Markov Chains based route travel time estimation considering link spatio-temporal correlation
作者: Jinjun TangJin HuWei HaoXinqiang ChenYong Qi
作者单位: 1Smart Transport Key Laboratory of Hunan Province, School of Traffic and Transportation Engineering, Central South University, Changsha, 410075, China
2School of Transportation Engineering, Changsha University of Science and Technology, Changsha, 410205, China
3Institute of Logistics Science and Engineering, Shanghai Maritime University, Shanghai 201306, China
4School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China
刊名: Physica A: Statistical Mechanics and its Applications, 2020, Vol.545
来源数据库: Elsevier Journal
DOI: 10.1016/j.physa.2019.123759
关键词: Route travel timeGMM methodMarkov ChainsSpatiotemporal correlation
原始语种摘要: Abstract(#br)Travel time is a critical measure for road network traffic conditions, and travel time estimation provides available information for travellers and traffic management. This paper proposes an improved method based on Markov Chains to estimate route travel time by considering spatio-temporal correlation from related links. The method mainly contains three parts. Firstly, in the light of traffic flow data collected from microwave detectors, Gaussian mixture model (GMM) is applied to cluster travel time data under two consecutive links, and thus capture the underlying traffic states. The transition probability matrix is constructed to estimate variations of traffic states over time. Then, link travel time distributions can be estimated from historical observations. Accordingly,...
全文获取路径: Elsevier  (合作)

  • travel 旅行
  • correlation 对比
  • estimation 估计
  • estimate 估计
  • temporal 现世的
  • route 航线
  • based 基于
  • link 通信信道
  • traffic 话务量
  • historical 历史的