Abstract
Closed-loop validation of autonomous vehicles is an open problem, significantly influencing development and adoption of this technology. The main contribution of this paper is a novel approach to reproducible, scenario-based validation that decouples the problem into several sub-problems, while avoiding to brake the crucial couplings. First, a realistic scenario is generated from the real urban traffic. Second, human participants, drive in a virtual scenario (in a driving simulator), based on the real traffic. Third, human and automated driving trajectories are reproduced and compared in the real vehicle on an empty track without traffic. Thus, benefits of automation with respect to safety, efficiency and comfort can be clearly benchmarked in a reproducible manner. Presented approach is used to benchmark performance of SBOMP planner in one scenario and validate SuperHuman driving performance.
| Original language | English |
|---|---|
| Title of host publication | 2020 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2020 |
| Pages | 3860-3867 |
| Number of pages | 8 |
| Volume | 2020-October |
| ISBN (Electronic) | 9781728185262 |
| DOIs | |
| Publication status | Published - 11 Oct 2020 |
| Event | 2020 IEEE International Conference on Systems, Man, and Cybernetics - Virtuell, Canada Duration: 11 Oct 2020 → 14 Oct 2020 |
Conference
| Conference | 2020 IEEE International Conference on Systems, Man, and Cybernetics |
|---|---|
| Abbreviated title | IEEE SMC 2020 |
| Country/Territory | Canada |
| City | Virtuell |
| Period | 11/10/20 → 14/10/20 |
Keywords
- automated driving
- lane change
- multi-lane driving
- planning
- SuperHuman
- traffic lights
- urban driving
- validation
ASJC Scopus subject areas
- Software
- Human-Computer Interaction
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Computer Science Applications