Skip-stop operation is a low cost approach to improving the efficiency of metro operation and passenger travel experience. This paper proposes a novel method to optimize the skip-stop scheme for bidirectional metro lines so that the average passenger travel time can be minimized. Different from the conventional “A/B” scheme, the proposed Flexible Skip-Stop Scheme (FSSS) can better accommodate spatially and temporally varied passenger demand. A genetic algorithm (GA) based approach is then developed to efficiently search for the optimal solution. A case study is conducted based on a real world bidirectional metro line in Shenzhen, China, using the time-dependent passenger demand extracted from smart card data. It is found that the optimized skip-stop operation is able to reduce the average passenger travel time and transit agencies may benefit from this scheme due to energy and operational cost savings. Analyses are made to evaluate the effects of that fact that certain number of passengers fail to board the right train (due to skip operation). Results show that FSSS always outperforms the all-stop scheme even when most passengers of the skipped OD pairs are confused and cannot get on the right train.
Optimized Skip-Stop Metro Line Operation Using Smart Card Data
2017
Article (Journal)
Electronic Resource
Unknown
Metadata by DOAJ is licensed under CC BY-SA 1.0
Robust and optimized urban rail timetabling using a marshaling plan and skip-stop operation
Taylor & Francis Verlag | 2020
|British Library Conference Proceedings | 2002
|Recognizing metro-bus transfers from smart card data
Taylor & Francis Verlag | 2019
|Continuous approximation for skip-stop operation in rail transit
Online Contents | 2013
|