EVALUATION OF SYSTEM RELIABILITY FOR A FREEWAY SYSTEM WITH STOCHASTIC SPEED

Authors

  • Yi-Kuei Lin Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
  • Cheng-Fu Huang Department of Business Administration, Feng Chia University, Taichung 40724, Taiwan
  • Jsen-Shung Lin Department of Information Management, Central Police University, Taoyuan 33304, Taiwan
  • Shin-Ying Li Department of Industrial Management, National Taiwan University of Science and Technology, Taipei 10607, Taiwan

DOI:

https://doi.org/10.23055/ijietap.2019.26.1.3595

Keywords:

system reliability, stochastic-flow freeway network (SFFN), stochastic speed, traffic flow, system time

Abstract

The purpose of this study is to apply network analysis to evaluate the service performance of a freeway system, in which the speed on each section is stochastic owing to user behavior, accidents, tunnels, road gradient, and road repairs. A stochastic-flow freeway network (SFFN) is constructed to model the freeway system with stochastic speed. System reliability is defined as the probability of a certain number of vehicles in a freeway system completing their journey smoothly within a restricted time. From the quality management viewpoint, this can serve as an important performance indictor in the planning and management of freeway system traffic flow. Two SFFN models were built to describe the relationships among traffic flow, system time and stochastic speed. After obtaining the probability distribution of speed by collecting historical data, two algorithms with respect to different models were proposed to generate all minimal speed vectors (MSVs). The system reliability can be subsequently computed in terms of MSVs. The Taiwan freeway system was considered as a case study to demonstrate the effectiveness of the proposed models and algorithms.

Published

2019-03-23

How to Cite

Lin, Y.-K., Huang, C.-F., Lin, J.-S., & Li, S.-Y. (2019). EVALUATION OF SYSTEM RELIABILITY FOR A FREEWAY SYSTEM WITH STOCHASTIC SPEED. International Journal of Industrial Engineering: Theory, Applications and Practice, 26(1). https://doi.org/10.23055/ijietap.2019.26.1.3595

Issue

Section

2016 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling