to the types of motorization obtained.

5. Method according to one of the preceding claims, in which the indicator of attendance of the section (121) by electric vehicles comprises a rate of attendance of the section by the electric vehicles among all vehicles circulating on the section during a given period and / or a density of electric vehicles (314.1; 314.2; 324.1; 324.2; 324.3) on the section during the given period.

6. Method according to one of the preceding claims, in which the generation (203) of information (300) on electric vehicle traffic further comprises comparing the traffic indicator with at least one threshold, and determining a traffic level from among a predetermined set of traffic levels, based on a result of the comparison.

7. A method according to claim 6 and claim 5, the attendance indicator is the density of electric vehicles on the section during the given period, and the attendance level is one of several predefined electric vehicle density levels.

8. Method according to one of the preceding claims, further comprising implementing (204) an electric vehicle function from the generated electric vehicle traffic information, the function being a navigation function (160), an information display function in a passenger compartment of the electric vehicle (150) or a display function on an electronic traffic panel of a road infrastructure.

9. Computer program comprising instructions for implementing the method according to one of the preceding claims, when these instructions are executed by a processor (401).

10. Server comprising: - an interface (401) capable of communicating with at least one collection device (123.1; 123.2) for obtaining traffic data associated with at least one section (121) of at least one road (120); - a processor (402) configured to determine a frequency indicator (314.1; 314.2; 324.1; 324.2; 324.3) of the section by electric vehicles and assign the determined frequency indicator to an identifier of the section in a database, to generate traffic information (300) of electric vehicles.

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