Paper Info
Title
Speed Profile Optimisation For Intelligent Vehicles In Dynamic Traffic Scenarios
Abstract
In the autonomous navigation of intelligent vehicles, collision avoidance is essential for driving safety. Similar to the driving preference of human, the driving path and speed can be determined separately. This paper is concerned with speed profile optimisation problem for dynamic obstacle avoidance given the reference path. The optimisation consists of smoothness, risk, and efficiency terms with obstacle constraints. For task formulation, thes-tmotion space is constructed to describe the motion of the ego vehicle and obstacles. Then the high-dimensional trajectory space is mapped to the low-dimensionals-tspace for computational efficiency. The speed optimisation problem is transformed into a path searching problem considering collision avoidance and searching efficiency. RRT-based algorithm is proposed to search for the optimal speed profile in thes-tspace asymptotically. In each searching step, node extension strategy is designed for the space exploring efficiency; then the tree structure is locally refined for asymptotic optimisation. The optimal speed profile is generated after the searching process converges and the speed profile is planned periodically. For performance evaluation, simulation tests in typical traffic conditions are conducted based on the SUMO (Simulation of Urban MObility) platform. Results show the effectiveness and efficiency of this method.
Year
DOI
Venue
2020
10.1080/00207721.2020.1793227
INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
Keywords
DocType
Volume
Autonomous vehicles, speed profile, RRT, motion planning
Journal
51
Issue
ISSN
Citations 
12
0020-7721
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Zhuoyang Du100.34
Dong Li247567.20
Kaiyu Zheng300.34
Shan Liu431.74