Cooperative CAVs optimal trajectory planning for collision avoidance and merging in the weaving section

Abstract

Weaving sections may cause massive congestion and accident problems. Connected and automated vehicles (CAVs) are acknowledged to improve traffic safety and efficiency through effective communication and control. To this end, this study proposes a centralized cooperative vehicle trajectory planning framework for SAE Level 4 or 5 automation. Specifically, focusing on the complex movements at weaving sections, the longitudinal optimal trajectory control is proposed to avoid collisions. This improves traffic efficiency and reduces fuel consumption and driver discomfort. A sideswipe collision prediction algorithm takes into account the geometric features of vehicles and predicts the time of the collision. The merging sequences model with safety constraints is developed to avoid the collision between the on-ramp and off-ramp vehicles. The effectiveness of the proposed model is validated through simulations, where the proposed method is compared with the baseline to demonstrate its potential in improving safety and reducing the fuel consumption and travel time.

KEYWORDS:

• Connected and automated vehicle
• cooperative optimal trajectory planning
• collision avoidance
• merging sequences
• weaving section

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This research was supported by the National Key Research and Development Program of China [grant number 2018YFB1600604], National Natural Science Foundation of China [grant numbers 61603058 and 61703053], “111” Project on Information of Vehicle-Infrastructure Sensing and ITS [grant number B14043], Natural Science Foundation of Shaanxi Province [grant number 2018JQ6035], Key Research and Development Plan of Shaanxi Province [grant number 2018ZDCXL-GY-04-02], and the Fundamental Research Funds for the Central Universities [grant numbers 300102249702 and 300102248301].