944results about "Platooning" patented technology

A system receives vehicle metric data from a gateway device connected to a vehicle. The vehicle gateway device gathers data related to operation of the vehicle and / or location data. The system receives data from multiple vehicles in a fleet. The vehicle gateway device gathers vehicle metric data at a high frequency. Instead of transmitting a large amount of vehicle metric data at a fine level of granularity, the vehicle gateway device aggregates and buckets the vehicle metric data over a period of time (such as, every five minutes). The system uses the bucketed data for fleet management analysis.

Systems and methods are provided herein for implementing dynamic, scalable platoon formations for traveling vehicles. Such platoons may be formed and modified on the fly by vehicles that have varying sensing or autonomy capabilities. Platoons may be negotiated among available vehicles, to designate roles including global platoon leader, local leader(s), and platoon member(s). While the platoons are in place and the vehicles traveling in coordination, platoon members may depart the platoon, and the remaining members may re-allocate roles among the remaining members.

Systems and methods for transmission gear shift management of a vehicle having cooperative adaptive cruise control (CACC) are provided. A method includes: enabling a cooperative adaptive cruise control (CACC) mode of a vehicle; updating a transmission shift map to adjust at least one threshold associated with a transmission shift event in response to enabling the CACC mode of the vehicle; receiving a torque demand from the vehicle in response to enabling the CACC mode of the vehicle; determining a transmission shift event based on the received torque demand and the updated transmission shift map; and implementing the determined transmission shift event.

Systems, methods, and other embodiments described herein relate to improving obstacle avoidance for a virtually connected convoy of vehicles. In one embodiment, a method includes detecting an obstacle in a path of a convoy, determining that a vehicle in the convoy is to execute obstacle avoidance based on a property of the vehicle and a physical property of the obstacle, and disengaging a following mode of the convoy responsive to a determination that the vehicle is to execute obstacle avoidance.

The invention relates to the technical field of intelligent network connection, and discloses a mixed traffic flow-oriented highway ramp confluence optimization control method, which comprises the steps of selecting different control methods according to state information of vehicles entering a formation control area, indirectly guiding manual driving vehicles to form a mixed formation mode through intelligent network connection vehicles, and controlling the formation control area according to the mixed formation mode. The driving states of all vehicles in the motorcade are monitored in real time; and dynamically calculating a confluence sequence and confluence time according to the driving state of the vehicle team entering the confluence control area, and dynamically adjusting the driving path and speed of the vehicle according to the confluence sequence and the confluence time. According to the method, the passing efficiency in the confluence process is greatly improved, and particularly in a complex traffic flow environment, the problem that in a traditional method, complex dynamic interaction during vehicle team confluence cannot be processed is solved.

The invention discloses a vehicle queuing length dynamic estimation method and system based on unmanned aerial vehicle cruise, belongs to the technical field of traffic state monitoring, and is used for solving the technical problems of how to realize accurate identification and tracking of queuing vehicles and panoramic scene construction and solving the problem of vehicle position deviation caused by time difference under dynamic traffic flow. And the accuracy and stability of vehicle queuing length estimation are improved. The method comprises the following steps: acquiring cruise video data of a congested road section through an inspection unmanned aerial vehicle; performing image processing on the cruise video data, and extracting vehicle characteristic parameters of the congested road section; constructing a lane-level queuing vehicle discrimination model based on two indexes of vehicle speed and linear vehicle distance; acquiring an ordered queuing vehicle set of the congested road section through the model; determining the initial queuing length of each lane according to the ordered queuing vehicle set; and dynamically correcting the initial queuing length based on a space-time compensation correction algorithm to obtain the real-time queuing length of each lane in the congested road section.

Apparatus, methods, and computer program products for platoon formation are provided. An example method may include identifying a set of non-malicious vehicles based on at least one of data associated with the set of non-malicious vehicles or communication from a second vehicle or a RSU. The example method may further include transmitting a request message to the set of non-malicious vehicles. The example method may further include receiving an acceptance message from at least one vehicle of the set of non-malicious vehicles. The example method may further include configuring a platoon with the at least one vehicle of the set of non-malicious vehicles.

The invention provides a vehicle-road cooperative control method and system for a double-layer ecological city in a mixed traffic flow environment, and the method comprises the steps: taking a signal lamp at each intersection as an intelligent agent, and obtaining the real-time driving information of a vehicle through infrastructure communication; the intelligent agent calculates the vehicle number and the driving speed of each motorcade according to the headstock distance between the vehicles; the upper perceptron predicts the time required by the motorcade to arrive at an intersection stop line by stacking a full-connection layer and a long-short-term memory network; the predicted time information is input into a strategy network and a value network of the intelligent agent to generate actions, and the strategy network is updated through delayed feedback rewards; the optimized suggested driving speed is sent to the head vehicle of the motorcade so as to optimize the driving track of the motorcade, relieve road network congestion and reduce pollutant emission; according to the invention, cooperative control is carried out through distributed decision making and cooperative learning by the intelligent agent, and the vehicle-road cooperative control capability and the traffic passing efficiency of the urban road network are improved.

A method by which a first device performs maneuver driving in an intelligent transportation system (ITS) according to various embodiments may comprise: receiving a vehicle-to-everything (V2X) message related to a maneuver sharing and coordinating service (MSCS) from a second device; and determining whether to perform cooperative driving with the second device on the basis of the V2X message.

The invention relates to a formation driving coordination method based on vehicle-road cooperation, and the method comprises the steps: a road side unit RSU is used for releasing a traffic constraint weight value containing the information of passing restriction, path guidance, risk distribution and the like into a formation driving region, and the weight value forms a traffic environment guidance domain with a potential gradient at a vehicle end; the vehicle autonomously completes formation aggregation and position arrangement based on the own state and the weight change trend in the local sensing environment; after the formation is completed, the vehicles dynamically form a multi-level influence circle structure according to relative positions, historical cooperative behaviors and influence factors provided by the RSU, a current leading vehicle exists in each layer of influence circle, the leading vehicle has local scheduling guidance capability, and when the state of the leading vehicle is unstable or the behavior is abnormal, the control right is transferred to the auxiliary control vehicle; according to the method, the traffic environment guidance domain with the potential gradient is constructed through the traffic constraint weight value issued by the RSU, and the vehicles can autonomously perform formation aggregation and array sorting based on the local weight change trend.

Systems and methods for swarm adaptation based on social value orientations are provided. In one embodiment, a method includes calculating social value orientations for a proximate vehicle of a plurality of proximate vehicles on a roadway with a plurality of swarm vehicles of a swarm. The method includes determining a total cost for the one or more proximate vehicles based on the social value orientations. The total cost for the proximate vehicle is based on an individual cost of the proximate vehicle and a joint cost of the proximate vehicle relative to the roadway vehicles. The method includes generating a global objective function based on a summation of the total cost of the plurality of proximate vehicles. The method includes determining a swarm action for a swarm vehicle by minimizing the total cost of the global objective function. The method includes causing the swarm vehicle to execute the swarm action.

One or more driving analysis computing devices in a driving analysis system may be configured to analyze driving data, determine driving behaviors, and calculate driver scores based on driving data transmitted using vehicle-to-vehicle (V2V) communications. Driving data from multiple vehicles may be collected by vehicle sensors or other vehicle-based systems, transmitted using V2V communications, and then analyzed and compared to determine various driving behaviors by the drivers of the vehicles. Driver scores may be calculated or adjusted based on the determined driving behaviors of vehicle drivers, and also may be calculated or adjusted based on other the driver scores of nearby vehicles.

An operating method of a first device (100) in a wireless communication system is presented. The method may comprise the steps of: determining that a first device (100) interrupts walking of a pedestrian; and determining, on the basis of the determination that the first device (100) interrupts walking of the pedestrian, whether to perform a first operation for preventing the interruption.

The invention provides an automatic driving vehicle lane changing intelligent decision-making method based on multi-dimensional evaluation, and the method comprises the steps: obtaining the environment information of a passing road section of an automatic driving vehicle queue through advanced sensing equipment and technology, constructing an optimization decision-making space in an automatic driving lane changing vehicle target queue, and carrying out the optimization decision-making space; and determining a candidate set where the lane changing vehicle is inserted into the target queue. And then, selecting a sine curve and model prediction control (MPC) to carry out track planning and control on the lane-changing vehicle, and traversing in sequence to obtain tracks and control information of the lane-changing vehicle inserted into each candidate position. Then, calculating the influence of the lane changing vehicle at each candidate position on four dimension indexes of operation safety, stability, efficiency and smoothness of the original queue and the target queue of the lane changing vehicle, dynamically updating the weights of the four dimension indexes according to road environment information, and carrying out weighted calculation to obtain a comprehensive score; finally, after traversal is finished, the comprehensive scores are compared, the insertion position with the highest score and the trajectory planning and control decision of the insertion position are selected as the optimal lane changing strategy to complete lane changing, the queue safety is guaranteed, and the passing efficiency is improved.

A method for controlling a vehicle platoon, performed by a computer device, includes: establishing a communication connection with a first vehicle, wherein the first vehicle is a free vehicle; obtaining vehicle status information of the first vehicle; obtaining at least one platoon status information of at least one vehicle platoon; matching a first target vehicle platoon of the at least one vehicle platoon with the first vehicle based on the vehicle status information and the at least one platoon status information; generating a first platoon control instruction based on: a first distance between the first vehicle and the first target vehicle platoon, the vehicle status information, and platoon status information of the first target vehicle platoon; and instructing the first vehicle to join the first target vehicle platoon based on transmitting the first platoon control instruction to at least one of the first target vehicle platoon or the first vehicle.

The invention discloses a non-signalized intersection vehicle right-of-way decision and speed guidance method. The method comprises the following steps: S1, collecting positions, speeds, accelerated speeds, vehicle types and intention information of all vehicles in a non-signalized intersection planning area; s2, determining a motorcade division scheme according to a formation rule combined with the vehicle intention; s3, establishing a road right optimization model of the non-signalized intersection, and determining the moment when each vehicle enters a confluence area of the non-signalized intersection and the allocated vehicle fleet occupation time of the non-signalized intersection; s4, constructing a speed suggestion algorithm, and inputting the moment when the vehicle enters the confluence area of the non-signalized intersection and vehicle state information; and S5, providing an on-line speed suggestion for the vehicle, and realizing conflict-free passing of the vehicle at the non-signalized intersection. The non-signalized intersection vehicle right-of-way decision and speed guidance method provided by the invention has stronger adaptability and can reduce the calculation complexity, and the vehicle passing efficiency and safety are improved.

The vehicle travel control device includes: an absolute position calculation unit configured to acquire GNSS information through a GNSS receiver mounted on a vehicle and calculate an absolute position of the vehicle by the standalone positioning; a reception determination unit configured to determine whether GNSS correction information required for relative positioning can be received from an external reference station; a relative position calculation unit configured to calculate a relative position of the vehicle by the relative positioning; and a communication unit configured to transmit the current position information of the vehicle to a remote control device. The communication unit is configured to: transmit position information based on the relative position in a case in which the GNSS correction information can be received; and transmit position information based on the absolute position in a case in which the GNSS correction information cannot be received.

The invention provides a vehicle formation control method fusing graph nerve and reinforcement learning, and the method comprises the steps: constructing a graph structure model between vehicles, extracting the structural interaction characteristics between a current vehicle and a neighbor vehicle through a graph attention network, and combining with the dynamic evolution characteristics of the modeling historical time steps of a long-short-term memory network, and predicting a neighbor aggregation state at a future moment. And processing the two-dimensional reflection image acquired by the vehicle sensor by using a convolutional neural network, and extracting the spatial semantic information of the surrounding environment. A vehicle state, neighbor features and environment features are fused as strategy input, joint training is performed based on a multi-agent depth deterministic strategy gradient algorithm, and end-to-end control strategy optimization is realized by adopting a centralized value network and distributed strategy network structure. According to the invention, the intelligent decision-making level of the formation system is improved, and the system has good environment adaptability and cooperative control performance.

A vehicle platoon intersection decision-making system includes multiple vehicles. When executing the intersection decision-making process, the captain vehicle determines whether the platoon can pass through the intersection at the current speed command; if yes, the captain vehicle directs each vehicle to maintain travelling at the current speed command to pass through the intersection; if not, the captain vehicle generates a first optimized speed control information through a first speed decision-making process, making the platoon decelerate before reaching the intersection and begin to accelerate at an acceleration critical time point such that the platoon passes through the intersection. When the platoon passes through the intersection at the current speed command, no energy for accelerating or decelerating is wasted. The platoon decelerates first and then begins to accelerate at the appropriate time through the intersection, avoiding or reducing the time spent waiting for traffic lights at the intersection.

The invention discloses an automatic driving motorcade control method, device and equipment and a storage medium, relates to the technical field of automatic driving, and discloses an automatic driving motorcade control method comprising the following steps: obtaining initial vehicle position data and initial environment data, and carrying out edge calculation on the initial vehicle position data and the initial environment data to obtain an initial feature vector; generating initial vehicle control data, and generating initial local empirical data according to the initial vehicle control data; generating noise-added local empirical data according to the Laplacian noise, encrypting the noise-added local empirical data through an encryption algorithm, uploading the noise-added local empirical data to a cloud end, and calculating an action value by the cloud end according to the noise-added local empirical data; and generating target vehicle control data according to the action value, the current vehicle position data and the current environment data, and controlling the vehicle to run according to the target vehicle control data to complete automatic driving fleet control. The technical effect that the communication efficiency is optimized while the collaborative decision-making efficiency and safety of the automatic driving motorcade are improved is achieved.

This application is directed to a centralized system for predicting vehicle trajectory. A computer system associated with a fixed installation having one or more first sensors obtains, from the first sensors, information of a plurality of vehicles that are traveling within a zone of interest of a road. The computer system generates a first travel trajectory for a first vehicle of the plurality of vehicles based on the information obtained from the one or more first sensors. The computer system sends, to the first vehicle, the first travel trajectory such that the first vehicle is configured to at least partially autonomously drive the first vehicle based on the first travel trajectory of the first vehicle.

Methods and systems for a vehicle of a remote transportation system. A vehicle includes a non-transitory computer readable media and one or more processors configured by programming instructions on the non-transitory computer readable media to: coordinate a platooning operation between the first vehicle and a second vehicle; monitor an environment of the first vehicle and the second vehicle while platooning; in response to the monitoring, determine a threat level vassociated with a cut-in operation of at least one object within the environment; and selectively activate at least one visual or audio cue based on the threat level to avoid the cut-in operation.

The invention discloses a formation riding danger information sharing method and system for intelligent riding helmets, and relates to the technical field of information sharing, and the method comprises the steps: carrying out the deep fusion of the adjacent beacons of all intelligent helmets, the state information of a vehicle, and the multi-source heterogeneous data of an external sensor, vehicle-road cooperation and the like; and constructing and dynamically maintaining a topological graph reflecting the space-time relationship among the formation members in real time. On the basis, intelligent source end propagation strategy decision is carried out on perceived semantic danger information, and topology-based directional relay and propagation are carried out. And finally, the decided propagable information is combined with the state of the rider, so that a highly personalized early warning instruction is generated. In this way, undifferentiated global information broadcast can be effectively converted into accurate risk announcement based on individual context, and the efficiency of dangerous information sharing in formation riding and the cooperative safety capability of the whole system are remarkably improved.

The invention is suitable for the technical field of intelligent driving regulation, and provides an intelligent traffic flow line optimized driving behavior regulation method and system, and the method comprises the steps: continuously collecting the behavior characteristic data of the following distance, lane changing frequency, accelerator stability and the like of a driver, and generating aggressive or prudent driving style DNA tags; in combination with vehicle navigation destinations and routes, a temporary motorcade containing one aggressive leader vehicle and two cautious following vehicles is established in the vehicles sharing the main road path; sending a team establishment application through the Internet of Vehicles, establishing a temporary collaborative team after confirmation of all the members, and planning an exclusive collaborative route; the leader vehicle broadcasts control instructions such as lane changing and speed changing, a vehicle team is regarded as a whole to calculate a cooperative safety space, instruction transmission intervals are dynamically set, and a unified driving strategy is generated. According to the invention, vehicle complementation and cooperation are realized, the traffic flow line is optimized, the driving behavior is adjusted, and the traffic efficiency and safety are improved.

The disclosure relates to a method (100) for coordinating a first road user (10) with a second road user (20) located in an environment of the first road user (10). Furthermore, the disclosure relates to a system (40) comprising at least two motorized vehicles (50, 60), wherein the system (40) is designed to carry out a method according to one of the preceding method claims, wherein at least one of the motorized vehicles (50) is designed to carry out the method steps in order to act as the first road user (10), and wherein at least one of the motorized vehicles (60) is designed to carry out the method steps in order to act as the second road user (20).

The invention discloses an intelligent electric vehicle queue optimization method based on congestion prediction and DRL. The method comprises the following steps: (1) modeling a queue position optimization problem of an electric vehicle queue into a mathematical model which takes energy balance as a target and is constrained by a traffic environment; and (2) solving the mathematical model in the step (1) by adopting a DRL method based on a TRPO algorithm to obtain an optimal queue adjustment strategy of the electric vehicle queue. In the step (2), congestion state information in an external traffic environment is obtained through an LSTM traffic prediction and FCM method, and the congestion state information, the remaining electric quantity of each vehicle in the motorcade and the accumulated driving distance are jointly used as state input of a TRPO algorithm; according to the TRPO algorithm, a strategy network and a value network are adopted to respectively obtain a strategy for adjusting the queue position, and the return expectation in the current state is evaluated. The TRPO algorithm dynamically adjusts the updating step length of the strategy through the KL divergence updated by the constraint strategy, and guarantees the stability and convergence in the strategy updating process.

Certain aspects of the present disclosure provide techniques for enhancing vehicle operations safety using coordinating vehicle platooning or enhancing platooning safety against location spoofing attacks. In one example, a source user equipment (UE) detects a potential spoofing event associated with location information being altered in an unauthorized manner, the source UE may transmit a request to a platoon control system (PCS) to join a vehicle platoon. In another example, a first UE associated with a lead vehicle in an existing platoon may detect a potential spoofing event associated with location information being altered in an unauthorized manner. The lead vehicle may transmit to a second UE of another vehicle in the platoon an indication of the detection and a request to exchange the respective roles in the platoon. The PCS may also monitor the conditions of the first and the second UEs, and arrange for the platoon reorganization.

Techniques are disclosed to increase the safety of vehicles travelling in a vehicle platoon. These techniques include the utilization of a comprehensive safety framework such as a safety driving model (SDM) for the platoon control systems. In contrast to the conventional approaches, the use of the SDM model allows for platoon vehicle control systems to consider the acceleration / deceleration capabilities of the vehicles to calculate minimum safe longitudinal distances between the platoon vehicles. The disclosed techniques may utilize the periodicity of platoon messages as well as other parameters to improve upon platoon vehicle control and safety.

Aspects of the disclosure provide for route variation for autonomous vehicles. For example, a plurality of routes may be identified. Each route of the plurality may be a current route on which an autonomous vehicle of a fleet of autonomous vehicles is currently traveling. Each of the autonomous vehicles may use a cost-based analysis to determine routes. That there will be a cluster of autonomous vehicles of the fleet of autonomous vehicles on a road segment may be determined. A signal may be sent to one or more of the autonomous vehicles of the cluster of autonomous vehicles a signal to adjust a cost of traversing the road segment in order to increase a likelihood of the one or more of the autonomous vehicles of the cluster of autonomous vehicles avoiding the road segment.