Abstract

The objective of this paper is to discuss the replication of passenger congestion (overcrowding) effects on output path choices in public transport assignment models. Based on a comprehensive literature review, the impact of passenger overcrowding effects was summarised in 3 main categories: the inclusion of physical capacity constraints (limits); the feedback effect between transport demand and supply performance; and the feedback effect on travel cost (discomfort penalty). Further on, sample case studies are presented, which prove that the inclusion of capacity constraints might significantly influence the assignment output and overall results in public transport projects’ assessment – yet most state-of-the-practice assignment models would either miss or neglect these overcrowding-induced phenomena. In a classical 4-step demand model, their impact on passengers’ travelling strategies is often limited to path (route) choice stage, while in reality they also have far-reaching implications for modal choices, temporal choices and long-term demand adaptation processes. This notion has been investigated in numerous research works, leading to different assignment approaches to account for impact of public transport capacity constraints – a simplified, implicit approach (implemented in macroscopic-based models, e.g. PTV VISUM), and a more complex, explicit approach (incorporated in mesoscopic-based models, e.g. BusMezzo). In the simulation part of this paper, sample tests performed on a small-scale network aim to provide a general comparison between these two approaches and arising differences in the assignment output. The implicit approach reveals some differences in assignment output once network capacity constraints are accounted for – though in a simplified manner, and producing somewhat ambiguous output (e.g. in higher congestion scenarios). The explicit approach provides a more accurate representation of overcrowding-induced phenomena - especially the evolving demand-supply interactions in the event of arising congestion in the public transport network. Further studies should involve tests on a city-scale, multimodal transport model, as well as empirical model validation, in order to fully assess the effectiveness of these distinct assignment approaches. - The paper discusses the inclusion of overcrowding effects on path choices in public transport assignment models - These can be grouped into 3 main categories: physical constraints, demand-supply feedback and path discomfort cost - Sample case studies show that their inclusion may substantially affect the assignment output - Two general methods of modelling capacity constraints are: the implicit and explicit approach - An illustrative example shows that both approaches produce different output with the explicit one being more specific and adequate

Highlights

  • Path choice process comprises a crucial step within every single transport assignment model (Fig. 1)

  • Whereas the volumedelay function (VDF) functions are commonly available and widely applied to replicate the capacity limits in modern-day private transport (PrT) assignment models (Branston, 1976), the incorporation of capacity constraints effects in public transport (PuT) assignment models remains – to the best of our knowledge – much less examined and advanced, usually limited to individual case studies and modelling developments; in practical approach, the implications of capacity constraints on passenger path choices are often neglected in state-of-thepractice modelling algorithms

  • Evaluation and conclusions The objective of this paper was to discuss the incorporation of passenger congestion effects in public transport assignment models

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Summary

Introduction

Path choice (or route choice) process comprises a crucial step within every single transport assignment model (Fig. 1). The path cost formula comprises the following trip components: perceived travel times (i.e. in-vehicle, waiting, walking times), monetary costs (fares), transfer penalties and temporal utilities of earlier (or later) O-D connections – which are described in relative (weighted) terms, reflecting the user perceptions of disutility associated with particular trip stages (e.g. increased disutility associated with waiting and walking times) This path cost evaluation algorithm forms a key component within the classical 4-stage assignment modelling framework, where it is applicable at the modal split stage – i.e., used to evaluate the choice probability between the public and private transport modes (Szarata, 2014) – and eventually at the trip assignment stage – i.e., used to compute the choice probability of feasible network paths (routes, lines etc.). Our aim is that the observations and conclusions from this study would illustrate the possibility of reproducing the overcrowding effects in these two main modelling algorithms, provide indications for their application on bigger-scale transport models – and together with a summary of the state-of-the-art in public transport congestion modelling, it would point out fields for future improvement works

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