Multi-Vehicle Planning using RRT-Connect*

Paladyn: Journal of Behavioral Robotics

Kala Rahul¹  Warwick Kevin¹ 

[1] School of Cybernetics, School of Systems Engineering, University of Reading, Whiteknights, Reading, Berkshire, United Kingdom;

关键词: autonomous vehicles;    rapidly exploring random trees;    rrt-connect;    multi-robot path planning;    coordination;    robocars;    planning;    intelligent vehicles;   

DOI  :  10.2478/s13230-012-0004-5

来源: DOAJ

【 摘 要 】

The problem of planning multiple vehicles deals with the design of an effective algorithm that can cause multiple autonomous vehicles on the road to communicate and generate a collaborative optimal travel plan. Our modelling of the problem considers vehicles to vary greatly in terms of both size and speed, which makes it sub-optimal to have a faster vehicle follow a slower vehicle or for vehicles to drive with predefined speed lanes. It is essential to have a fast planning algorithm whilst still being probabilistically complete. The Rapidly Exploring Random Trees (RRT) algorithm developed and reported on here uses a problem specific coordination axis, a local optimization algorithm, priority based coordination, and a module for deciding travel speeds. Vehicles are assumed to remain in their current relative position laterally on the road unless otherwise instructed. Experimental results presented here show regular driving behaviours, namely vehicle following, overtaking, and complex obstacle avoidance. The ability to showcase complex behaviours in the absence of speed lanes is characteristic of the solution developed.

【 授权许可】

Unknown