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Modeling Left-Turn Driving Behavior at Signalized Intersections with Mixed Traffic Conditions

机译:用混合交通状况建模左转驾驶行为

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摘要

In many developing countries, mixed traffic is the most common type of urban transportation; traffic of this type faces many major problems in traffic engineering, such as conflicts, inefficiency, and security issues. This paper focuses on the traffic engineering concerns on the driving behavior of left-turning vehicles caused by different degrees of pedestrian violations. The traffic characteristics of left-turning vehicles and pedestrians in the affected region at a signalized intersection were analyzed and a cellular-automata-based “following-conflict” driving behavior model that mainly addresses four basic behavior modes was proposed to study the conflict and behavior mechanisms of left-turning vehicles by mathematic methodologies. Four basic driving behavior modes were reproduced in computer simulations, and a logit model of the behavior mode choice was also developed to analyze the relative share of each behavior mode. Finally, the microscopic characteristics of driving behaviors and the macroscopic parameters of traffic flow in the affected region were all determined. These data are important reference for geometry and capacity design for signalized intersections. The simulation results show that the proposed models are valid and can be used to represent the behavior of left-turning vehicles in the case of conflicts with illegally crossing pedestrians. These results will have potential applications on improving traffic safety and traffic capacity at signalized intersections with mixed traffic conditions.
机译:在许多发展中国家,混合交通是最常见的城市交通类型;这种类型的流量面临交通工程中的许多主要问题,例如冲突,低效率和安全问题。本文侧重于交通工程问题对由不同程度的行人违规行为引起的左转车辆的驾驶行为问题。分析了左转车辆和行人的流量特性,并分析了信号交叉口的受影响区域,并提出了一种基于蜂窝自动机的“后续冲突”驾驶行为模型,主要解决了四种基本行为模式,以研究冲突和行为左转车辆通过数学方法的机制。在计算机模拟中再现四种基本驾驶行为模式,并且还开发了行为模式选择的Logit模型来分析每个行为模式的相对共享。最后,确定受影响区域中交通流量的驾驶行为的微观特征和越来越的流量。这些数据对信号交叉口的几何和容量设计是重要的参考。仿真结果表明,拟议的型号有效,可用于代表与非法交叉行人冲突的左转车辆的行为。这些结果将有潜在的应用,即提高信号交叉口的交通安全和交通量的交通量。

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