PhD student - Passenger behavioural response to planned railway maintenance disruptions

PhD student - Passenger behavioural response to planned railway maintenance disruptions 100%, Zurich, fixed-term

The Chair of Transportation and Mobility Planning, led by Professor Dr. Eva Heinen within the Institute for Transport Planning and Systems of the Department of Civil, Environmental and Geomatic Engineering (D-BAUG) is looking for a PhD candidate.

This position focuses on the development of revealed and stated preference surveys to model passenger response to the effects on train service of planned railway maintenance disruptions in Switzerland.

Railway infrastructure provides substantial capacity for the movement of people and goods, yet this capacity is reduced or suspended whenever there are interventions. Interventions, which range from condition monitoring through minor and major maintenance to renewal and expansion, require time, money, machines, and personnel, and they partially block access to the track. Consequently, traffic and timetables must be modified, and passengers are affected.

Decisions on when, where, and how such interventions should be grouped or separated, and on how the associated timetables should be planned, must be taken well ahead of execution and under considerable uncertainty regarding maintenance costs, timetable feasibility, and passenger impact.

In terms of impact on passenger demand, very little is known about the range of traveller’s response to planned maintenance disruptions. These disruptions can have a wide variety of effects for passengers such as increased travel time, additional transfers, reduced train frequency, increased likelihood of delays and crowdedness, replacements services (e.g., bus). These effects, in turn, can affect the decision to travel (cancel travel, work from home), the choice of alternative routes, the travel mode and even destination choices.

To assess how different maintenance scenarios affect passenger response requires considering individual heterogeneity, time constraints, mode substitution, trip purpose, seasonality, etc. Furthermore, there is currently no known approach to estimate long-term effects on demand of planned service disruptions of railway networks. Long term effects on user dissatisfaction can include loss of reputation and trust in the railway operator and potentially affect political and social support for railway funding.

The contribution of our research group to this project is to develop revealed and stated preference surveys and estimate models of short and long-term passenger response considering various operational maintenance scenarios. The outputs of those models will be used as inputs to the other work packages of the project to improve the estimation of the inherent uncertainty related to railway maintenance interventions and, ultimately, guide decision-making.

As contribution to this project, the doctoral candidate will aim to:

• Review the literature on the impact of railway disruptions on passenger response (short and long term)
• Develop (longitudinal) revealed preference surveys and stated preference experiments
• Model stated and observed passenger response and obtain elasticities for the various effects of maintenance disruption on rail service quality
• Develop a methodology to assess the long-term impacts of experienced disruptions on trust and reputation of the railway operator and concurrent effect on public support for railway investment
• Regularly interact with the other research groups to align research outcomes

In addition to contributing to this research project, we are looking for a candidate who can:

• Participate in (ongoing) research projects and support the acquisition of new research projects
• Contribute to teaching and examinations
• Successfully author research papers in high-impact research journals and will successfully author and defend a doctoral dissertation on the main research project

• MSc degree in the fields of transportation, civil engineering, computer science, spatial planning, geography, geoinformation, psychology, economics, or an equivalent qualification
• You must have a Msc certificate before you start
• Experience with discrete choice modelling…