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The dataset originates from a common revealed preferences survey conducted in 2023 across 9 European cities: Munich (Germany), Geneva (Switzerland), Jerusalem (Israel), Athens (Greece), Rotterdam (Net…
SUM Mobility Survey The objective of this survey is to investigate the travel preferences of the citizens of each Living Lab (LL). These travel preferences are collected before and after the implement…
We focus on the problem of defining optimal bike-sharing service regions that maximize demand coverage under the constraints of construction and operational budgets. Strategically located shared-bike…
In the case of modes like bike-sharing and scooter-sharing, fleet size decisions depend on rebalancing decisions. Smart and efficient fleet rebalancing algorithms can reduce not only operating costs,…
We consider the integration of ride-pooling fleets and public transport (PT) by developing a framework that restricts some ride-pooling vehicles to arrive at a PT station shortly before the arrival of…
We propose a preference-based optimization tool for multimodal trip planning. This tool, developed by TU Delft, integrates public transport, ride-pooling services, and shared micro-mobility options (e…
This tool assumes that fleet sizes for New Shared Modes are also subject to optimization. In this case, a full social welfare function is presented, in which users’ preferences are taken into ac…
Timetable synchronization seeks to optimize the timing of bus arrivals at transfer nodes, ensuring minimal waiting times for passengers transferring between routes. This is particularly important in m…
The SUM Simulation-Optimization Framework was developed by researchers from Tel Aviv University (TAU) and has been implemented in the Jerusalem Living Lab, in order to find promising New Shared Modes…