Posted in January 2014

This paper presents research on synchronization of transfers and its impact on service reliability from a passenger perspective. Passenger reliability is analyzed for the case of a multi-operator transfer node. A method is developed to calculate the passenger centered reliability indicators: additional travel time and reliability buffer time, using scheduled and actual vehicle arrival and departure times as an input. Five major factors are identified as affecting reliability at a particular transfer: scheduled transfer time, distributions of actual arrivals of the first and second line, headways, transfer walking time, and transfer demand. It is demonstrated in a real network case that changing a specific transfer has effects on other transfers from the transfer point. This method can be applied in a cost benefit analysis to identify the benefits and costs of reliability for different groups of passengers, thereby supporting proper decision making.

This paper won the Best Paper Award of all submissions by the TRB Committee on Transit Capacity and Quality of Service.

Read more: Paper Lee TRB 2014

Nowadays, transport demand models do not explicitly evaluate the impacts of service reliability of transit. Service reliability of transit systems is adversely experienced by users, as it causes additional travel time and unsecure arrival times. Because of this, travelers are likely to perceive a higher utility from higher reliable transport systems. In order to mimic and measure the impacts of service reliability on a transit demand model a three-step approach is proposed using intelligent transport systems data. The approach consists of determining the probabilistic distribution of transit trip times, defining demand patterns and estimating the average impacts of unreliability per passenger. This approach was successfully tested on the model of the city of Utrecht in The Netherlands. By adding service reliability as a variable parameter of transit systems the results of the demand model improved showing that the absolute difference between the observed and the estimated demand decreased by 18%. In addition, the proposed approach allows measuring the effects of expected changes in level of service reliability on traveler behavior. Finally, the authors have identified future research topics required to improve the estimation of those effects

Read more: TRB 2014 Paper Van Oort