基于风险量化的自适应式巡航控制及其在信号交叉点接近行为中的应用
Haozhan Ma1, Chen Qian1, Linheng Li1
1School of Transportation, Southeast University, Nanjing, Jiangsu Province 211189, PR China; Institute on Internet of Mobility, Southeast University and University of Wisconsin-Madison, Southeast University, Nanjing, Jiangsu Province 211189, PR China.
Accident; analysis and prevention
|January 29, 2025
概括
本研究引入了基于风险的自适应巡航控制 (RACC) 连接和自动驾驶汽车 (CAV) 以减少信号上的交通振荡. RACC显著减少了延误和燃料消耗,改善了交通流量和安全.
科学领域:
- 智能运输系统 智能运输系统
- 控制理论 控制理论
- 汽车工程 汽车工程
背景情况:
- 交通信号引发停止和继续行为,危及交通安全,效率和燃油经济.
- 互联和自动驾驶汽车 (CAV) 为缓解这些问题提供了潜在的解决方案.
研究的目的:
- 开发和评估一种新的基于风险的自适应式巡航控制 (RACC) 系统,用于CAV.
- 为了最大限度地减少交通波动,并提高信号交叉点的性能.
主要方法:
- RACC将交叉约束模型作为风险,确保适应性和合规性.
- 理论分析证实了弦的稳定性和过度缩的特性.
- 模拟验证了RACC在各种交通条件和市场透率 (MPR) 下的性能.
主要成果:
- 通过及时基于风险的调整,RACC确保了排队安全和高吞吐量.
- 配备RACC的CAV表现出平稳的轨迹,减少风险,延误和燃料消耗.
- 观察到显著的减少:旅行时间延迟高达87.1%,燃油消耗高达54.8%.
结论:
- RACC有效地减轻了信号交叉点的交通波动.
- 该系统显示了比现有方法显著的计算效率和性能改进.
- 未来的研究应该在复杂的场景中探索RACC,例如多车道道路和变车道.
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