Modelling public transport on-board congestion: comparing schedule-based and agent-based assignment approaches and their implications
Authored by Oded Cats, Maximilian Hartl
Date Published: 2016
DOI: 10.1002/atr.1398
Sponsors:
European Union
Department of Transport Science
Platforms:
VISUM
Model Documentation:
Other Narrative
Mathematical description
Model Code URLs:
Model code not found
Abstract
Transit systems are subject to congestion that influences system
performance and level of service. The evaluation of measures to relieve
congestion requires models that can capture their network effects and
passengers' adaptation. In particular, on-board congestion leads to an
increase of crowding discomfort and denied boarding and a decrease in
service reliability. This study performs a systematic comparison of
alternative approaches to modelling on-board congestion in transit
networks. In particular, the congestion-related functionalities of a
schedule-based model and an agent-based transit assignment model are
investigated, by comparing VISUM and BusMezzo, respectively. The
theoretical background, modelling principles and implementation details
of the alternative models are examined and demonstrated by testing
various operational scenarios for an example network. The results
suggest that differences in modelling passenger arrival process, choice-set generation and route choice model yield systematically
different passenger loads. The schedule-based model is insensitive to a
uniform increase in demand or decrease in capacity when caused by either
vehicle capacity or service frequency reduction. In contrast, nominal
travel times increase in the agent-based model as demand increases or
capacity decreases. The marginal increase in travel time increases as
the network becomes more saturated. Whilst none of the existing models
capture the full range of congestion effects and related behavioural
responses, existing models can support different planning decisions.
Copyright (c) 2016 John Wiley \& Sons, Ltd.
Tags
Simulation
networks
Capacity constraints
systems
Strategies
Train
Transit assignment
Route-choice
User
equilibrium