4 results about "Local road" patented technology

The application discloses a vehicle positioning method and device, electronic equipment and computer storage medium. The vehicle positioning method comprises the following steps: performing road perception processing on a collected target image to obtain a road center point in a vehicle coordinate system; performing projection processing on the road center point according to a vehicle trajectory to obtain current local road information of the vehicle; performing matching processing on the current local road information and each local road information in a positioning area of the vehicle; and determining a road center point in target local road information matched with the current local road information in the positioning area as a target position of the vehicle. In this way, the positioning accuracy of vehicle position information can be improved.

This invention provides an intelligent operation and maintenance scheduling method for charging stations based on a large language model and multi-starting-point policy reinforcement learning. The main steps include: collecting alarm and latitude / longitude data of target charging stations, and constructing a symmetrical global time-distance matrix by combining macro and local road networks; initializing the large language model decision center to generate macro control parameters (including weight parameters and penalty coefficients for each region, and the number of clusters) containing the number of operation and maintenance personnel; using a clustering algorithm based on these parameters to divide all stations into several controlled operation and maintenance areas; extracting real two-dimensional coordinates, using a multi-starting-point policy reinforcement learning network to perform path planning for stations within the operation and maintenance areas, and implementing real-time posterior arbitration; calculating the total maintenance time and workload variance of the planned routes; if the target is not met, generating a natural language diagnostic report and feeding it back to the large language model to readjust the weight coefficients, penalty coefficients, and number of clusters, and iterating until the solution meets the workload balance satisfaction threshold; and outputting the final optimal path planning routes and total time consumption for all target operation and maintenance charging stations.

The application discloses a highway automatic driving commercial vehicle trajectory prediction and decision method and system based on complex network theory, which utilizes a complex network encoder in a prediction model to encode a high-definition map and an agent context into node coding of a directed weighted complex network to obtain the accessibility of each node.A target point predictor predicts target points of each agent according to historical trajectory information and local road features of the agent, and obtains a joint distribution of reference trajectories in combination with lane node accessibility and agent node criticality.A trajectory decoder inputs historical trajectories of the agent and kinematics or dynamics constraints to decode and generate a predicted trajectory and optimize the predicted trajectory under the condition of the reference trajectory.A decision model inputs a navigation route provided by an upstream global path planning layer, judges whether there is a lane changing requirement, and determines a priority of a lane.Combining a joint distribution probability of the reference trajectory, a complex network risk value and the lane priority, a cost function is designed to select an optimal trajectory as a decision result.