Formulating a New Express Minibus Service Design Problem as a Clustering Problem

Abstract

This paper presents the formulation of a new optimization problem designated as the express minibus problem, which intends to form small groups of clients with compatible boarding/exiting points in time and space for a new type of urban mobility service. This new transport option, as a competitive alternative to the private car, aims to provide almost direct services between dispersed demand poles in places where high-capacity and efficient public transport options are scarce, thus combining the major strengths of both public transport and private vehicles. Conventional public transport systems can present efficient space and energy consumption, whereas private vehicles have high levels of flexibility, are fast, and are always available. The proposed algorithm aims at assessing the potential demand of this new service by developing a clustering algorithm in which the groups of clients formed for each minibus route should present the following characteristics: there is a small number of boarding and exiting points, where in each point there is only boarding or alighting; boarding points should be close to each other, as well as the exiting points; there must be a reasonable distance between the last boarding point and the first exiting point; the average load factor must be high; and for all clients the overall detour time relative to the direct service should be small. This paper presents the rationale and structure of the clustering algorithm, followed by an application for the Lisbon metropolitan area during the morning peak, which could be adapted to the afternoon peak with some slight modifications.

Real-world meeting points for shared demand-responsive transportation systems

“…The second approach used spatio-temporal constraints to cluster the requests (Cullen, Jarvis, and Ratliff, 1981;Gidofalvi et al, 2008;Ma, Zheng, and Wolfson, 2013;Martínez, Viegas, and Eiró, 2014;Morris et al, 2016). In the routing optimization phase, each cluster is treated as a single trip/request.…”

Commuting by Customized Bus: A Comparative Analysis with Private Car and Conventional Public Transport in Two Cities

“…CB service is more comfortable, convenient, and reliable than conventional PT service and more efficient, cost-effective, and environmentally-friendly than PC. Therefore, CB serves as a good alternative for reducing urban traffic congestion, improving traffic safety, and alleviating energy consumption and greenhouse gas emission problems (Eiró et al 2011;Martínez et al 2014;Liu and Ceder 2015).…”

“…The share of driving alone continues to grow for total commuting, whereas the share for carpooling has declined continuously since 1980 in the U.S. (AASHTO 2015). In recent years, new ridesharing programs that incorporate Internet, smartphone apps, and social networking have been developed for better online matching between commuters and service providers by employing information and communication technologies (Eiró et al 2011;Chan and Shaheen 2012;Martínez et al 2014;Liu and Ceder 2015). This new kind of travel mode is viewed as a good alternative to PC and a complementary mobility option that supports traditional PT systems.…”

“…It has been launched and implemented successfully in many cities around the world, such as Beijing, Lisbon, and San Francisco (Shaheen 2001;Eiró et al 2011;Martínez et al 2014;Liu and Ceder 2015), and has great potential for meeting the ever-increasing, diversified commuting mobility needs of large populations and helping to improve the commuting experience.…”

A Model for the Stop Planning and Timetables of Customized Buses

“…Shaheen et al reviewed the development of CBs from the concept of "car sharing" and summarized the advantages of CBs [6], but CB networks and timetable modeling was not examined. Eiro et al [7], Martinez et al [8], and Lopes et al [9] proposed methods based on clustering analysis and a multi-agent model to solve the network planning and timetable problems of a CB in Lisbon, Portugal. However, the dynamic and real-time of passenger demand were not considered in these articles.…”