A space-time visualization analysis method for taxi operation in Beijing. (December 2015)

• Record Type: Journal Article
• Authors: Jianqin, Zhang; Peiyuan, Qiu; Yingchao, Duan; Mingyi, Du; Feng, Lu
• Is Part Of: Journal of visual languages & computing. Volume 31:Part A(2016)
• Page Start: 1
• Page End: 8
• Publication Date: 2015-12
• Subjects: Space-time visualization analysis -- Data mining -- GIS for transportation; Visual programming languages (Computer science) -- Periodicals; Visual programming (Computer science) -- Periodicals; Programming languages (Electronic computers) -- Semantics -- Periodicals; Langages de programmation visuelle -- Périodiques; Programmation visuelle -- Périodiques; Langages de programmation -- Sémantique -- Périodiques; Programming languages (Electronic computers) -- Semantics; Visual programming (Computer science); Visual programming languages (Computer science); Periodicals; Electronic journals; 005
• DOI: 10.1016/j.jvlc.2015.09.002
• Languages: English
• ISSNs: 1045-926X

Abstract

Abstract: Traffic phenomena are associated with a complex dynamic behavior of spatiotemporal traffic patterns. It is possible to understand the features of real traffic by a spatiotemporal analysis approach for real measured traffic data. In this paper, a space-time visualization analysis method is designed and carried out for taxi spatiotemporal dataset from Beijing floating car data acquisition system and Beijing GIS data. Through this method, large-amount taxi GPS data is processed and the spatial–temporal trajectory is analyzed. And then taxi daily operation time, operating range and residence location of individual driver, vehicle operation and rest periods and other indicators are calculated, which are important characteristic parameters of Beijing Taxi Operations. In sum, continuous, comprehensive, and dynamic analysis information for monitoring taxi operation status can be acquired through the method. These information can provide the decision basis for city taxi operation management, and help to improve the city taxi operation management level. Highlights: A spatial visualization analysis method for taxi is designed and carried out. The residence location of driver, vehicle operation and rest periods are counted. The results show that most drivers lack enough time to relax. The distribution of taxi driver׳s working location are counted and summed. The result show that many taxi drivers have a operation psychological space.