An instance-based learning approach for evaluating the perception of ride-hailing waiting time variability

Understanding user's perception of service variability is essential to discern their overall perception of any type of (transport) service. We study the perception of waiting time variability for ride-hailing services. We carried out a stated preference survey in August 2021, yielding 936 valid responses. The respondents were faced with...

Automatic bottleneck detection using AVL data: A case study in Amsterdam

In daily practice, public transport authorities and operators are constantly searching for improvements in public transport operations. To this end, it is necessary to identify inefficiencies and bottlenecks in the current public transport services. In this paper, we propose a method to automatically detect bottlenecks in the public transport...

Value of Reliability for the Waiting Stage, In-vehicle Stage and Transfer Stage of Demand Responsive Transport (DRT) Services

On-demand modes are playing an ever-increasing role in urban transportation. In<br/>particular, Demand Responsive Transit (DRT) (shared on-demand modes such as<br/>shared ride-hailing and microtransit) can complement scheduled public transport<br/>thanks to their collective nature. These services offer flexible and convenient<br/>mobility: they...

Improving railway passengers experience: Two perspectives

This paper describes two perspectives to improve the passenger experience. The passenger satisfaction pyramid is introduced, consisting of the base of the pyramid (dissatisfiers) focusing on time well saved and the top of the pyramid (satisfiers) aiming at time well spent. The challenge in planning and design of public transport services is to...

Data driven enhancement of public transport planning and operations: Service reliability improvements and ridership predictions

Automatic Vehicle Location (AVL) and smartcard data are of great value in planning, design and operations of public transport. We developed a transport demand model, which utilizes smartcard data for overall and what-if analyses, by converting these data into passengers per line and OD-matrixes and allowing network changes on top of a base...