Can passenger flow distribution be estimated solely based on network properties in public transport systems?
- PDF / 2,447,774 Bytes
- 20 Pages / 439.37 x 666.142 pts Page_size
- 72 Downloads / 200 Views
Can passenger flow distribution be estimated solely based on network properties in public transport systems? Ding Luo1 · Oded Cats1 · Hans van Lint1
© The Author(s) 2019
Abstract We present a pioneering investigation into the relation between passenger flow distribution and network properties in public transport systems. The methodology is designed in a reverse engineering fashion by utilizing passively measured passenger flow dynamics over the entire network. We quantify the properties of public transport networks using a range of centrality indicators in the topological representations of public transport networks with both infrastructure and service layers considered. All the employed indicators, which originate from complex network science, are interpreted in the context of public transport systems. Regression models are further developed to capture the correlative relation between passenger flow distribution and several centrality indicators that are selected based on the correlation analysis. The primary finding from the case study on the tram networks of The Hague and Amsterdam is that the selected network properties can indeed be used to approximate passenger flow distribution in public transport systems to a reasonable extent. Notwithstanding, no causality is implied, as the correlation may also reflect how well the supply allocation caters for the underlying demand distribution. The significance and relevance of this study stems from two aspects: (1) the unraveled relation provides a parsimonious alternative to existing passenger assignment models that require many assumptions on the basis of limited data; (2) the resulting model offers efficient quick-scan decision support capabilities that can help transport planners in tactical planning decisions. Keywords Public transport systems · Passenger flow distribution · Network properties · Topology · Centrality · Complex network science
Introduction Estimation and prediction of passenger flow distribution is one of the most significant topics in the field of public transport (PT) research given its critical role in assisting planning and management. The conventional approach, like that in the road traffic research, is to develop passenger assignment models which take demand profiles—typically in the * Ding Luo [email protected] 1
Department of Transport and Planning, Faculty of Civil Engineering and Geosciences, Delft University of Technology, P.O. Box 5048, 2600 GA Delft, The Netherlands
13
Vol.:(0123456789)
Transportation
form of origin–destination matrices—as input and then distribute the demand across the network (Ortúzar and Willumsen 2011). These models are normally referred to as transit assignment models in the transport research community, and their core pertains to modeling travelers’ route choices in PT systems as functions of network conditions and travel preferences (Liu et al. 2010). Two types of static equilibrium transit assignment models have been mostly developed over the past decades, namely the frequency-based and schedule-b
Data Loading...
