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First published online April 28, 2019

Long-Term Upgrade Strategy for Light Rail and Regional Rail: Robust Methodological Approach

Abstract

Suburban light rail transit (LRT) and regional rail systems face similar challenges when it comes to upgrade perspectives. A particular planning process is required for upgrade measures apart from conventional alignment modifications. This study investigated the similarities between LRT and regional rail characteristics and developed a robust decision framework that linked demand modeling, timetable construction, and infrastructure design in an integrated approach. The study applied a three-stage planning process for a regional railway system in a midsized Austrian city. A multimodal travel demand model that included demographic changes over the next 2 decades was used. Travel demand was calculated with the current timetable and forecasted changes in regional planning. Within a sensitivity analysis, the impact of alternative timetables on modal shift was checked. A detailed analysis of these results was undertaken to optimize the best-ranked timetable model. Different infrastructure measures such as electrification, double-track sections, road grade crossings, station layout, and alignment changes were identified to match the optimal target timetable with fixed hub-to-hub travel times. Various stakeholders were involved in deciding the political objectives of modal shares, transit headways, and regional rail infrastructure. A well-defined planning process with fixed milestones led to a common agreement on a stepwise upgrade plan for the next 25 years. The proposed method can be applied to regional rail as well as LRT.

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Article first published online: April 28, 2019
Issue published: January 2015

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Stefan Walter
Institute of Railway Engineering and Transport Economy, Graz University of Technology, Rechbauerstrasse 12, 8010 Graz, Austria.
Martin Fellendorf
Institute of Highway Engineering and Transport Planning, Graz University of Technology, Rechbauerstrasse 12, 8010 Graz, Austria.

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