Simulation and analysis of non-recurrent traffic congestion triggered by crashes in road networks using a grid-based approach
Author(s) -
Li Sulan,
Shi Junqing,
Zhang Xiedong,
Zhu Hongwei,
Meng Guolian
Publication year - 2019
Publication title -
advances in mechanical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.318
H-Index - 40
eISSN - 1687-8140
pISSN - 1687-8132
DOI - 10.1177/1687814019884166
Subject(s) - cellular automaton , intersection (aeronautics) , crash , traffic congestion , computer science , traffic congestion reconstruction with kerner's three phase theory , grid , traffic simulation , simulation , transport engineering , duration (music) , microsimulation , engineering , mathematics , artificial intelligence , programming language , geometry , literature , art
The non-recurrent traffic congestion triggered by crashes is one of the most important factors that undermine the traffic efficiency of urban road networks. In this article, an improved cellular automaton model was proposed to simulate the non-recurrent congestion triggered by crashes in grid networks with signalized intersections. Four rules were adopted to represent vehicle movements on road sections and intersections. The network speed is adopted to capture the propagation and dissipation of the non-recurrent congestion. The effect of main influencing factors of crashes on the road network was evaluated through the simulation. Simulation results showed the incident duration and areas affected by the distance between the crash point and the upstream intersection, the number of closed lanes, and the crash duration. In addition, the stop-start wave was observed in the simulation. The realistic findings from the simulations validated the model to have the potential for practical applications in the analysis of the non-recurrent congestion triggered by crashes.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom