Heavy vehicle eco-driving control method for multi-red-green-light intersection considering preceding vehicle factors

By optimizing the path and speed of heavy-duty vehicles using the A* algorithm and control strategy, the problem of frequent stops of heavy-duty vehicles at traffic light intersections was solved, resulting in more efficient traffic flow and reduced fuel consumption.

CN116394940BActive Publication Date: 2026-06-23WUHAN UNIV OF TECH
2 Cites 0 Cited by

Patent Information

Application Number
CN202310363224.8
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2023-04-06
Publication Date
2026-06-23
Estimated Expiration
2043-04-06

AI Technical Summary

Technical Problem

Frequent stops by heavy-duty vehicles at traffic light intersections result in additional energy consumption, affecting driving comfort and traffic efficiency. Existing eco-driving strategies cannot effectively guide heavy-duty vehicles to navigate under multiple speed restrictions and interference from other vehicles.

Method used

The A* algorithm is used to determine the global optimal path. Combined with the first, second and third control strategies, the speed and fuel consumption rate of heavy-duty vehicles are optimized by predicting traffic light intervals and the longitudinal dynamics model of vehicles, so as to avoid frequent starts and stops and improve traffic efficiency.

Benefits of technology

It effectively avoids frequent starts and stops and slow traffic speeds for heavy-duty vehicles, improves traffic efficiency, reduces fuel consumption, and enhances driving comfort and environmental friendliness.

✦ Generated by Eureka AI based on patent content.
Patent Text Reader

Abstract

The application provides a heavy-load vehicle ecological driving control method for multiple-red-green-light intersections considering the influence of preceding vehicles, comprising the following steps: S1. obtaining the start point and end point position information of the current heavy-load vehicle and the traffic information between the start point and the end point of the current heavy-load vehicle, and determining the feasible path between the start point and the end point; S2. determining the global optimal path from the feasible path, and determining the remaining paths as suboptimal passing paths; S3. establishing a control strategy, including a first control strategy, a second control strategy and a third control strategy; S4. determining the maximum passing time and the minimum passing time of the current heavy-load vehicle passing through the kth red-green-light intersection between the start point and the end point, and predicting the green light interval of the front intersection in the feasible path of the heavy-load vehicle based on the maximum passing time and the minimum passing time; S5. determining control strategy determination parameters, including the real-time distance between vehicles, the safety distance between vehicles, the distance between the vehicle and the red-light intersection in the kth road section, the distance between the end point of the kth road section and the red-light intersection, and the average speed of the heavy-load vehicle on the distance already traveled in the kth road section; and S6. determining the control strategy of the current heavy-load vehicle according to the control strategy determination parameters.
Need to check novelty before this filing date? Find Prior Art