Buses operating in mixed traffic experience problems with delay and travel time variability in peak periods. Numerous transit priority measures are found in the literature but most rely on separating buses from other vehicles. Complete separation such as dedicated bus lanes might underutilize the system capacity when the frequency of buses is not high. We propose a “dynamic bus lane policy”, where control adjusts the proportion of cars to buses in one lane of a multi-lane arterial instead of enforcing complete separation of vehicle types. This strategy is analyzed with aggregated macroscopic dynamics for different models of lane choice. It is shown to benefit both cars and buses by maintaining higher outflow during the peak period and helping the system to recover more quickly at the end of the peak. Greater reductions in travel time are possible with increased information available to vehicles. Analytical derivations and non-linear optimization are then used to obtain the system optimal allocation of cars, as well as the toll needed to achieve it. The system optimal tolling would be difficult to implement in practice. Another optimization which includes tolls paid in its objective is nearly as good at reducing vehicle hours traveled and produces a much simpler pricing structure amenable to feedback control. A microsimulation with feedback control confirms the results of the macroscopic model and shows additional benefits attributable to driver behavior. Future work will look into varying control parameters to achieve a global minimum travel time and will incorporate user heterogeneity to test pricing strategies.

在混合交通中行驶的公交车在高峰时段会遇到延误和行驶时间变化的问题。文献中有许多公交优先措施，但大多数措施是将公交车与其他车辆分开。当公交车的频率不高时，诸如专用公交车道之类的完全隔离可能会利用系统容量不足。我们提出了一项“动态公交专用道政策”，其中控制措施是在多车道动脉的一个专用道中调整汽车与公交车的比例，而不是强制完全分离车辆类型。针对不同车道选择模型，使用汇总宏观动力学分析了此策略。通过在高峰期保持较高的流出量并在高峰期结束后帮助系统更快地恢复，它对汽车和公交车均有利。随着车辆可用信息的增加，可以大大减少旅行时间。然后，使用分析性推导和非线性优化来获得系统对汽车的最佳分配以及实现这一目标所需的通行费。该系统的最佳通行费在实践中将难以实现。另一个包括按目标收费的通行费的优化措施，在减少行车时间方面几乎同样出色，并且产生了一种更简单的价格结构，易于进行反馈控制。带有反馈控制的微观仿真证实了宏观模型的结果，并显示了可归因于驾驶员行为的其他好处。未来的工作将研究各种控制参数以实现全球最小旅行时间，并将结合用户的异质性来测试定价策略。