Abstract
As the level of passenger demand in rail transit systems increases, major railway stations in urban centres face serious capacity issues. Both analytical and simulation methods have been used to analyse complex station areas; however, prior efforts have only focused on either train or pedestrian movements with over-simplified assumptions that do not properly capture the impact of their interaction on capacity. This study applies an integrated crowd and transit simulation platform “Nexus” to simultaneously study the impact of pedestrian and train movements on the system performance of a complex railway station. Unlike other methods such as sequential simulation methods, the integrated simulation platform permits linkage between commercial-grade simulators. Instead of treating each simulator separately, this integrated method enables detailed modelling of how the train and crowd dynamic interact at station platforms. Such integration aims to explore the interactive effect on both types of movement and enable performance analysis possible only through this combination. To validate the model, a case study is performed on Toronto’s Union Station. Extensive data were collected, processed and input into railway and pedestrian models constructed using OpenTrack and MassMotion, respectively, and integrated via Nexus. Examining scenarios of increased levels of train and passenger volumes, a 9% drop in on-time performance of train operation is observed, while the level of service experienced by passengers on the platform deteriorates significantly due to crowding. Both length and variation in dwell time due to pedestrian movement are recognized as the main factors of performance deterioration, especially when the system approaches capacity limit. The simulation model produces estimates of the practical track-side capacity of the station and associated platform crowding levels, and helps identify locations where passengers experience severe overcrowding, which are not easily obtainable from mathematical models.
Highlights
Passenger rail hubs have become the beating heart of transit systems in large cities
For scenarios 1–5, all measures indicate deteriorating performance as passenger volumes increase for both train movements (9% drop in simulated on-time performance (SOTP)) and pedestrian movements
Similar trends can be observed for the average dwell time and its standard deviation, both rising with the inbound passenger volume
Summary
Passenger rail hubs have become the beating heart of transit systems in large cities. Expanding railway infrastructure and station size to accommodate this growth is an expensive proposition in many of these cases: Limited additional space in urban rail corridors, historic buildings that require special consideration during renovations, and the high cost of land near these stations all make infrastructure expansion a long-term option for improved capacity. Station operators must look for ways to manage increased volumes more efficiently [1]. This requires complex and comprehensive analysis of a hub’s rail and passenger capacity to better understand the root causes of overcrowding and delay due to congestion
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