Modelling growth principles of metropolitan public transport networks

Abstract

The development of metropolitan public transport networks often involves choosing between investing in extending radial lines or constructing ring connections. While the former enlarges network coverage the latter enhances network connectivity and reduces the need to perform detours. Moreover, investments might be better directed at increasing the capacity of already existing infrastructure. In this study we address the following question: how do transport networks in metropolitan areas evolve over time and how can we effectively model this growth as function of demand and cost function? The goal of this study is to determine the fundamental relations between population distribution, modal costs on the prevailing network structure and its evolution. The approach taken in this study offers a theoretical contribution to the field of transport network growth by combining principles from several research streams: transport geography, economics of network growth and network science. We propose an iterative investment model network analysis framework. The results of the network growth experiments manifest an overall trend in network growth with an early phase of expansion of the network, followed by a period of intensification manifested in capacity increments and finally adding some links that contribute to its densification. Furthermore, our findings suggest that bus networks include more ringradial connections than Light Rail Train and Metro networks which are more concentrated on radial connections.

Analyse diachronique de la croissance du réseau ferroviaire français entre 1860 et 1930 : entre expansion connexionniste et sélection hiérarchique ?

“…Plus récemment, Ducruet et Beauguitte (2014) ont listé un nombre important de travaux dont certains décrivent l'évolution d'un réseau de transport (Bretagnolle, 2009 ;Dancoisne, 1984). Ces travaux de référence introduisent des indicateurs plus géographiques, tels que l'éloignement moyen du graphe et la distance moyenne entre tous les sommets du graphe, alors même que les premières études de réseau entreprises par les physiciens ou les sociologues ignoraient toute notion de distance.…”

“…Nous identifions deux pistes encore peu explorées : peu d'essais historiques quantifiés existent pour démontrer l'évolution hiérarchisée d'un réseau de transport, en raison essentiellement des difficultés à mobiliser des données suffisamment riches et précises (Delaplace, 2014). Par ailleurs, la « vitesse différenciée » (Ollivro, 2000) a encore peu été intégrée dans l'analyse de la croissance d'un réseau de transport et dans son rapport avec le territoire (Bretagnolle, 2009 ;Kasraian et alii, 2016). Elle constitue pourtant une nouvelle métrique topologique des relations entre les lieux et bouleverse les configurations existantes : « c'est le temps de parcours qui compte et non la distance » (Riboud, 1981).…”

RETRACTED CHAPTER: Management System for Optimizing Public Transport Networks: GPS Record

“…It is necessary to place monitoring nodes at different points of the transportation unit. These points will communicate wirelessly via a Bluetooth Mesh network [ 2 ]. The information will be concentrated in the main node of the vehicle which will communicate the monitored variables with the nearby nodes using the Thread network and, in case the vehicle has a LTE modem, the information will also be sent by this means to the information system (Fig.…”

“… As cities continue to grow in size and population, the design of public transport networks becomes complicated, given the wide diversity in the origins and destinations of users [ 1 ], as well as the saturation of vehicle infrastructure in large cities despite their attempts to adapt it according to population distribution. This indicates that, in order to reduce users’ travel time, it is necessary to implement alternative road solutions to the use of cars, increasing investment in public transportation [ 2 , 3 ] by conducting a comprehensive analysis of the state of transportation. This situation has made appear the solutions and development oriented to transportation based on Internet of Things (IoT) which allows, in a first stage, monitoring of public transport systems, in order to optimize the deployment of transport units and thus reduce the time of transfer of users through the cities [ 4 ].…”

Modeling the Public Transport Networks: A Study of Their Efficiency

“…Reference [27] developed an area-based model of highway growth. Specifically, a binary logit model in order to estimate the new route growth probability of divided highways and secondary highways using high-quality geographic information system (GIS) data of land-use, population distribution, and highway network for the Twin Cities Metropolitan Area from 1958 to 1990 was obtained in [28]. A growth model that iteratively invested in constructing new links or incrementing the capacity of those existing was implemented.…”