Patent Application
20200234572
The present invention relates to a platform for supervising an infrastructure for transport vehicles, in particular autonomous, at least one target vehicle comprising an obstacle detection module of predetermined range and a geolocation module that are embedded, said target vehicle being configured to follow a predefined route on the infrastructure.
The invention also relates to a vehicle, in particular autonomous, that is capable of moving on an infrastructure for transport vehicles that is supervised by such a supervision platform, at least one target vehicle comprising an obstacle detection module with a predetermined field of view and a geolocation module that are embedded, said target vehicle being configured to follow a predefined route on the infrastructure.
The invention also relates to a transport system comprising a fleet of vehicles, in particular autonomous, that are capable of moving on an infrastructure for transport vehicles, the fleet of vehicles comprising at least one target vehicle comprising an obstacle detection module with a predetermined field of view and a geolocation module that are embedded, said target vehicle being configured to follow a predefined route on the infrastructure.
The invention also relates to a vehicle, in particular autonomous, that is capable of moving on an infrastructure for transport vehicles that is supervised by such a supervision platform, at least one target vehicle comprising an obstacle detection module with a predetermined field of view and a geolocation module that are embedded, said target vehicle being configured to follow a predefined route on the infrastructure.
The invention also relates to a computer program including software instructions which, when executed by a computer, implement such a supervision method.
The invention relates to the field of the supervision of a fleet of transport vehicles on an infrastructure, in particular road or rail, and particularly the field of automatic driving of autonomous transport vehicles.
Indeed, in the field of the secure driving of vehicles, and in particular in autonomous driving (that is to say, autonomous piloting), one of the main issues is the early identification of obstacles on the path of a moving vehicle, making it possible to take corrective measures so that the vehicle does not strike these obstacles, as well as the transmission of information between each vehicle in the fleet and a corresponding piece of electronic equipment to a remote supervision platform of the fleet of motor vehicles.
The considered obstacles are of any type, for example stationary obstacles, such as safety railings, parked vehicles, or moving obstacles, for example other vehicles or pedestrians. It will be understood that it is critical to avoid any collision between a moving vehicle and such obstacles, and also to ensure a proper transmission of information between each vehicle and the supervision equipment.
Vehicles are known that are each equipped with at least one obstacle detection module configured to detect any obstacle entering its field of vision. However, such obstacle detection implemented by the vehicle alone is limited by the field of view of the obstacle detection module that it comprises.
Furthermore, vehicle driving assistance collective perception systems are known comprising communication devices able to identify obstacles in a circulation area via sensors, installed in the road and/or embedded in a plurality of separate vehicles, and able to inform the supervision platform thereof remotely. The remote supervision platform is able to determine and send a setpoint to a vehicle circulating in said road circulation area.
However, the transmission of this information from the platform to the vehicle is not always satisfactory, the quantity of collective perception data collected by the supervision platform to be relayed via the datalink sometimes being too substantial for the available bandwidth.
The aim of the invention is to resolve the drawbacks of the state of the art by proposing a more effective remote supervision platform, in particular in case of limited data throughput of the communication link established with each supervised vehicle.
To that end, the invention relates to a platform for supervising an infrastructure for transport vehicles, in particular autonomous, at least one target vehicle comprising at least one obstacle detection module with a predetermined field of view and a geolocation module that are embedded, said target vehicle being configured to follow a predefined route on the infrastructure, the platform comprising:
an analysis and regulating module configured to determine whether, at the current moment, the external element is in the field of view or outside the field of view of the obstacle detection module of the target vehicle, and configured to generate and send a driving setpoint to at least one vehicle on the infrastructure when the external element is outside the field of view of the obstacle detection module of the target vehicle.
Thus, with the supervision platform according to the invention, a driving setpoint is sent to at least one vehicle on the infrastructure that it supervises only when an external element, detected in a safety zone comprising the predefined route of a target vehicle, is outside the field of view of the obstacle detection module embedded in this vehicle.
In other words, the supervision platform makes it possible to anticipate any obstruction, in particular temporary, of the field of view of the obstacle detection module embedded in the target vehicle while filtering the quantity of collective perception data collected for example via sensors, installed in the road and/or embedded in a plurality of separate vehicles.
The supervision platform according to the invention is therefore improved relative to the supervision platform of the state of the art in particular through its analysis and regulation module, which is configured to systematically implement processing of the received data in order to limit the generation of driving setpoint(s) to be transmitted by making it subject to the meeting of a double condition, namely that the detected external element, in particular for example by a collective perception, is both in the predetermined safety zone comprising the predefined route of a target vehicle and outside the field of view of the obstacle detection module embedded in this same target vehicle.
According to other advantageous aspects of the invention, the supervision platform comprises one or more of the following features, considered alone or according to any technical possible combinations:
when the element external to the target vehicle is moving, the acquisition module is also configured to receive speed and/or acceleration information associated with the information representative of the presence of the external element;
the analysis and regulation module comprises a prediction tool configured to supply a prediction of the route of the external element and/or at least one prediction of a spatial-temporal contact position between the external element and the target vehicle on the predefined route;
the spatial-temporal position corresponds to an elliptical zone and wherein the prediction tool comprises an instrument for calculating parameters of the elliptical zone, the surface of the elliptical zone being proportional to a degree of uncertainty associated with the prediction supplied by the prediction tool;
the analysis and regulation module comprises a verification tool configured to verify, at least at one moment after the current moment, the validity of the prediction(s), and configured to adapt the driving setpoint to the later moment as a function of said validity;
the platform is configured to classify the external element according to several categories comprising at least:
another vehicle, separate from the target vehicle,
traffic congestion,
a pedestrian or group of pedestrians,
a bicyclist or group of bicyclists,
a construction or restricted traffic zone,
a weather phenomenon,
a natural obstacle,
and to adapt the type of setpoint based on the category of external element.
The invention also relates to a vehicle, in particular autonomous, configured to move on an infrastructure for transport vehicles supervised by a supervision platform according to any one of the preceding claims, at least one target vehicle comprising at least one obstacle detection module with a predetermined field of view and a geolocation module that are embedded, said target vehicle being configured to follow a predetermined route on the infrastructure,
said vehicle comprising a reception and processing module configured to receive and process a driving setpoint sent by the supervision platform in the presence of an external element both in a predetermined safety zone comprising the predetermined route and outside the field of view of the obstacle detection module of the target vehicle.
The invention also relates to a transport system comprising a fleet of vehicles, in particular autonomous, that are capable of moving on an infrastructure for transport vehicles, the fleet of vehicles comprising at least one target vehicle comprising at least one obstacle detection module with a predetermined field of view and a geolocation module that are embedded, said target vehicle being configured to follow a predefined route on the infrastructure,
further comprising a supervision platform as previously described and in that at least one vehicle of the fleet of vehicles comprises a reception and processing module configured to receive and process a driving setpoint sent by the supervision platform in the presence of an external element both in a predetermined safety zone comprising the predetermined route and outside the field of view of the obstacle detection module of the target vehicle.
The invention relates to a method for supervising an infrastructure for transport vehicles, in particular autonomous, at least one target vehicle comprising at least one obstacle detection module with a predetermined field of view and a geolocation module that are embedded, said target vehicle being configured to follow a predefined route on the infrastructure, the method being implemented by a platform for supervising the infrastructure for transport vehicles, in particular autonomous, at least one target vehicle comprising at least one obstacle detection module with a predetermined field of view and a geolocation module that are embedded, said target vehicle being configured to follow a predefined route on the infrastructure, the method being implemented by a supervision platform of the infrastructure, the method comprising the following steps:
determining whether, at the current moment, the external element is in the field of view or outside the field of view of the obstacle detection module of the target vehicle, then generating and sending a driving setpoint to at least one vehicle on the infrastructure when the external element is outside the field of view of the obstacle detection module of the target vehicle.
The invention also relates to a computer program including software instructions which, when executed by a computer, implement a supervision method as defined above.
These features and advantages of the invention will appear more clearly upon reading the following description, provided solely as a non-limiting example, and done in reference to the appended drawings, in which:
In the rest of the description, the expression “substantially equal to” designates a relationship of equality to within plus or minus 10%, preferably to within plus or minus 5%.
In
In the example of
Such an autonomous vehicle 12A comprises, in a known manner, front wheels, rear wheels, a motor (not shown) mechanically connected via a transmission chain to the front and/or rear wheels for the driving of said wheels in rotation around their axis, a steering system (not shown), suitable for acting on the front and/or rear wheels of the autonomous vehicle 12A so as to modify the orientation of its trajectory, and a braking system (not shown), suitable for exerting a braking force on the wheels of the autonomous vehicle 12A.
One skilled in the art will then understand that the vehicle 12A is shown from above in the schematic view of
According to the invention, such an autonomous vehicle 12A is provided with at least one obstacle detection module 16, the field of view 18 of which is predetermined and known by the supervision platform 14.
Such an obstacle detection module 16 for example comprises one or several sensors embedded within the vehicle corresponding to an image sensor, that is to say, a photosensor or a camera or chosen from the group of sensors comprising at least: a lidar (light detection and ranging), a leddar (light-emitting diode detection and ranging), a radar (radio detection and ranging) and an ultrasound sensor.
Furthermore, as illustrated in
A geolocation module 20 hereinafter refers to an instrument capable of positioning the autonomous vehicle 12A on a plan or map using its geographical coordinates. Such a geolocation module 20 is capable of being located, for example using a satellite positioning system, receiving its geographical position in real time, for example via a GPS receiver, and broadcasting it in real time.
Other geolocation techniques can be used according to the invention, such as geolocation by geocoder, GSM, Wi-Fi, using an inertial unit, a radar or a lidar.
Such geolocation techniques are, according to one specific aspect of the invention, optimized by a map matching technique or a simultaneous localization and mapping (SLAM) technique.
According to one specific aspect of the invention, the geolocation module 20 and the clock H are according to an ASIL D (Automotive Safety Integrity Level) operating safety design effort level, this ASIL D level representing the maximum degree of rigor required to meet the safety requirements associated with a maximum danger level. The ASIL by definition is obtained by multiplying a trio of values respectively representative of three safety criteria, namely the severity, the exposure and the controllability.
In other words, during the design of the autonomous vehicle 12A according to the present invention, the maximum precision level in terms of temporal indication(s) delivered by the clock H and in terms of geographical geolocation precision of the autonomous vehicle 12A delivered by the geolocation module 20 is required.
Hereinafter, autonomous driving module 22 refers to a logic controller suitable for controlling the autonomous vehicle autonomously by receiving information on the environment of the autonomous vehicle 12A by means of sensors, located outside or inside the autonomous vehicle, and by acting on the motor (not shown), the steering system (not shown) and the braking system (not shown) so as to modify the speed and path of the autonomous vehicle 12A in response to the received information and so as to comply with a mission programmed in the logic controller.
In particular, such a mission corresponds to following a predefined path, for example the path followed by a bus or tram line or any other autonomous public transportation means on one or several traffic paths 24, visible in
Furthermore, the autonomous vehicle 12A comprises a reception and processing module 26 configured to receive, via the dedicated link Lv (optionally secure), and process a driving setpoint sent by the supervision platform 14 in the presence of an external element 27 in a predetermined security zone comprising the predefined route and outside the field of view of its own obstacle detection module 16, according to this example, the autonomous vehicle 12A being the target of the supervision implemented by the supervision platform 14. Such a setpoint in particular corresponds to an order, or a deceleration value or change of route, and is subsequently transferred by the reception module 26 to the autonomous driving module 22 for processing and/or application.
As an optional addition, the reception module 26 is also configured to receive information representative of the position of the external element 27 and to verify that the external element 27 is outside the field of view of the obstacle detection module 16 of the autonomous vehicle 12A, which makes it possible to avoid the application of an additional driving setpoint if, after verification, the external element 27 is visible by the obstacle detection module 16 and the autonomous driving module 22 has intrinsically already taken this external element 27 into account to adapt the behavior of the autonomous vehicle 12A.
The supervision platform 14 is a piece of electronic equipment able to supervise remotely, or control remotely, the fleet of motor vehicle(s) 12, the supervision platform also being called PCC (Poste de Commande Central, central control unit).
According to the invention, the supervision platform 14 comprises an acquisition module 28 configured to acquire, at a current moment, at least one piece of information representative of the presence or absence, in the predetermined safety zone comprising the predefined route, of an element external to the target vehicle 12A, and an analysis and regulating module 30 configured to determine whether, at the current moment, the external element is in the field of view or outside the field of view of the obstacle detection module 16 of the target vehicle 12A, and configured to generate and send a driving setpoint to at least one vehicle on the infrastructure when the external element is outside the field of view of the obstacle detection module of the target vehicle 12A.
“Predetermined safety zone” refers to a geographical zone whose surface area is strictly larger than that corresponding to the predefined route.
According to a first variant, the predetermined safety zone has a surface area with a static size extending on either side of the traffic path with a margin substantially equal to 10 m.
According to a second variant, the predetermined safety zone has a surface with a dynamic size proportional to the speed of the target vehicle.
As an optional addition, the analysis and regulation module 30 comprises a prediction tool 32 able to supply a prediction of the route of the external element 27 and/or at least one prediction of a spatial-temporal contact position between the external element 27 and the target vehicle 12A on the predefined route.
According to one specific aspect of this optional addition, the spatial-temporal position corresponds to an elliptical zone and the prediction tool 32 comprises an instrument IC for calculating parameters of the elliptical zone, the surface of the elliptical zone being proportional to a degree of uncertainty associated with the prediction supplied by the prediction tool 32.
For example, the prediction tool 32 comprises a Kalman filter capable of estimating the states of the dynamic external element 27. More specifically, the Kalman filter is capable of predicting parameters corresponding to the position and the speed of the detected external element 27 and capable of calculating the uncertainties of these parameters.
To that end, a two-dimensional representation along a pair of axes (X, Y) of the position of the external element 27 can be implemented by the prediction tool 32 and the Kalman filter calculates a degree of uncertainty in each dimension. Such a degree of Uncertainty is quite simply a possible deviation measurement, or in a variant, the maximum possible deviation, of the estimated position. In particular, if the degree of uncertainty on X is equal to the degree of uncertainty on Y, the spatial-temporal contact position obtained from two degrees of uncertainty corresponds to a circular zone. Conversely, if the external element 27 moves along the axis X, the degree of uncertainty of the prediction of its position along the axis X is greater than that along Y and the spatial-temporal contact position obtained from two degrees of uncertainty corresponds to an elliptical zone.
According to the example of
According to another per specific aspect, the analysis and regulation module 30 comprises a verification tool 38 configured to verify, at least at one moment after the current moment, the validity of the prediction(s), and configured to adapt the driving setpoint to the later moment as a function of said validity.
Such a tool allows the setpoint generation to be governed in real time as a function of the received observation of external element(s).
In the example of
In the example of
The memory 42 of the target vehicle 12A is then able to store first geolocation software to allow the geolocation of the target vehicle 12A, second autonomous driving software suitable for steering the autonomous vehicle autonomously by receiving information on the environment of the autonomous vehicle 12A by means of sensors, located outside or inside the autonomous vehicle, and by acting on the motor (not shown), the steering system (not shown) and the braking system (not shown) so as to modify the speed and path of the autonomous vehicle 12A in response to the received information and so as to comply with a mission programmed in the logic controller, third reception and processing software configured to receive and process a driving setpoint sent by the supervision platform 14 in the presence of an external element 27 both in a predetermined safety zone comprising the predetermined route and outside the field of view of the obstacle detection module of the target vehicle 12A.
The processor 44 is then able to execute each software application from among the first geolocation software, the second autonomous driving software, the third reception and processing software for a driving setpoint sent by the supervision platform 14.
In a variant that is not shown, the geolocation module 20, the autonomous driving module 22 and the reception and processing module 26 are each made in the form of a programmable logic component, such as an FPGA (Field Programmable Gate Array), or in the form of a dedicated integrated circuit, such as an ASIC (Application Specific Integrated Circuit).
When part of the autonomous vehicle 12A is made in the form of one or several software programs, i.e., in the form of a computer program, this part is further able to be stored on a medium, not shown, readable by computer. The computer-readable medium is for example a medium suitable for storing electronic instructions and able to be coupled with a bus of a computer system. As an example, the readable medium is an optical disc, a magnetic-optical disc, a ROM memory, a RAM memory, any type of non-volatile memory (for example, EPROM, EEPROM, FLASH, NVRAM), a magnetic card or an optical card. A computer program including software instructions is then stored on the readable medium.
In the example of
Furthermore, in the example of
In the example of
The memory 48 of the supervision platform 14 is then able to store acquisition software configured to acquire, at a current moment, at least one piece of information representative of the presence or absence, in a predetermined safety zone comprising the predefined route, of an element 27 external to the target vehicle 12A, analysis and regulation software capable of determining whether, at a the current reception moment of a piece of information representative of the presence or absence, in the predetermined safety zone comprising the predefined path, whether the external element 27 is in the field of view or outside the field of view of the obstacle detection module 16 of the target vehicle 12A, and configured to generate and send a driving setpoint to at least one vehicle on the infrastructure when the external element is outside the field of view of the obstacle detection module of the target vehicle.
The processor 50 is then able to execute the acquisition software, the analysis and regulation software and the software tools that it comprises.
In a variant that is not shown, the acquisition module 28, the analysis and regulation module 30 and its tools are each made in the form of a programmable logic component, such as an FPGA (Field Programmable Gate Array), or in the form of a dedicated integrated circuit, such as an ASIC (Application Specific Integrated Circuit).
When part of the supervision platform 14 is made in the form of one or several software programs, that is to say, in the form of a computer program, this part is further able to be stored on a medium, not shown, readable by computer. The computer-readable medium is for example a medium suitable for storing electronic instructions and able to be coupled with a bus of a computer system. As an example, the readable medium is an optical disc, a magnetic-optical disc, a ROM memory, a RAM memory, any type of non-volatile memory (for example, EPROM, EEPROM, FLASH, NVRAM), a magnetic card or an optical card. A computer program including software instructions is then stored on the readable medium.
In the example of
According to the first situation of
The offboard sensor C1 is then configured to escalate instantaneously, or practically instantaneously, via a terminal T1 and a dedicated link LC (wired or wireless (for example, radio)), optionally secured, information representative of the presence of the pedestrian 27 on the platform 14.
The acquisition module 28 of the supervision platform 14 is configured to acquire, from the offboard sensor C1 installed in the road, this information representative of the presence of the pedestrian 27.
According to a variant that is not shown, the acquisition module 28 of the supervision platform 14 is configured to acquire this information representative of the presence of the pedestrian 27, by an avenue other than that associated with the offboard sensor C1, for example by following the mobile terminal of the pedestrian 27.
When the external element corresponds to an imminent weather phenomenon such as a very localized bad weather event, a sheet of ice or a natural obstacle, the information representative of the presence of this specific external element is generated by any other device capable of generating it. For example, such information corresponds to an SMS (short message service) sent by a pedestrian and/or a motorist to notify the supervision platform of a fallen tree after a storm or gale.
As an optional addition, the acquisition module 28 is also configured to acquire speed and/or acceleration information associated with the information representative of the presence of the external element 27.
The analysis and regulation module 30 of the supervision platform 14 is first configured to process this information by using the predetermined safety zone comprising the predefined path of the target vehicle 12A.
For example, when the predefined path of the target vehicle 12A is such that at a moment, after the current moment, it comprises a left turn VG relative to the movement vector K of the target vehicle 12A, the analysis and regulation module 30 is capable of determining that the external element corresponding to the pedestrian 27 is absent from the safety zone.
Conversely, when the predefined path of the target vehicle 12A is such that at a moment, after the current moment, it comprises a right turn VD relative to the movement vector K of the target vehicle 12A, the analysis and regulation module 30 is capable of determining that the external element corresponding to the pedestrian 27 is present in the safety zone.
Furthermore, the analysis and regulation module 30 of the supervision platform 14 is capable of taking account of the geolocation position of the target vehicle 12A obtained using the geolocation module 20 of the target vehicle 12A to determine whether elements of the road are obstructing the field of view 18 of the obstacle detection module 16 embedded in the target vehicle 12A.
In relation with the example of
In this configuration, the obstacle detection module 16 of the target vehicle 12A not “seeing” the external element corresponding to the pedestrian 27, the autonomous driving module 22 cannot anticipate this potentially disruptive external element and automatically adapt the route/speed of the target vehicle 12A.
In the presence of a dual condition corresponding to an external element 27 that is both in the safety zone comprising the predefined path of the target vehicle 12A and outside the field of view 18 of the obstacle detection module 16 of the target vehicle 12A, the analysis and regulation module 30 of the supervision platform 14 generates and transmits a driving setpoint to at least one vehicle in the infrastructure.
According to a first variant, the vehicle receiving the setpoint is the target vehicle 12A.
Alternatively and/or in addition to the first variant, the vehicle receiving the setpoint is a vehicle other than the target vehicle 12A.
According to an optional additional aspect, the external element is configured to be classified by the supervision platform according to the invention according to several categories, comprising at least:
another vehicle, separate from the target vehicle,
a pedestrian 27 or a group of pedestrians GP as illustrated in the exemplary situation of
traffic congestion as illustrated in
a bicyclist or group of bicyclists,
a construction or restricted traffic zone,
a weather phenomenon,
a natural obstacle, such as a tree, a branch, an animal, etc.
According to the second situation of
The target vehicle 12A approaches the supervision site S1, and its obstacle detection module 16 (not shown in
Owing to the present invention, the supervision platform 14 is capable of processing the information representative of the presence of the group of pedestrians GP transmitted by the processing terminal T1 directly connected to the offboard sensor C1. More specifically, the analysis and regulation module 30 of the supervision platform 14 is capable of taking account of the geolocation position of the target vehicle 12A obtained using the geolocation module 20 of the target vehicle 12A to determine that the group of pedestrians GP is located in the safety zone comprising the predefined path of the target vehicle 12A, and that because of the distance separating the target vehicle 12A from the group of pedestrians GP, the group of pedestrians is outside the field of view of the obstacle detection module 16.
According to the third situation of
In other words, the supervision platform 14 in particular allows a transfer to the site S2 of a setpoint taking account of a piece of information relative to the site S1 in which the offboard sensor C1 is in particular configured to escalate, via the terminal T1 and the dedicated link LC, the presence of an external element corresponding to the vehicle 12 that is moving at a high speed such as a police vehicle, an ambulance, a private vehicle.
More specifically, the target vehicle 12A moves from the site S2 toward the site S1 and the supervision platform 14, via the prediction tool 32, is capable of predicting the route of the vehicle 12 from the site S1 and determining that this vehicle 12 appears be moving, in particular at a high speed, toward the site S2.
More specifically, the prediction tool 32 is capable of providing, on a timescale, the successive positions of the vehicle 12 and a spatial-temporal contact position between the vehicle 12 and the target vehicle 12A on the predefined path.
In light of this prediction and the fact that the vehicle 12 located on the site 51 is out of range of the obstacle detection module 16 (not shown in
As an optional addition, the verification tool 38 of the analysis and regulation module 30 of the supervision platform 14 is capable of verifying, in real time, whether these predictions are satisfied and in case of invalidation, modifying or deleting the driving setpoint previously transmitted.
In particular, to perform such a verification, the verification tool 38 of the analysis and regulation module 30 is capable of using information provided by a sensor O2 separate from the sensor C1, which, at the current moment, has provided the information representative of the presence of the vehicle 12 on the predefined path on the site 51.
According to the fourth situation of
According to this fourth situation, the target vehicle 12A is moving from the site S2 toward the site S1, and the offboard sensor C1 is in particular capable of escalating, via the terminal T1 and the dedicated link LC, the presence of an external element corresponding to traffic congestion of four vehicles 12, such as a traffic jam or a traffic accident.
The supervision platform 14 according to this example is capable of classifying the detected external elements and adapting the driving setpoint as a function of the obtained class. According to the fourth situation, because the external element is traffic congestion capable of blocking traffic up to the predicted spatial-temporal contact position between the traffic congestion, corresponding to the four vehicles 12 stopped on the site S1, and the target vehicle 12A, the generated driving setpoint this time corresponds to a change of route and not to a deceleration as applied in the preceding situations.
In other words, according to this aspect, the supervision platform 14 is “smart” and capable of performing a bijective association of an external element class and a setpoint type.
Like for the third situation, the verification tool 38 of the analysis and regulation module 30 of the supervision platform 14 is capable of verifying, in real time, whether these predictions are fulfilled (that is to say, the evolution of the traffic congestion), in particular using a sensor C2 separate from the sensor C1 that supplied, at the current moment, the information representative of the presence of the vehicle 12 on the predefined path on the site S1, and in case of invalidation, modifying or even deleting the driving setpoint previously transmitted.
The operation of the supervision platform 14 according to the invention will now be explained using
During an initial step R, the supervision platform 14 acquires, at a current moment, at least one piece of information representative of the presence or absence, in a predetermined safety zone comprising the predefined route, of an element 27, GP outside the target vehicle 12A.
Optionally, the supervision platform 14 simultaneously acquires speed information, or acceleration information, associated with the information representative of the presence or absence, in a predetermined safety zone comprising the predefined route, of an element 27, GP outside the target vehicle 12A.
The supervision platform 14 next determines, during an analysis and regulating step D, whether, at the current moment, the external element 27, GP is in the field of view or outside the field of view of the obstacle detection module 16 of the target vehicle 12A, and configured to generate and send a driving setpoint to at least one vehicle on the infrastructure when the external element 27, GP is outside the field of view of the obstacle detection module 16 of the target vehicle 12A.
According to optional additional aspects shown in dotted lines, the analysis and regulation step D comprises two intermediate steps:
a step P, in which the prediction tool 32 of the analysis and regulation module 30 supplies at least one prediction of the route of the external element 27, GP and/or at least one prediction of a spatial-temporal contact position between the external element and the target vehicle 12A on the predefined route.
a step E, in which, when the spatial-temporal position corresponds to an elliptical zone, the calculating instrument IC of the prediction tool 32 calculates parameters of the elliptical zone, the surface of the elliptical zone being proportional to a degree of uncertainty associated with the prediction P supplied by the prediction tool.
More specifically, the prediction step P comprises predicting the path of the external element from its position and its speed vector (or its acceleration vector if obtained during the acquisition step R), determining the point of intersection (if one exists) of the path of the external element with the predefined path of the target vehicle and determining the time period TTC that separates the current moment from the moment of arrival of the external element at this point, determining the future position of the target vehicle on its predefined path once the period TTC has elapsed from its dynamic parameters (speed, acceleration, etc.), the risk of a collision being proportional to the distance between this future position and the point of intersection).
Following the analysis and regulation step D, during a step T, the generating tool 34 generates and the transmission tool 36 transmits a driving setpoint to at least one vehicle on the infrastructure when the external element 27, GP is outside the field of view of the obstacle detection module 16 of the target vehicle (12A), such a setpoint being, as previously described, adapted to the situation being supervised.
During an optional subsequent step V, the supervision platform 14 uses its verification tool 38 to verify whether the predictions obtained during step P are valid.
Based on the result of the verification step V during a step S, which is also optional, the supervision platform 14 generates a modification setpoint, or a deletion setpoint for the driving setpoint previously generated.
Thus, the supervision platform 14 according to the invention, while filtering the information acquired using the set of embedded/offboard sensor(s) and monitoring devices to which it is connected and able to assist the target vehicle that it is supervising to allow it, or to allow other vehicles present on the infrastructure, to better anticipate any element that may constitute a potential obstacle and that is not visible by the obstacle detection module 16 embedded in the target vehicle 12A.
One can thus see that the supervision platform 14 according to the invention makes it possible to offer more effective monitoring and improved safety for vehicles traveling on the infrastructure that it is supervising by addressing the obstructions in the field of view or the lack of range of the obstacle detection modules embedded in vehicles.
| Number | Date | Country | Kind |
|---|---|---|---|
| 19 00421 | Jan 2019 | FR | national |
