423results about "Platooning" patented technology

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.

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.

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.

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.

A system for mapping road segment free spaces for use in autonomous vehicle navigation. The system includes at least one processor programmed to: receive from a first vehicle one or more location identifiers associated with a lateral region of free space adjacent to a road segment; update an autonomous vehicle road navigation model for the road segment to include a mapped representation of the lateral region of free space based on the received one or more location identifiers; and distribute the updated autonomous vehicle road navigation model to a plurality of autonomous vehicles.

The invention relates to the technical field of vehicle control, in particular to a vehicle queue optimal control method and system based on a function deviation triggering mechanism, and the method comprises the steps: 1, constructing a piloting dynamics model of a piloting vehicle and a following dynamics model of a following vehicle; 2, defining a local tracking error of the ith following vehicle, defining control input of the following dynamical model as a function of the local tracking error according to an optimal control target, further defining an optimal value function, and determining optimal control input according to the optimal value function; 3, obtaining an optimal value function estimation value through an adaptive commentator neural network; 4, designing a function deviation triggering mechanism according to the optimal value function estimation value and the local tracking error so as to dynamically adjust the optimal control input of the following dynamical model; and 5, setting a communication association relationship and an initial state of the leading vehicle and the following vehicle to obtain a queue control result. According to the invention, efficient cooperative driving in a complex dynamic environment is realized.

The invention relates to the technical field of call center control, and discloses an unmanned vehicle formation control and obstacle avoidance reconstruction system based on complex road conditions. The system call data acquisition module is used for acquiring multi-source interaction data in real time; the dynamic feature extraction module is used for performing semantic intention hierarchical analysis on the voice stream text conversion data, performing event fragment segmentation on the user behavior time sequence data, and generating an operation track feature vector; the scene clustering engine module is used for performing space-time alignment on the semantic intention hierarchical analysis result and the event fragment segmentation result to generate a multi-dimensional scene clustering tag; the strategy matching core module is used for retrieving an interaction strategy set matched with the current scene from a distributed strategy library according to the multi-dimensional scene clustering label and generating a dynamic control instruction sequence; and the instruction distribution execution module is used for distributing the dynamic control instruction sequences to corresponding seat terminals and voice routing equipment after sorting the dynamic control instruction sequences according to priorities.

An apparatus of a first vehicle includes a processor configured to detect a fault associated with a second vehicle. The processor is configured to obtain sensor data associated with a sensing region of the second vehicle. The processor is configured to provide an output, based on the sensor data, for controlling the second vehicle to traverse a vehicle transportation network

Collective action by multiple vehicles traversing a vehicle transportation network is used to improve operation of vehicles and utilization of the vehicle transportation network. Sensor data for multiple monitored vehicles traveling in a common direction along a road in a vehicle transportation network is received and used as input to a traffic estimation model to determine an estimated congestion for the road in the common direction. A cruise control setting for each of several controlled vehicles, at least some of the controlled vehicles traveling behind the monitored vehicles in the common direction, is determined from the estimated congestion. The cruise control setting is transmitted to the controlled vehicles to modify operation of the controlled vehicles using respective cruise control systems of the controlled vehicles.

The disclosure relates to a motor vehicle, to a driver assistance system, and to a method for operating the driver assistance system. A relevant slipstream region of a further motor vehicle driving in a predetermined surrounding region of the motor vehicle is detected. A current slipstream efficiency is ascertained based on whether the motor vehicle is driving in the slipstream region and, if so, based on which of the slipstream partial regions of the slipstream region the motor vehicle is driving in. An overall aerodynamic efficiency is ascertained based on a current driving speed of the motor vehicle and the current slipstream efficiency. An individual overall aerodynamic efficiency potential that characterizes an overall aerodynamic efficiency that will be achieved by the motor vehicle when same drives in the slipstream region of the further motor vehicle is assigned to the further motor vehicle based on the driving speed and slipstream region.

The invention discloses a three-stage cooperative lane changing method for a vehicle queue in a ramp diversion area in an intelligent network connection environment, and the method comprises the steps: firstly, determining a safety gap of a target lane based on a minimum safety distance and a maximum deceleration, and selecting a vehicle which can change the lane to the safety gap from a CAV queue for preferential lane changing; secondly, establishing a longitudinal trajectory planning model based on self-adaptive model predictive control, performing longitudinal distance adjustment on a lane-changed vehicle by using the model, and reversely calculating an initial position required by the vehicle to smoothly drive into a ramp based on a quintic polynomial trajectory planning method; embedding into adaptive model predictive control as a ramp tail end constraint to form a new safety gap of the target lane; and finally, the vehicles which do not change lanes are controlled to sequentially change lanes to the corresponding safety gaps, and lane changing of the CAV queue is achieved. According to the method, the CAV queue can efficiently and orderly drive into the exit ramp, the vehicle speed fluctuation of a shunting area can be reduced, and the overall passing efficiency of a road section is improved.

Platoons of vehicles are operated remotely by a teleoperator. A lead vehicle of a platoon establishes communications with a teleoperator station, which receives drive state data from the lead vehicle and generates reference instructions for the lead vehicle. When a lead vehicle is under control of a teleoperator, and a follower vehicle joins a platoon with the lead vehicle, the follower vehicle receives drive state data from the lead vehicle and reference instructions for the lead vehicle from the teleoperator station. The follower vehicle captures data regarding its own drive state, and generates instructions based on the drive state data of the lead vehicle and the reference instructions for the lead vehicle. Drive state data of a lead vehicle of a platoon may be estimated, augmented or refined for accuracy based on drive state data of other vehicles of the platoon.

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.

A system for enhancing autonomous ride-sharing network liquidity through adaptive vehicle configuration is disclosed. The system comprises a fleet of vehicles with dynamically activatable features, a central control system for monitoring market demand and vehicle availability, and modules for feature activation and dynamic configuration and deployment. This invention allows a single vehicle type to serve multiple market segments by dynamically adjusting its feature configuration and tier deployment based on real-time demand, thereby optimizing fleet utilization and enhancing service flexibility.

The invention provides a method for determining a motorcade driving strategy and electronic equipment, and relates to the technical field of path planning, and the method comprises the steps: firstly, determining a comprehensive operation index of a motorcade based on cooperation data and a basic operation index of the motorcade; secondly, the collaborative data and interaction data and prior data of the motorcade are fused to obtain fused data, the interaction data are data of the current running state of the vehicle and the road condition of the environment where the vehicle is located, and the prior data are used for representing historical driving data matched with the current scene; and finally, based on the fusion data, the comprehensive operation index and the path planning data of the motorcade, determining a target driving strategy of the motorcade, the path planning data being a constraint for supporting path planning. The technical problem that in the prior art, cooperative requirements of distance control, path conflict avoidance and the like of the motorcade in an off-road environment are not considered, so that the overall passing efficiency and safety of the motorcade are insufficient is solved.

Techniques are provided which may be implemented using various methods and / or apparatuses in a vehicle to utilize vehicle external sensor data, vehicle internal sensor data, vehicle capabilities and external CV2X input to determine, send, receive and utilize data elements to determine inter-vehicle spacing, intersection priority, lane change behavior and spacing and other autonomous vehicle behavior.

The invention provides a motorcade active-disturbance-rejection control method and system with a variable time interval strategy. The method comprises the following steps: acquiring state information of each vehicle in a vehicle queue system; the leader vehicle and the following vehicle carry out information transmission; under the condition of considering external disturbance, a vehicle dynamics model referring to the Newton second law is established, and a variable time interval strategy is constructed; compensating unmodeled dynamic and external disturbances in the vehicle dynamics model by using a time-varying gain expansion state observer in an active disturbance rejection control technology, and constructing a virtual controller and an actual controller based on a backstepping method; and according to the constructed virtual controller and the actual controller, realizing position and speed synchronization of the following vehicle and the leading vehicle in the queue under the condition of considering unmodeled dynamics and external disturbance. According to the method, the non-smooth problem at the saturation threshold is solved, the fluctuation influence can be effectively reduced, the safety is guaranteed, and the passing efficiency is improved; and the problem of gain attenuation is solved while the high gain characteristic is reserved.

The invention relates to the technical field of vehicle control, in particular to a motorcade collaborative automatic driving method and system based on distributed consensus decision. The invention provides a motorcade collaborative automatic driving method based on a distributed consensus decision, and the method comprises the steps: carrying out the dynamic networking and data broadcasting, enabling vehicles in a motorcade to automatically discover and carry out the networking through a V2V communication module, and forming a logic cluster; triggering a cooperative task and generating a proposal, and when a local system of any vehicle in the cluster detects a scene needing a motorcade cooperative response, the vehicle serves as a proposal node and generates a cooperative action proposal based on the vehicle and received shared information; and based on BFT distributed consensus decision, vehicles in the cluster independently verify security and rationality to achieve a consensus process after receiving a proposal. After all the vehicles reach the consensus, a time synchronization mechanism is kept, and it is ensured that all the vehicles execute the instructions on the same standard. The technical problem that in the prior art, an RSU-based motorcade collaborative automatic driving method is needed is solved.

A method, in a first network function, for providing one or more platoon recommendations for platooning of a plurality of communication devices the method comprising: obtaining mobility information for the plurality of communication devices; determining, based on the mobility information, a platoon recommendation comprising a subset of the plurality of communication devices to be grouped into a platoon and a head communication device of the subset of communication devices to be responsible for reporting reference signal measurements on behalf of the platoon; and transmitting the platoon recommendation to a second network function.

The present disclosure relates to safety devices and systems for light mobility vehicles. In one example, a light mobility vehicle safety system includes one or more sensors and a processor coupled to a light mobility vehicle. The processor may be configured to determine that the light mobility vehicle is part of a group of two or more light mobility vehicles; determine a position of the light mobility vehicle relative to one or more other light mobility vehicles in the group; determine one or more relevant sensors of the one or more sensors based on the position of the light mobility vehicle and positioning of the one or more sensors on the light mobility vehicle; receive first relevant safety-related data from the one or more relevant sensors; and transmit the first relevant safety-related data to one or more other light mobility vehicles in the group.

Systems and methods are disclosed for coordinating multiple autonomous vehicles for group transportation, including a server initializing a motorcade session based on a motorcade formation request and starting a motorcade session, wherein the motorcade session includes coordination of integrated functionality across the autonomous vehicles within the motorcade via communication with a server or via vehicle-to-vehicle communication channels.

The invention relates to a method and to a device for the mutual monitoring and / or control of a multiplicity of autonomous technical systems which are at least partially interconnected to one another via a communication network (NW) At least one of the autonomous technical systems is embodied as a monitoring autonomous technical system (ASobs1) and monitors the operating behaviour of other autonomous technical systems. On the basis of a specified first rule, the monitoring autonomous technical system (ASobs1) detects an operating behaviour, which is contrary to the rule, of a first autonomous technical system (AS1) and generates a status message about the operating behaviour which is contrary to the rule therefrom. The status message is transmitted by the monitoring autonomous technical system (ASobs1) to some of the other autonomous technical systems, is received thereby and evaluated jointly. Depending on the evaluation, a control rule is derived for the first autonomous technical system (AS1) and communicated to a control module (CTLM) which is assigned to the first autonomous technical system (AS1). The operating behaviour of the first autonomous technical system (AS1) is controlled on the basis of the control rule.

A travel support device supports vehicle traveling. The travel support device includes one or more processors. The one or more processors are configured to execute travel management processing when a target vehicle is traveling on a road having a specific lane in which a specific type of vehicle preferentially travels. The target vehicle is of a different type from the specific type. The travel management processing includes travel permission processing of permitting the target vehicle to travel in the specific lane when the target vehicle is traveling in a vehicle train being a train of vehicles that perform platooning, and entry inhibition processing of inhibiting entry of the target vehicle into the specific lane when the target vehicle is not traveling in the vehicle train.

A method for automated vehicle driving control in a platoon includes obtaining first operational parameters of a first vehicle, including at least a first measured braking performance of the first vehicle, obtaining second operational parameters of a second vehicle, including at least a first measured braking performance of the second vehicle, determining a platoon sequence according to the operational parameters by assigning whichever of the first vehicle and the second vehicle that has a lesser measured braking performance as a lead vehicle in the platoon sequence, and assigning the other of the first vehicle and the second vehicle as a follower vehicle in the platoon sequence, initiating a platoon sequence driving route, and controlling automated driving of the follower vehicle according to tracking of the lead vehicle, wherein the automated driving includes automated steering control, automated acceleration and automated braking based on tracked movement of the lead vehicle.

A travel support method for a vehicle to be executed by a processor, comprising, estimating a position of a subject vehicle, acquiring map information from a database, generating a subject vehicle traveling route on which the subject vehicle travels, based on the estimated position of the subject vehicle and the map information, calculating a degree of first reliability indicating reliability of the subject vehicle traveling route, detecting a preceding vehicle traveling ahead of the subject vehicle, generating a preceding vehicle traveling route on which the preceding vehicle travels, calculating a degree of second reliability indicating reliability of the preceding vehicle traveling route, based on a shape of the preceding vehicle traveling route, calculating, based on the degree of the first reliability and the degree of the second reliability, an integration ratio for integrating the subject vehicle traveling route and the preceding vehicle traveling route, calculating a target traveling route of the subject vehicle by integrating the subject vehicle traveling route and the preceding vehicle traveling route at the calculated integration ratio, and controlling the subject vehicle based on the target traveling route.