Research on differential constraints-based planning algorithm for autonomous-driving vehicles

For better timing performance, existing autonomous driving platforms generally introduce local planner into the conventional two-layer path panner scheme (path planning { path following) to reduce the requirements for costly global replanning by avoiding collision with obstacles while keeping tracking the desired path. This paper presents an improved three-layer planning algorithm for fully autonomous driving in real scenarios at a speed up to 40 km/h. Compared with general algorithms, differential constraints are taken into account in the local planner to improve the elegance in steering control and provide a better tracking ability at high speed. Longitudinal planning based on speed profile under dynamic constraints is involved in the planner as well so as to provide the smoothness safety and stability in driving. Desired motion commands are generated based on the local environment without manually tuned parameters, which is helpful for a general-purpose autonomous driving system. The algorithm was implemented on the BIT self-driving platform in 2011 and 2012 Intelligent Vehicle Future Challenge.