In In this study, we set out to explore how various spatial patterns of travel demand drive the effectiveness of ride-pooling services. To do so, we generate a broad range of synthetic, yet plausible demand patterns. We experiment with the number of attraction centres, the dispersion of destinations around these centres, and the trip length distribution. We apply a strategic ride-pooling algorithm across the generated demand patterns to identify shareability potential using a series of metrics related to ridepooling. Our findings indicate that, under a fixed demand level, vehicle-hour reduction due to ride-pooling can range between 18 and 59%. These results depend on the concentration of travel destinations around the centre and the trip length distribution. Ride-pooling becomes more efficient when trips are longer and destinations are more concentrated. A shift from a monocentric to a polycentric demand pattern is found to have a limited impact on the prospects of ride-pooling.

The most relevant issues related to headway variability in public transport planning, operations and quality of service are reviewed in this paper. We discuss the causes and consequences of headway variability, the alternative metrics that have been proposed to measure it, the preventive and reactive strategies to control headway variability in both research and practice, including the role of drivers and of present and future technology, and how service provision contracts might deal with headway variability through metrics and financial incentives. The most influential elements that explain headway variability along a route are the irregularity at which vehicles are dispatched, the scheduled frequency, the distance travelled or route length, the passenger demand and associated dwell times, and the number of stops. We conclude that there is a large gap between the state-of-the-art and the state-of-practice in terms of identification of headway variability issues, as well as in the development of mitigation and control measures. It is therefore paramount that future research will contribute to closing this gap by addressing organisational, contractual and technological barriers in the implementation of measures aimed at mitigating headway variability in public transport services.

Headway management can potentially reduce passenger waiting time and on-board crowding on high-frequency services. In this study, a headway control experiment was conducted and evaluated for Washington Metropolitan Area Transit Agency routes 70 and 79 in Washington, D.C. The field experiment is evaluated by performing a before–after empirical evaluation. The organizational process and challenges involved with the implementation are discussed. Overall, a reduction of 26% in passenger excess waiting time was attained, which implies annual time savings that translate into US$1 million. Even though the field experiment implementation was far from ideal, the benefits obtained so far might pave the road to a long-term commitment to shift into a fully controlled headway-based management.

Service reliability has an important impact on the satisfaction stated by public transport users with the service they receive. The main source of unreliability is found in headway variance, which also affects waiting times and distributes passengers unevenly across vehicles. However, it is still unclear how headway irregularity, with its impact in waiting, crowdedness and reliability, affect travellers’ service satisfaction. Different stated preference studies have identified non-linear impacts produced by overcrowding. However, none of these studies is directly related to users’ satisfaction evaluation. In this study, we investigate the existence of this non-linearity in users’ satisfaction caused by both the crowding level and the number of denied boardings through a post-service satisfaction survey of bus and metro users. An Ordered Logit Model was estimated, accounting for sample heteroscedasticity and preference heterogeneity. Overall, there is a significant and negative perception of the bus mode, keeping all other attributes equal. For users under 35 years old, comfort experienced almost always plays an important role in service satisfaction, while for those over 35 years old women are significantly more sensitive to this attribute. Most important, crowding has a negative and non-linear impact on how passengers evaluate their travel satisfaction. Using a Likert-type scale, this curve is convex. This relationship between crowding and satisfaction might bias service planning and delivery if performance indicators associated to service are not properly weighted by the number of passengers served. Improving level of service indicators in this direction might provide public transport agencies a clearer and more accurate perception of the actual users’ experience.