Name
Abstract | ||
|---|---|---|
At intersections and in merging traffic, intelligent road vehicles must solve challenging optimal control problems in real-time to navigate reliably around moving obstacles. We present a complete planner that computes collision-free, optimal longitudinal control sequences (acceleration and braking) using a novel visibility graph approach that analytically computes the reachable subset of path-velocity-time space. We demonstrate that our method plans over an order of magnitude faster than previous approaches, making it scalable and fast enough (tenths of a second on a PC) to be called repeatedly on-line. We demonstrate applications to autonomous driving and vehicle collision warning systems with many moving obstacles. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1109/IVS.2013.6629533 | Intelligent Vehicles Symposium |
Keywords | Field | DocType |
braking,acceleration,vehicle collision warning systems,optimal control,autonomous driving,optimal control problems,automated highways,acceleration control,intelligent road vehicles,graph theory,optimal longitudinal control planning,moving obstacles,path-velocity-time space,collision avoidance,visibility graph approach,optimal longitudinal control sequences,merging,uncertainty,planning,algorithms,trajectory | Warning system,Graph theory,Visibility graph,Optimal control,Control theory,Collision,Acceleration,Merge (version control),Mathematics,Scalability | Conference |
ISSN | ISBN | Citations |
1931-0587 | 978-1-4673-2754-1 | 9 |
PageRank | References | Authors |
0.77 | 5 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jeff Johnson | 1 | 21 | 4.67 |
| Kris K. Hauser | 2 | 759 | 52.72 |