Modular vehicle routing for combined passenger and freight transport

This study investigates the potential of modular vehicle concepts and consolidation to increase the efficiency of urban freight and passenger transport. Modularity is achieved by connecting multiple vehicles together to form a platoon. Consolidation is realized by integrating passenger and freight demand in the routing problem. Vehicles are...

Quantifying travellers’ evaluation of waiting time uncertainty in public transport networks

Although waiting times are inherently uncertain in public transport networks, previous research has primarily studied route choice behaviour under risk. Since understanding such behaviour is important to correctly model network flows and gain better understanding of traveller satisfaction, we propose a method to assess travellers’ route...

A passenger-pedestrian model to assess platform and train usage from automated data

We present a transit model that, based on automated fare collection and train tracking data, describes pedestrian movements in train stations and vehicle-specific train ridership distributions. Our approach differs from existing models in that we describe on-board passenger dynamics and pedestrian dynamics at stations in a joint framework. We...

Determinants of bus riding time deviations: Relationship between driving patterns and transit performance

Urban bus services are subject to high levels of uncertainty and disturbances. Methods to determine the timetable are designed to absorb variations in riding times between stops by allocating additional travel time. The propagation of service unreliability along the route could be restrained by drivers' adjustment at stops and between stops....

Automated Setting of Bus Schedule Coverage Using Unsupervised Machine Learning

The efficiency of Public Transportation (PT) Networks is a major goal of any urban area authority. Advances on both location and communication devices drastically increased the availability of the data generated by their operations. Adequate Machine Learning methods can thus be applied to identify patterns useful to improve the Schedule Plan. In...