Mobile phone GPS data in urban customized bus: dynamic line design and emission reduction potentials analysis

Abstract Customized Bus is a new mode of Internet-supported public transportation. It is regarded as one of the major strategies to reduce the usage of private cars and mitigate greenhouse gas emissions from road traffic. For a customized bus system, a dynamic bus line planning system based on the demand can largely improve the performance and promote the public acceptance of customized bus service. This paper introduces a method to generate planning suggestions for bus lines and stops based on massive demand data. A link network is generated from the input to represent the sharing route of the demand. With community detection, the link network is segmented into communities with similar travel routes. By examining the core-peripheral structure and matching the core part of communities with the road network, the customized bus lines are generated. Boarding and alighting hotspots are identified as the suggestion for customized bus stops. The methodology is tested by using mobile phone data in Tokyo. With the input of one-day sample, the algorithm can generate the result in approximately 1 minute and extract 29 bus lines. According to the shape and spatial location of the bus lines, three types of bus lines serving different travel patterns are classified: radiation type lines, ring-type lines, and suburban lines. Analyzing the emission reduction potential of the extracted bus lines manifestes that bus line planning of the proposed method has the potential to relieve emission pressure on urban expressways and to reduce approximately 13% of road traffic emission.