| Autor: |
Guo Ming James Fu, Baoxing Qin, Zhuang Jie Chong, Wei Liu, Xiaotong Shen, Marcelo H. Ang, Scott Pendleton |
| Rok vydání: |
2015 |
| Předmět: |
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| Zdroj: |
Intelligent Vehicles Symposium |
| DOI: |
10.1109/ivs.2015.7225901 |
| Popis: |
Vehicle-to-vehicle (V2V) communication enables intention sharing among neighboring vehicles and thereby vehicles' motion can be coordinated to incorporate collision (or conflict) avoidance. In this paper, we propose a general framework to distribute the computational burden for coordinating multiple vehicles' stop-or-go motion. We formulate the multi-vehicle motion coordination problem as a total stopping time minimization problem under the constraint of mutual collision avoidance. The minimal stopping time solution, if such exists, is found using the A∗ search algorithm in the coordination diagram. The solution is executed efficiently by placing temporary virtual obstacles on the desired path. The communication latency is analyzed for practical applications. The simulations show the correctness and efficacy of our algorithm. An on-road experiment involving two autonomous vehicles, each equipped with V2V communication devices, was performed to demonstrate how deadlocks are successfully avoided. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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