Patent Description:
An autonomous or automated vehicle must be able to perform different tasks including self-localization, environment modelling, mapping and tracking of external objects such as pedestrians, other vehicles, bikes, whatever the circumstances.

Self-localization may be the most important task of an autonomous vehicle. The more accurate the self-localization of the autonomous vehicle, the more accurate the localization and tracking of external objects. Self-localization of the autonomous vehicle can be performed based on data collected by different onboard sensing systems such as cameras, LiDARs, radars, etc..

Furthermore, the autonomous vehicle has to generate an environment model to recognize the static objects, for example a wall, in its surrounding environment, avoid collisions with the static objects, and plan an optimal path from a point A to a point B.

A known method of self-localization uses a satellite navigation system such as GNSS (Global Navigation Satellite System). It allows the vehicle provided with a receiver for receiving the GNSS signals to determine its location (longitude, latitude, and altitude/elevation) to high precision (within a few centimeters to meters) using time signals transmitted along a line of sight by radio from satellites. However, within an indoor environment, e.g., in a tunnel or a parking garage, the signals from the satellite navigation system are generally not available and the self-localization must be performed in a different way.

Different methods are known for self-localization of an autonomous vehicle in an indoor environment.

A first known method consists in tracking the position and orientation of the vehicle using mechanical motion sensors, such as accelerators and gyroscopes, and a motion model.

In a second known method, successive observations are collected by one or more onboard sensors, such as a LiDAR or a camera, and registered, and the motion of the vehicle is derived from these successive observations.

The document <CIT> discloses an indoor positioning method for positioning a vehicle within an indoor space, based on a machine learning and/or artificial intelligence algorithm. The vehicle acquires image information of the indoor space with a sensing system, and the acquired information is matched with a pre-generated indoor map to localize the vehicle in the indoor space based on the matching result.

A disadvantage of the first and second methods is that they perform a relative positioning, which requires to know an initial position and orientation of the vehicle. The method of <CIT> is limited to the positioning of one vehicle in the indoor space based on a pre-generated indoor map. <CIT> and <CIT> also represent relevant prior art for the application.

The known methods are limited to the self-localization of one vehicle in an indoor environment. Therefore, there is a need for improving the vehicle automated driving and/or the vehicle driving assistance within an indoor environment that other participants, like other vehicles and/or pedestrians, can enter.

The present disclosure concerns a computer-implemented method for vehicle driving assistance within a delimited area, including the followings steps performed by a central data processing system :.

The present method originates from a need for improving vehicle autonomous driving and/or vehicle driving assistance within an indoor environment. However, the present method applies more generally to a delimited area that may include a tunnel, a car park, a warehouse, a bridge, or any other type of zone requiring an improved vehicle driving assistance, for example for security reason. The present method allows to obtain a centralized perception of the delimited area by sharing the sensing systems or sensors of all vehicles located in the delimited area. It is as if the central data processing system was equipped with the sensors of all vehicles. Furthermore, the processing of the sensing data collected by the sensors is carried out by the central data processing system, which allows to have basic and low-cost sensors without processing means in the vehicles. As a result, the implementation is simple and low-cost.

In an embodiment, the step of centrally processing and fusing may include generating a fused map of the delimited area based on the sensing data received from the plurality of vehicles, and the step of transmitting an information for vehicle driving assistance includes transmitting the generated map.

The fused map may aggregate the environmental information perceived by the sensing systems of all the vehicles and may be shared with all vehicles, in real time. In this way, each vehicle can map the environment within the delimited area as perceived by the sensors of all vehicles.

Other features of the present disclosure are defined in the appended claims.

The present disclosure concerns a computer-implemented method for vehicle driving assistance within a delimited area <NUM>.

For example, the delimited area <NUM> may include an indoor space such as a road tunnel as illustrated in <FIG>, a car park, or a warehouse where automated vehicles drive to perform logistics tasks. The delimited area may include any other zone requiring improved vehicle driving assistance, in particular for security reason. For example, the delimited area may include a road bridge. These examples are only illustrative and non-limitative.

A plurality of vehicles, referenced as Vi with i = <NUM>, <NUM>, <NUM>,. , may enter and move within the delimited area <NUM>. Other participants, such as pedestrians, may also enter and move within the delimited area <NUM>.

The delimited area <NUM> is equipped with a central data processing system <NUM> and is covered by a wireless local area network <NUM>, to which vehicles Vi can connect.

The delimited area <NUM> may be termed as a sensing area, as it is an area in which vehicles send, or upload, sensing data captured by vehicle onboard sensors to the central data processing system <NUM> through the wireless local area network <NUM>, as will be described later in more details.

In an embodiment, the wireless local area network <NUM> may a <NUM>-based network using the <NUM> technology. The <NUM> technology offers an extremely low latency rate that is the delay between the sending and receiving information. Alternatively, the wireless local area network <NUM> could be based on any other technology for wireless communication offering a low latency rate, for example <NUM> and any future generation communication system. The local area network <NUM> has a network identifier, or network ID, that may be broadcast by one or more base stations within an area covering the delimited area <NUM>. The covering area <NUM> of the base station(s) may extend beyond the delimited area <NUM> to allow vehicles that are outside the delimited area <NUM> and move towards an access to the delimited area <NUM> to connect to the wireless local area network <NUM> before entering the delimited area <NUM>. The wireless local area network <NUM> could be a part of a mobile telecommunication network, for example to one or more cells of the mobile telecommunication network.

The vehicles Vi, with i = <NUM>, <NUM>, <NUM>,. , may be automated vehicles or vehicles comprising one or more ADAS (Advanced Driving Assistance System) systems. Each vehicle Vi has one or more onboard sensors or sensing systems, such as radar(s), LiDAR(s), and/or camera(s), for collecting sensing data related to its own vehicle environment. Furthermore, each vehicle Vi comprises a radio communication module for connecting to the the wireless local area network <NUM> and communicating through it. The radio communication module may include a radio transmitter and a radio receiver. It can comprise hardware means and/or software means. The radio communication module allows the vehicle Vi to connect to the wireless local area network <NUM>, transmit the sensing data collected by the sensors of the vehicle Vi to the central data processing system <NUM> and receive from the central data processing system <NUM> an information for vehicle driving assistance. Each vehicle may also include a registration module for registering with the central data processing system <NUM> upon detection and/or connection to the wireless local area network <NUM>.

<FIG> illustrates the computer-implemented method for vehicle driving assistance within the delimited area <NUM>, according to an embodiment.

At a first point in time, referenced as t<NUM>, a plurality of vehicles Vi with i = <NUM>,<NUM>,<NUM>,. , are located within the delimited area <NUM> and connected to the wireless local area network <NUM>. The vehicles Vi can be started vehicles or stopped vehicles, for example parked vehicles or temporarily stopped vehicles. In any case, the vehicles Vi have one or more active sensors operable to capture sensing data and a radio communication module operable to transmit the sensing data captured by the sensors. In an embodiment, each of the vehicles Vi may have previously registered with the central data processing system <NUM> through the wireless local area network <NUM>, for example when or shortly before entering the delimited area <NUM>. A registration step S0 may be executed by each vehicle Vi entering the delimited area <NUM>, for example upon detection and connection to the wireless local area network <NUM>. The central data processing system <NUM> may store information on the registered vehicles Vi with i = <NUM>, <NUM>, <NUM>,. in a database and manage the database. The vehicles Vi may be deleted from the database for example when they are no longer connected to the wireless local area network <NUM>.

The sensing data collected, or captured, by the sensors in each vehicle Vi is continuously transmitted from the vehicle Vi to the central data processing system <NUM> in real time, through the wireless local area network <NUM>, in a step S1. The transmission of the data collected by the onboard sensors of each vehicle Vi may be performed automatically, without any action from a user. The sensing data may be transferred to the central data processing system in real time, as soon as it is collected. The sensing data may be raw, unprocessed data from the sensor(s). Thus, the central data processing system <NUM> receives from the plurality of vehicles Vi located within the delimited area <NUM> and connected to the wireless local area network <NUM>, the sensing data related to the environment around each vehicle Vi. Each vehicle Vi perceives its surrounding environment with its own onboard sensors. The output of the sensors, termed as the sensing data, may be transferred to the central data processing system <NUM>, through the wireless local area network <NUM>, by an onboard radio transmitter of the vehicle Vi. For example, the sensing data may include point clouds for radars and LiDARs, and picture frames for cameras. The sensing systems of the vehicles Vi, that may include cameras, radars, LiDARs, do not need to have additional means for processing the sensing data. They can be basic and low-cost sensing systems having only the functions of sensing data and transferring the data.

In a step S2, the central data processing system <NUM> receives the sensing data from each vehicle Vi located within the delimited area <NUM>, though the wireless network <NUM>. The sensing data from the vehicles Vi may be received in real time, as soon as it is collected.

In a step S3, the central data processing system <NUM> centrally processes and fuses, or aggregates, the sensing data received from the plurality of vehicles Vi to determine a fused, or aggregated, environmental information of the environment within the delimited or sensing area <NUM>. Thus, the sensor information from all the vehicles Vi located within the delimited area <NUM> is fused or aggregated by the central processing system <NUM>. It is as if the central processing system <NUM> was equipped with the onboard sensors of all the vehicles Vi located in the delimited area <NUM>. The fused or aggregated environmental information may be shared with all the vehicles Vi within the delimited area <NUM> through the wireless network <NUM>. In this way, each vehicle Vi is virtually equipped with the sensors of all the vehicles Vi located in the delimited area <NUM>.

<FIG> illustrates the step S3, according to an embodiment.

In an embodiment, the step S3 of centrally processing and fusing, or aggregating, the sensing data from the plurality of vehicles Vi may include a step S30 of generating a fused, or aggregated, map of the delimited area <NUM> based on the sensing data received from the plurality of vehicles Vi.

The central data processing system <NUM> may have access to a predefined map of the delimited area <NUM>. This predefined map may be stored in a memory of the central processing system <NUM>, and/or obtained from an online database of a service provider like OpenStreetMap® or Google Maps®. In the step S30, the central data processing system <NUM> may process and analyze the sensor data received from all the vehicles Vi to obtain additional information related to the environment within the delimited area <NUM>, and update the predefined map by using this additional information. The update of the predefined map may allow to add or delete objects or participants in the predefined map, and/or add information that may be useful for vehicle driving assistance in the delimited area <NUM>. For example, one or more pedestrians, an object that has fallen to the ground, a traffic jam, a hazardous event such as a stopped vehicle or a collision, etc. may be added to the predefined map.

In a variant, in the step S30, the central processing system <NUM> may generate an individual map for each vehicle Vi, representing an area around the vehicle Vi, by using the sensor data from said vehicle Vi, and then fuse, or aggregate, the plurality of individual maps generated for the plurality of vehicles Vi to generate a fused map of the delimited area <NUM>.

In an embodiment, by processing and fusing the sensing data from the plurality of vehicles Vi, the central data processing system <NUM> may determine, or identify, a hazardous situation in the delimited area <NUM>, in a step S31. For example, an accident has occurred in the delimited area <NUM>, a vehicle is stopped on a road lane in a tunnel, or an object has fallen down to the ground within the delimited area <NUM>. The hazardous situation may be identified by processing and analyzing the sensing data received from the vehicles Vi. For example, a stationary traffic can be detected by analyzing the speed data from the vehicles Vi, an object on the ground or pedestrians can be detected by image analysis of images captured by sensors of vehicles Vi. , a collision may be detected by analyzing images captured by vehicles, etc.. In that case, the central data processing system <NUM> generates a warning message or a warning information to inform the vehicles Vi in the delimited area <NUM>, in a step S32.

In an embodiment, in a step S33, the central data processing system <NUM> may generate commands to control a driving or parking function of one or more target vehicles Vi in the delimited area <NUM>, based on a result of centrally processing and fusing the sensor data of all the vehicles Vi. For example, the commands may control a target vehicle to adapt its speed in a tunnel, or take over the driving of a target vehicle to a chosen parking lot in a car park. In case of a warehouse comprising automated vehicles such as forklifts, the commands may control the movements of the automated vehicles in the warehouse.

In a step S4, the central data processing system <NUM> transmits a fused information for vehicle driving assistance, based on a result of the step S3 of centrally processing and fusing the sensing data from the vehicles Vi, to one or more target vehicles Vt of the vehicles Vi with i = <NUM>, <NUM>, <NUM>,. connected to the wireless local area network <NUM>. The target vehicles may include one or more vehicle(s) located within the delimited area <NUM>, and/or one or more vehicle(s) located outside the delimited area <NUM> but within the covering area <NUM> of the wireless local area network <NUM>. For example, one or more target vehicles could be vehicles located outside the delimited area <NUM> and moving towards an access to the delimited area <NUM> to enter it.

The step S4 may include the following actions performed by the central data processing system <NUM>:.

The central data processing system <NUM> continuously receives the sensing data collected by the sensors of all the vehicles Vi with i = <NUM>, <NUM>, <NUM>,. located within the delimited area <NUM>, processes and fuses the received sensing data to update the information for vehicle driving assistance transmitted to the target vehicles.

Furthermore, when a new vehicle enters the delimited area <NUM> and registers with the central data processing system <NUM>, the central data processing system <NUM> may transmit a current information for vehicle driving assistance, for example the current fused map, and/or a current warning message, and/or commands for driving or parking, to the newly registered vehicle.

The information for vehicle driving assistance is continuously updated, in real time, based on the sensing data received over time by the central data processing system <NUM>.

Optionally, in a step S5, the central data processing system <NUM> executes, for each vehicle Vi with i = <NUM>, <NUM>, <NUM>,. located within the delimited area <NUM>, one or more tasks of driving assistance or autonomous driving including self-localization of the vehicle Vi, mapping around the vehicle Vi, tracking external objects around the vehicle Vi, path planning for the vehicle Vi and controlling the vehicle Vi for example for driving and/or parking, by processing the sensing data collected by the sensors of the vehicle Vi and transferred to the central data processing system <NUM> through the wireless network <NUM>. The fused environmental information resulting from the step of centrally processing and fusing the sensing data from all vehicles Vi may also be used by the central data processing system <NUM> to perform the tasks of driving assistance or autonomous driving for the considered vehicle Vi. The result of each task of driving assistance or autonomous driving is transferred from the central data processing system <NUM> to the vehicle Vi through the wireless network <NUM>, in a step S6. In this way, the processing of the sensing data collected by each vehicle Vi with i = <NUM>, <NUM>, <NUM>,. located within the delimited area <NUM> to execute tasks of driving assistance and/or autonomous driving is deported into the central data processing system <NUM>. The low latency of the network <NUM> allows to deport the processing of the sensing data collected by each vehicle Vi with i = <NUM>, <NUM>, <NUM>,. located within the delimited area <NUM>, while allowing this vehicle Vi to use the result of the processing in real time, or almost in real time.

For the task of self-localization of the vehicle Vi, the central data processing system <NUM> may match a landmark information detected in the environment around said vehicle Vi, based on the sensing data received from said vehicle Vi, and a predefined map of the delimited area <NUM> including eh landmarks. For example, the delimited area <NUM> may comprise reflecting elements at predetermined positions, and the predefined map may include the reflecting elements. As a result, the central data processing system can match the landmark information obtained by processing the collected sensing data and the landmarks included in the predefined map to precisely localize the vehicle.

The central data processing system <NUM> includes means for carrying out the steps of the method previously described. It is configured to receive the sensing data from the vehicles Vi, with i = <NUM>, <NUM>, <NUM>,. , located within the delimited area <NUM>, through the wireless local area network <NUM>, to centrally process and fuse the received sensor data, transmit an information for vehicle driving assistance, based on a result of the processing and fusion of the received sensing data, to target vehicles.

In an embodiment, the central data processing system <NUM> may include a network interface <NUM> for connecting to the wireless local area network <NUM>, a reception module <NUM>, a data processing module <NUM> and a transmission module <NUM>.

The reception module <NUM> is configured to receive from each vehicle Vi, with i = <NUM>, <NUM>, <NUM>,. , sensing data related to an environment of the vehicle Vi, through the network <NUM>.

The data processing module <NUM> is responsible for centrally processing and fusing or aggregating the sensing data from the plurality of vehicles Vi, with i = <NUM>, <NUM>, <NUM>,. , and for generating a fused information for vehicle driving assistance based on a result of the processing and fusion of the sensing data. Optionally, the data processing module <NUM> may be configured to execute, for each vehicle Vi with i = <NUM>, <NUM>, <NUM>,. located within the delimited area <NUM>, tasks of driving assistance and/or autonomous driving such as self-localization of the vehicle Vi, mapping around the vehicle Vi, tracking external objects around the vehicle Vi, and controlling the vehicle Vi, by processing the sensing data collected by the sensors of the vehicle Vi.

The transmission module <NUM> is configured to transmit the information for vehicle driving assistance generated based on processing and fusing the sensing data from the plurality of vehicles Vi, with i = <NUM>, <NUM>, <NUM>,. , to target vehicles in the delimited area <NUM>, through the wireless network <NUM>. The transmitted information may include the fused environmental information, and/or an information generated based on the fused environment information, for example one or more commands for controlling the target vehicle Vt to drive autonomously, or a warning message.

Optionally, the transmission module <NUM> is configured to transfer to a vehicle Vi the result of one or more tasks of driving assistance and/or autonomous driving executed by processing the sensing data from said vehicle Vi, as previously explained.

The central data processing system <NUM> may further include a vehicle database <NUM> for storing information on the vehicles located within the delimited area, that have registered with the central data processing system <NUM>, a registration module <NUM> configured to perform the task of registration of vehicles located within the delimited area <NUM>, and a database management module <NUM> responsible for storage, retrieval and update of information in the database <NUM>. The registration module <NUM> is responsible for registering in the database <NUM>.

Claim 1:
A computer-implemented method for vehicle driving assistance within a sensing area (<NUM>), including the following steps performed by a central data processing system (<NUM>) :
- receiving (S2) in real time from a plurality of vehicles (Vi, i = <NUM>, <NUM>, <NUM>, ... ) located within the sensing area (<NUM>), through a wireless local area network (<NUM>) covering said sensing area (<NUM>), raw sensing data captured by sensors of the vehicles (Vi), whereby the sensing data from each vehicle (Vi) is related to an environment around said vehicle (Vi);
- centrally processing and fusing (S3) the sensing data from the plurality of vehicles (Vi) by generating (S30) a real-time fused map of the sensing area (<NUM>) based on the sensing data received from the plurality of vehicles (Vi , i=<NUM>,<NUM>,<NUM>,... );
- transmitting (S6) to at least one target vehicle (Vi), through the wireless local area network (<NUM>), an information for vehicle driving assistance including the real time fused map.