Abstract
A two-stage method of intelligent vehicle (IV) decision making for traffic interaction in an intersection was proposed in this paper. In the first stage, a driver type recognition model was presented based on fuzzy logic to get the aggressive rate of social vehicles. In the second stage, a rule-based decision-making algorithm was used to generate the best behavior for IV based on vehicle's aggressive ratio and time to collision (TTC). Finally, a Co-simulation with Prescan and Matlab/Simulink was performed to verify the algorithm. The results show that the method could lead IV get through intersection safely and efficiently.
| Original language | English |
|---|---|
| Pages (from-to) | 917-922 |
| Number of pages | 6 |
| Journal | Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology |
| Volume | 36 |
| Issue number | 9 |
| DOIs | |
| Publication status | Published - 1 Sept 2016 |
Keywords
- Decision making
- Driver type
- Intelligent vehicle
- Intersection
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Song, W. L., Xiong, G. M., Wang, S. Y., & Chen, H. Y. (2016). Decision making for intelligent vehicles based on driver type analyzing in an intersection. Beijing Ligong Daxue Xuebao/Transaction of Beijing Institute of Technology, 36(9), 917-922. https://doi.org/10.15918/j.tbit1001-0645.2016.09.007