Name
Abstract | ||
|---|---|---|
This paper presents an obstacle avoidance algorithm for low speed autonomous vehicles (AV), with guaranteed safety. A supervisory control algorithm is constructed based on a barrier function method, which works in a plug-and-play fashion with any lower level navigation algorithm. When the risk of collision is low, the barrier function is not active; when the risk is high, based on the distance to an avoidable set, the barrier function controller will intervene, using a mixed integer program to ensure safety with minimal control effort. This method is applied to solve the navigation and pedestrian avoidance problem of a low speed AV. Its performance is compared with two benchmark algorithms: a potential field method and the Hamilton-Jacobi method. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TCST.2017.2654063 | IEEE Trans. Contr. Sys. Techn. |
Keywords | Field | DocType |
Safety,Vehicle dynamics,Navigation,Supervisory control,Collision avoidance,Heuristic algorithms,Autonomous vehicles | Obstacle avoidance,Integer,Control theory,Pedestrian,Supervisory control,Control theory,Control engineering,Collision,Barrier function,Vehicle dynamics,Mathematics | Journal |
Volume | Issue | ISSN |
26 | 1 | 1063-6536 |
Citations | PageRank | References |
8 | 0.55 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuxiao Chen | 1 | 29 | 6.20 |
| Huei Peng | 2 | 805 | 150.82 |
| J. w. Grizzle | 3 | 2188 | 215.15 |