A Cell Automation Traffic Flow Model for Mixed Traffic

Chen, Guangjiao; Meng, Fanbin; Fu, Guolong; Deng, Mingyang; Li, Ling

doi:10.1016/j.sbspro.2013.08.160

Cited by 10 publications

(4 citation statements)

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“…The parameters and driver behaviors are described differently depending on the interacting vehicle classes (SHIOMI et al, 2012). Space discretization methods are also introduced to accommodate lateral movement within a lane and the variation 2 in vehicle size (Chen et al, 2013;Mathew et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

Modeling and analysis of mixed flow of cars and powered two wheelers

Gashaw

Goatin

Härri

2018

Transportation Research Part C: Emerging Technologies

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In modern cities, a rapid increase of motorcycles and other types of Powered Two-Wheelers (PTWs) is observed as an answer to long commuting in traffic jams and complex urban navigation. Such increasing penetration rate of PTWs creates mixed traffic flow conditions with unique characteristics that are not well understood at present. Our objective is to develop an analytical traffic flow model that reflects the mutual impacts of PTWs and Cars. Unlike cars, PTWs filter between cars, have unique dynamics, and do not respect lane discipline, therefore requiring a different modeling approach than traditional "Passenger Car Equivalent" or "Follow the Leader". Instead, this work follows an approach that models the flow of PTWs similarly to a fluid in a porous medium, where PTWs "percolate" between cars depending on the gap between them. Our contributions are as follows: (I) a characterization of the distribution of the spacing between vehicles by the densities of PTWs and cars; (II) a definition of the equilibrium speed of each class as a function of the densities of PTWs and cars; (III) a mathematical analysis of the model's properties (IV) an impact analysis of the gradual penetration of PTWs on cars and on heterogeneous traffic flow characteristics.

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Section: Introductionmentioning

confidence: 99%

Modeling and analysis of mixed flow of cars and powered two wheelers

Gashaw

Goatin

Härri

2018

Transportation Research Part C: Emerging Technologies

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“…Recently, cellular-automata-based driving behavior models [18][19][20] have been studied in depth. Hu et al [19] used a typical KKW (Kerner-Klenov-Wolf) cellular-automata (CA) model to investigate the formation mechanism of the illegal lane-changing behavior of nonmotorized vehicles.…”

Section: Introductionmentioning

confidence: 99%

“…Hu et al [19] used a typical KKW (Kerner-Klenov-Wolf) cellular-automata (CA) model to investigate the formation mechanism of the illegal lane-changing behavior of nonmotorized vehicles. Chen et al [20] proposed a cellular-automata-based traffic model to describe mixed traffic.…”

Section: Introductionmentioning

confidence: 99%

“…focused on the capacity of various intersections under mixed traffic conditions. As mentioned above, Hu et al [19] and Chen et al [20] also studied the mixed traffic modeling problem. Moreover, Marisamynathan and Vedagiri [24] developed a pedestrian delay model for crosswalks at signalized intersections under mixed traffic conditions, and they verified the validity of the proposed model using field data from India.…”

Section: Introductionmentioning

confidence: 99%

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Modeling Left-Turn Driving Behavior at Signalized Intersections with Mixed Traffic Conditions

et al. 2016

Mathematical Problems in Engineering

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In many developing countries, mixed traffic is the most common type of urban transportation; traffic of this type faces many major problems in traffic engineering, such as conflicts, inefficiency, and security issues. This paper focuses on the traffic engineering concerns on the driving behavior of left-turning vehicles caused by different degrees of pedestrian violations. The traffic characteristics of left-turning vehicles and pedestrians in the affected region at a signalized intersection were analyzed and a cellular-automata-based “following-conflict” driving behavior model that mainly addresses four basic behavior modes was proposed to study the conflict and behavior mechanisms of left-turning vehicles by mathematic methodologies. Four basic driving behavior modes were reproduced in computer simulations, and a logit model of the behavior mode choice was also developed to analyze the relative share of each behavior mode. Finally, the microscopic characteristics of driving behaviors and the macroscopic parameters of traffic flow in the affected region were all determined. These data are important reference for geometry and capacity design for signalized intersections. The simulation results show that the proposed models are valid and can be used to represent the behavior of left-turning vehicles in the case of conflicts with illegally crossing pedestrians. These results will have potential applications on improving traffic safety and traffic capacity at signalized intersections with mixed traffic conditions.

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