Abstract
To alleviate traffic congestion and traffic-related environmental pollution caused by the increasing numbers of private cars, public transport (PT) is highly recommended to travelers. However, there is an obvious contradiction between the diversification of travel demands and simplification of PT service. Customized bus (CB), as an innovative supplementary mode of PT service, aims to provide demand-responsive and direct transit service to travelers with similar travel demands. But how to obtain accurate travel demands? It is passive and limited to conducting online surveys, additionally inefficient and costly to investigate all the origin-destinations (ODs) aimlessly. This paper proposes a methodological framework of extracting potential CB routes from bus smart card data to provide references for CB planners to conduct purposeful and effective investigations. The framework consists of three processes: trip reconstruction, OD area division and CB route extraction. In the OD area division process, a novel two-step division model is built to divide bus stops into different areas. In the CB route extraction process, two spatial-temporal clustering procedures and one length constraint are implemented to cluster similar trips together. An improved density-based spatial clustering of application with noise (DBSCAN) algorithm is used to complete these procedures. In addition, a case study in Beijing is conducted to demonstrate the effectiveness of the proposed methodological framework and the resulting analysis provides useful references to CB planners in Beijing.
Highlights
With the rapid economic development, hyper-motorization and expanding urban areas have contributed to various traffic-related problems, including traffic congestion, degraded levels of transit, traffic fatalities and injuries, and serious environmental pollution
A whole methodological framework, containing trip reconstruction, OD area division, and customized bus (CB) route extraction processes, was presented to achieve this goal based on bus smart card data
In the OD area division process, a two-step division model was built in view of the uneven distribution of bus stops, which was characterized by the concept of “stop isolation” proposed in this paper
Summary
With the rapid economic development, hyper-motorization and expanding urban areas have contributed to various traffic-related problems, including traffic congestion, degraded levels of transit, traffic fatalities and injuries, and serious environmental pollution. To effectively mitigate such adverse effects, an efficient, reliable, and reasonable-priced public transport (PT) system is urgently needed [1,2]. A new innovative mode of public transport services, called customized bus (CB), has been launched and implemented successfully [3]. The CB operator aggregates similar travel demands and publishes candidate bus routes for users to reserve seats, so CB is a demand-responsive transit system. Users participate in various planning activities and have a great
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