Modeling and Simulation of Nonmotorized Vehicles’ Dispersion at Mixed Flow Intersections

Interactions between motorized and nonmotorized vehicles have drawn considerable attention from researchers. They are commonly seen at mixed flow intersections where nonmotorized vehicles, without the restriction of lane markers or physical barriers, may disperse into adjacent lanes and thus lead to...

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Main Authors: Qiyuan Liu, Jian Sun, Ye Tian, Ying Ni, Shinan Yu
Format: Article
Language:English
Published: Wiley 2019-01-01
Series:Journal of Advanced Transportation
Online Access:http://dx.doi.org/10.1155/2019/9127062
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author Qiyuan Liu
Jian Sun
Ye Tian
Ying Ni
Shinan Yu
author_facet Qiyuan Liu
Jian Sun
Ye Tian
Ying Ni
Shinan Yu
author_sort Qiyuan Liu
collection DOAJ
description Interactions between motorized and nonmotorized vehicles have drawn considerable attention from researchers. They are commonly seen at mixed flow intersections where nonmotorized vehicles, without the restriction of lane markers or physical barriers, may disperse into adjacent lanes and thus lead to complex interactions with motorized vehicles. Such a dispersion phenomenon between heterogeneous participants (e-bikes and bicycles as nonmotorized vehicles versus motorized vehicles) is difficult to model. In this paper, we were inspired by the dispersion of charged particles in an electric field and modeled the dispersion phenomenon of go-straight, nonmotorized vehicles at mixed flow intersections accordingly, as it was discovered in this research that these two dispersion phenomena share three underlying commonalities with each other. A novel particle dispersion model (PDM) based on a particle’s movement in an electric field is proposed. The model is calibrated and validated using 1,490 high-definition sets of trajectory data for go-straight, nonmotorized vehicles during 43 cycles at two typical mixed flow intersections. The PDM is compared with the social force model (SFM) on their dispersion characteristics that are used to describe the nonmotorized bicycles’ behavior. The results show that the PDM performs better than the SFM with regard to depicting the dispersion characteristic indices of the nonmotorized vehicles, such as the travel time, the dispersion intensity of heterogeneous nonmotorized vehicles, the sectional dispersion degree, and other dispersion characteristics.
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spelling doaj-art-75be271778d74fb7bc5231ad0907818e2025-02-03T06:11:32ZengWileyJournal of Advanced Transportation0197-67292042-31952019-01-01201910.1155/2019/91270629127062Modeling and Simulation of Nonmotorized Vehicles’ Dispersion at Mixed Flow IntersectionsQiyuan Liu0Jian Sun1Ye Tian2Ying Ni3Shinan Yu4Key Laboratory of Road and Traffic Engineering in the Ministry of Education, Tongji University, Shanghai 201804, ChinaKey Laboratory of Road and Traffic Engineering in the Ministry of Education, Tongji University, Shanghai 201804, ChinaKey Laboratory of Road and Traffic Engineering in the Ministry of Education, Tongji University, Shanghai 201804, ChinaKey Laboratory of Road and Traffic Engineering in the Ministry of Education, Tongji University, Shanghai 201804, ChinaKey Laboratory of Road and Traffic Engineering in the Ministry of Education, Tongji University, Shanghai 201804, ChinaInteractions between motorized and nonmotorized vehicles have drawn considerable attention from researchers. They are commonly seen at mixed flow intersections where nonmotorized vehicles, without the restriction of lane markers or physical barriers, may disperse into adjacent lanes and thus lead to complex interactions with motorized vehicles. Such a dispersion phenomenon between heterogeneous participants (e-bikes and bicycles as nonmotorized vehicles versus motorized vehicles) is difficult to model. In this paper, we were inspired by the dispersion of charged particles in an electric field and modeled the dispersion phenomenon of go-straight, nonmotorized vehicles at mixed flow intersections accordingly, as it was discovered in this research that these two dispersion phenomena share three underlying commonalities with each other. A novel particle dispersion model (PDM) based on a particle’s movement in an electric field is proposed. The model is calibrated and validated using 1,490 high-definition sets of trajectory data for go-straight, nonmotorized vehicles during 43 cycles at two typical mixed flow intersections. The PDM is compared with the social force model (SFM) on their dispersion characteristics that are used to describe the nonmotorized bicycles’ behavior. The results show that the PDM performs better than the SFM with regard to depicting the dispersion characteristic indices of the nonmotorized vehicles, such as the travel time, the dispersion intensity of heterogeneous nonmotorized vehicles, the sectional dispersion degree, and other dispersion characteristics.http://dx.doi.org/10.1155/2019/9127062
spellingShingle Qiyuan Liu
Jian Sun
Ye Tian
Ying Ni
Shinan Yu
Modeling and Simulation of Nonmotorized Vehicles’ Dispersion at Mixed Flow Intersections
Journal of Advanced Transportation
title Modeling and Simulation of Nonmotorized Vehicles’ Dispersion at Mixed Flow Intersections
title_full Modeling and Simulation of Nonmotorized Vehicles’ Dispersion at Mixed Flow Intersections
title_fullStr Modeling and Simulation of Nonmotorized Vehicles’ Dispersion at Mixed Flow Intersections
title_full_unstemmed Modeling and Simulation of Nonmotorized Vehicles’ Dispersion at Mixed Flow Intersections
title_short Modeling and Simulation of Nonmotorized Vehicles’ Dispersion at Mixed Flow Intersections
title_sort modeling and simulation of nonmotorized vehicles dispersion at mixed flow intersections
url http://dx.doi.org/10.1155/2019/9127062
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AT yetian modelingandsimulationofnonmotorizedvehiclesdispersionatmixedflowintersections
AT yingni modelingandsimulationofnonmotorizedvehiclesdispersionatmixedflowintersections
AT shinanyu modelingandsimulationofnonmotorizedvehiclesdispersionatmixedflowintersections