An example apparatus includes at least one processor and at least one memory coupled to the at least one processor and storing programming instructions for execution by the at least one processor to: obtain map data at a current moment, where the map data includes a first road area at the current moment, the special road condition is located in the first road area, the first road area is obtained based on a road condition model and a vehicle parameter within a preset time period before the current moment, and the road condition model represents a correspondence between a feature of the vehicle parameter and the special road condition; and determine, based on a planned route of a vehicle, that a second road area exists in the planned route of the vehicle, where the second road area is in the first road area.

Systems and methods for detecting or predicting potential collisions between vehicles are provided. The systems and methods may receive sensor output indicative of a location, a heading, and/or a moving speed of a first vehicle and/or a second vehicle. The systems and methods may predict a collision between the vehicles at an intersection between routes based on the received sensor output. The systems and methods may change movement of the first vehicle and/or the second vehicle responsive to predicting the collision.

An operating situation obtaining unit obtains the operating situation information of a plurality of operating vehicles along a predetermined route. A delayed vehicle extraction unit extracts a delayed vehicle that is delayed in actual operation relative to the operation schedule from among the plurality of operating vehicles, based on the operating situation information of the respective operating vehicles. An overtaking instruction unit outputs an overtaking instruction to overtake the delayed vehicle to a following vehicle that immediately follows the delayed vehicle.

Disclosed embodiments include technologies for improving safety mechanisms in computer assisted and/or automated driving (CA/AD) vehicles for protecting vulnerable road users (VRUs). Embodiments include various mechanisms to enable early Responsibility Sensitive Safety (RSS) checks for the CA/AD vehicles driving policy to protect in-danger VRUs. Embodiments also include controlled forwarding mechanisms to notify other CA/AD vehicles and roadside infrastructure when a potentially dangerous situation is detected. Other embodiments are described and/or claimed.

An information processing server includes a target vehicle data recognition unit configured to recognize target vehicle data including a traveling state of a target vehicle and position information of the target vehicle on a map, an unstable behavior position recognition unit configured to recognize an unstable behavior position which is a position on the map, at which at least one target vehicle has performed an unstable behavior, based on a plurality of pieces of the target vehicle data, a determination unit configured to determine whether the unstable behavior position is in a continuous occurrence situation or a discontinuous situation, based on whether or not a plurality of the target vehicles perform the unstable behavior at the unstable behavior position, and a storage processing unit configured to store a determination result by the determination unit, in a storage database in association with the unstable behavior position.

Methods and systems for dynamically providing routes to users of vehicles. In some examples, a method includes determining a first traffic flow model for uninformed drivers of vehicles and determining a second traffic flow model for informed drivers of vehicles. Each of the informed drivers makes driving decisions based on receiving dynamic routes from a traffic routing system. The method includes iteratively updating the second traffic flow model using the first traffic flow model until a convergence criterion is met. The method includes sending, to at least one informed driver, a first dynamic route from a first origin to a first destination using the second traffic flow model.

Various examples are directed to systems and methods for routing an autonomous vehicle. For example, a system may access temporal data comprising a first temporal data item. The first temporal data item may describe a first roadway condition, a first time, and a first location. The system may also access a routing graph that comprises a plurality of route components and determine that a first route component of the routing graph corresponds to the first location. The system may generate a constrained routing graph at least in part by modifying the first route component based at least in part on the first roadway condition. The system may additionally generate a route for an autonomous vehicle using the constrained routing graph; and cause the autonomous vehicle to begin traversing the route.

A control system and a method for vehicle control in geographical control zones is provided. The control system receives traffic information, including a plurality of image frames of a group of moving objects in a geographical control zone and generates a set of images frames of a first moving object of the group of moving objects based on application of a trained Neural Network (NN) model on the received traffic information. The generated set of image frames corresponds to a set of likely positions of the first moving object at a future time instant. The control system predicts the unsafe behavior of the first moving object based on the generated set of image frames and generates first control information, including an alternate route for a first vehicle in the geographical control zone based on the predicted unsafe behavior. The first vehicle is controlled based on the generated first control information.

The present disclosure relates to an electronic device, a wireless communication method and a computer-readable storage medium. The electronic device for a vehicle according to the present disclosure comprises a processing circuit configured to: determine load information of the vehicle; generate vehicle information, with the vehicle information comprising the load information of the vehicle; and send the vehicle information to a server for the server to determine, according to the vehicle information, road planning information for the vehicle. By using the electronic device, the wireless communication method and the computer-readable storage medium according to the present disclosure, the load information of the vehicle can be taken into consideration during road planning and decision planning, thereby better managing the load of the vehicle and more rationally planning a road.

Systems and methods are provided for vehicle navigation. In one implementation, a system for navigating a vehicle may include at least one processor configured to receive a first image frame; detect in the first image frame a representation of a traffic light and determine a color state associated with lamps included on the traffic light. The at least one processor may receive an additional image frame includes a representation of the at least one traffic light; and determine, based on a comparison of the first image frame and the additional image frame, whether the at least one traffic light includes a blinking lamp. If the at least one traffic light includes a blinking lamp, the processor may cause the vehicle to implement a navigational action relative the traffic light in accordance with the determination and also based on a detected color state for the blinking lamp.