No abstract

Short-term disruptions can have a long-lasting negative effect on traffic flow exceeding the duration of the disruption itself. This is especially the case when traffic demand approaches the network’s capacity. On-demand ride-sourcing services like ride-hailing and ride-pooling do not only have an impact on the overall kilometers driven in a network, but also conduct frequent stopping maneuvers to let passengers board and alight. As further growth of such services is expected, municipalities will need to find ways to organize and, if needed, regulate such activities. This paper proposes, evaluates, and discusses two possible methods that can be part of a holistic strategy to mitigate the impacts of frequent mobility-on-demand curbside stops in an urban environment. The first method adapts the positions of stops at an intersection according to real-time signal timings without adding another variable to the already quite complex traffic signal optimization. The second method discusses a temporary reduction of the number of allowed stopping maneuvers on saturated street sections or in other sensitive areas. Both methods are evaluated using microscopic traffic simulation and result in significant reductions of average vehicle delay as well as standard deviation thereof in all investigated traffic demand scenarios. These results indicate that the proposed methods can help to preserve a stable traffic state in situations close to the capacity limit, which is to the benefit of all stakeholders involved.

Connected and automated vehicles (CAVs) will behave fundamentally differently than human drivers. In mixed traffic, this could lead to inefficiencies and safety-critical situations since neither human drivers nor CAVs will be able to fully anticipate or predict surrounding traffic dynamics. Thus, some researchers proposed to separate CAVs from conventional vehicles by dedicating exclusive lanes to them. However, the separation of road infrastructure can negatively impact the system’s capacity. While the effects of CAV lanes were addressed for freeways, their deployment in urban settings is not yet fully understood. This paper systematically analyzes the effects of CAV-lanes in an urban setting accounting for the corresponding complexities. We employ microscopic traffic simulation to model traffic flow dynamics in a detailed manner and to be able to consider a wide array of supply-related characteristics. These concern intersection geometry, public transport operation, traffic signal control, and traffic management. Our study contributes to the existing literature by revealing the potential of CAV lanes in an urban setting while accounting for the behavioral and topological complexities. The results of this study can support decision-makers in the design of future urban transportation systems and to prepare cities for the upcoming era of automation in traffic.