School of Transportation, Southeast University, Nanjing, China.
Centre for Informatics and Systems of the University of Coimbra, University of Coimbra, Coimbra, Portugal.
PLoS One. 2024 Mar 13;19(3):e0300286. doi: 10.1371/journal.pone.0300286. eCollection 2024.
The bilateral Bus Rapid Transit (BRT) system is a kind of BRT system in which the stops are located in the middle of the transit lane. By simultaneously serving transit lines in opposite directions, it is particularly designed to save space resources and enhance service quality. To improve the operational efficiency of the bilateral BRT, this paper optimizes the operational performance of bilateral BRT with elastic demand. The objective is to minimize the generalized time cost per passenger of the system by jointly optimizing the headway and number of stops of bilateral BRT. The cost includes the agency operating and user travel. The optimal design model is formulated as a mixed-integer program and solved using a fuzzy analytic hierarchy process (FAHP) and a genetic algorithm (GA). We conduct a case study and sensitivity analysis to show the effectiveness and reliability of the proposed approach. We conclude that the optimized minimum generalized cost per passenger is lower than the actual case for all demand levels, especially at off-peak hours, by about 22.5%. In addition, we find that the weights of agency and user costs have the most significant impact on headway, whereas the influence of walking, vehicle speed, and route length is minimal. In contrast, the optimal number of BRT stops is mostly influenced by the route length, and walking speed has essentially no effect on the optimal number of stops. Finally, we find that the generalized cost per passenger at peak hours is 10% to 15% smaller than at off-peak hours in various scenarios.
双边快速公交（BRT）系统是一种在公交专用道中间设置站点的BRT 系统。通过同时为相反方向的公交线路服务，它特别旨在节省空间资源并提高服务质量。为了提高双边 BRT 的运营效率，本文对具有弹性需求的双边 BRT 的运营性能进行了优化。其目标是通过联合优化双边 BRT 的发车间隔和站点数量，最小化系统每位乘客的广义时间成本。成本包括代理运营成本和用户出行成本。最优设计模型被制定为一个混合整数规划，并使用模糊层次分析法（FAHP）和遗传算法（GA）进行求解。我们进行了案例研究和敏感性分析，以展示所提出方法的有效性和可靠性。我们的结论是，对于所有需求水平，优化后的每位乘客最小广义成本都低于实际情况，尤其是在非高峰时段，约为 22.5%。此外，我们发现代理和用户成本的权重对发车间隔的影响最大，而步行、车辆速度和路线长度的影响最小。相比之下，BRT 站点的最佳数量主要受路线长度的影响，步行速度对最佳站点数量基本没有影响。最后，我们发现，在各种情况下，高峰时段每位乘客的广义成本比非高峰时段低 10%至 15%。
