Name
Title | ||
|---|---|---|
Roadside-assisted Cooperative Planning using Future Path Sharing for Autonomous Driving |
Abstract | ||
|---|---|---|
Cooperative intelligent transportation systems (ITS) are used by autonomous vehicles to communicate with surrounding autonomous vehicles and roadside units (RSU). Current C-ITS applications focus primarily on real-time information sharing, such as cooperative perception. In addition to realtime information sharing, self-driving cars need to coordinate their action plans to achieve higher safety and efficiency. For this reason, this study defines a vehicles future action plan/path and designs a cooperative path-planning model at intersections using future path sharing based on the future path information of multiple vehicles. The notion is that when the RSU detects a potential conflict of vehicle paths or an acceleration opportunity according to the shared future paths, it will generate a coordinated path update that adjusts the speeds of the vehicles. We implemented the proposed method using the open-source Autoware autonomous driving software and evaluated it with the LGSVL autonomous vehicle simulator. We conducted simulation experiments with two vehicles at a blind intersection scenario, finding that each car can travel safely and more efficiently by planning a path that reflects the action plans of all vehicles involved. The time consumed by introducing the RSU is 23.0% and 28.1% shorter than that of the stand-alone autonomous driving case at the intersection. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/VTC2021-FALL52928.2021.9625324 | 2021 IEEE 94TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2021-FALL) |
DocType | ISSN | Citations |
Conference | 2577-2465 | 0 |
PageRank | References | Authors |
0.34 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mai Hirata | 1 | 1 | 0.70 |
| Manabu Tsukada | 2 | 0 | 1.01 |
| Keisuke Okumura | 3 | 0 | 0.34 |
| Yasumasa Tamura | 4 | 0 | 2.37 |
| Hideya Ochiai | 5 | 3 | 3.13 |
| Xavier Défago | 6 | 0 | 0.34 |