Reliability prediction of further transit service based on support vector machine

Author:

Gu Xiaoning1,Chen Chao1,Yang Yunong2,Miao Xingzhi1,Yao Baozhen1ORCID

Affiliation:

1. School of Automotive Engineering, Dalian University of Technology, Dalian, P.R. China

2. Transportation Management College, Dalian Maritime University, Dalian, P.R. China

Abstract

The requirement for transit reliability grows with the increase of pace of life since unstable bus arrivals can raise the anxiety of waiting passengers. This paper proposes a reliability assessment method to evaluate the reliability of each bus stop on the route and the reliability of bus routes. In reliability prediction, the prediction target is locked by rolling horizon to reduce the interference of other information. In addition, a prediction method of the reliability of further transit service using the accurate online support vector machine is proposed. This prediction can provide more accurate and stable data for the arrival of buses and reduce unnecessary waiting of passengers. Finally, the reliability prediction method proposed is tested with the real data of a bus route in Dalian, China. The results show that the accurate online support vector machine with reasonable parameters can predict the reliability of transit service accurately.

Funder

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

SAGE Publications

Subject

Applied Mathematics,Control and Optimization,Instrumentation

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