In the context of urban traffic increasing, the study of driving behaviour in the vicinity of signalised intersection is emerging. Driving behaviour on the signalised road is different from the one on the highway due to the influence of signal lights. In this study, the authors analyse the trajectory data of Lankershim Boulevard from the next generation simulation (NGSIM) database. The car‐following data are filtered to exclude the influences of lane changing. They analyse the driving data from both micro‐ and macro‐perspectives. The quantitative relationship between acceleration and other factors, as well as the distribution of headway, are analysed. It is found that the statistic features of headway are in a discrepancy between different signal data. A simulation testbed is constructed, and two calibrated traditional car‐following models are utilised to reproduce the driving behaviour at signalised intersections. The simulation results illustrate that the traditional models cannot be used to simulate traffic flow on the signalised road, i.e. they cannot describe the difference of headway under different signal states. Based on the data analyses, the authors propose a new car‐following model with the consideration of signal status. The simulation results of the new model are in better agreement with the actual data.
Some features of car‐following behaviour in the vicinity of signalised intersection and how to model them
IET Intelligent Transport Systems ; 13 , 11 ; 1686-1693
2019-11-01
8 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
macro‐perspectives , signalised intersection , traditional models , traditional car , actual data , signalised road , signal data , signal states , simulation testbed , car‐following behaviour , generation simulation database , driving data , road traffic , signal lights , urban traffic increasing , car‐following data , driving behaviour , trajectory data , statistic features , simulation results , data analyses
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