同时考虑结伴行为和逆行行为的自行车流元胞自动机模型

结伴行为和逆行行为是两种常见的骑行方式,容易引起自行车流的局部自组织现象和通行效率下降。为研究结伴行为(包括左右结伴和前后结伴)和逆行行为共存对自行车流运动机理和交通特性的影响,建立同时考虑结伴和逆行行为的自行车流元胞自动机模型。通过仿真实验,分别分析左右结伴和前后结伴与逆行共存对自行车流的影响。研究表明:左右结伴和逆行共存会显著降低自行车流的通行能力、增加旅行时间和降低平均速度;前后结伴和逆行共存仅在高车流密度条件下减少平均速度,且引起自行车流轻微振荡;上述负面影响同结伴尺寸、结伴比例、逆行比例和自行车平均到达率等因素有关。这些研究结果有助于更好地管理自行车流,特别是逆行行为管理。

Extended cellular automata model for bicycle flow considering group and retrograde behaviors

Group and retrograde behaviors are two common bicycle riding that generally induce some local self-organization phenomena and reduce traffic efficiency. Herein, an extended cellular aulomata model that considers group and retrograde behaviors is proposed to explore the impacts of the two behaviors on the movement mechanism and traffic characteristics of bicycle flow. Simulation experiments are performed to investigate the impacts of shoulder/following group behavior and retrograde behavior on bicycle flow. Simulation results show that a mixture of shoulder group behavior and retrograde behavior will reduce the traffic capacity, increase the travel time, and decrease the average riding speed. Alternatively, a mixture of following group behavior and retrograde behavior decrease only the average speed and cause a slight oscillation in bicycle flow. These aforementioned negative impacts are related to various factors: group size, group proportion, retrograde proportion, and average bicycle arrival rate. The findings of this study can facilitate improved bicycle flow management (particularly in the case of retrograde behavior).