When introducing several measures to prioritize public transport services (i.e.dedicated lanes, holding control and boarding from all the rear door) at the same time – is the total effect larger than its parts? In a new paper with Jens West, we assess the implementation of several bus service improvement measures in a simulation model. We then analyze the effect of isolated and combinations of measures, and validates the model using field experiment data from Stockholm. We found that the three tested measures exercised negative synergy effects, with their combined effect being smaller than the sum of their marginal contributions, except for headway-based holding, which exercised positive synergy effects with the two other measures.
Click here for the full paper
(agency’s campaign signs in Swedish advising passengers that they can also board the bus from the rear door when boarding bus line 4)
New working paper entitled “Optimal Infrastructure Capacity for Rail-bound Demand Responsive Transit” is now available. Click here for full paper: Rail DRT
Abstract: Fully-automated services allow for greater flexibility in operations and lower marginal operational costs. The objective of this study is to determine the capacity requirements of an envisaged automated rail demand responsive transit (DRT) system which offers a direct non-stop service. An optimization model for determining the optimal track and station platform capacities for a rail-DRT system so that passenger, infrastructure and operational costs are minimized is formulated. The macroscopic model allows for studying the underlying relations between technological, operational and demand parameters, optimal capacity settings and the obtained cost components. The model is applied to a series of numerical experiments followed by its application to part of the Dutch railway network. The results of the numerical experiments and the case study application indicate that – unlike conventional rail systems in which stations often are capacity bottlenecks – link capacity properties are more critical for the performance of automated rail-DRT systems than station capacity. The performance is benchmarked against the existing service suggesting that in-vehicle times can be reduced by 10% in the case study network with the optimal link and station capacity allocation comparable to those currently available in this heavy rail network. A series of sensitivity analyses was performed to test the consequences of network and demand settings as well as the characteristics of future automated rail-DRT systems.