Impact of lane changing on adjacent vehicles considering multi-vehicle interaction in mixed traffic flow: A velocity estimating model

2021 ◽  
Vol 566 ◽  
pp. 125577
Author(s):  
Yanli Ma ◽  
Zhiliang Lv ◽  
Peng Zhang ◽  
Ching-Yao Chan
Keyword(s):  
Traffic Flow ◽  
Mixed Traffic ◽  
Lane Changing ◽  
Mixed Traffic Flow

TRAFFIC DYNAMICS IN A TWO-LANE MIXED TRAFFIC SYSTEM: EFFECT OF FOUR LANE CHANGING REGULATIONS

2008 ◽  
Vol 19 (11) ◽  
pp. 1705-1715 ◽  
Author(s):  
WEI-WEI ZHANG ◽  
RUI JIANG ◽  
YAO-MING YUAN ◽  
QING-SONG WU
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Flow Characteristics ◽  
Mixed Traffic ◽  
Traffic Dynamics ◽  
System Effect ◽  
Lane Changing ◽  
Traffic System ◽  
Mixed Traffic Flow ◽  
Traffic Flow Characteristics

This paper investigates traffic dynamics of two-lane mixed traffic flow system composed of cars and buses, which are characterized by different lengths and different maximum velocities. Four lane changing regulations are studied, which reveals effect of lane changing ban, symmetric and asymmetric lane changing rules on traffic flow characteristics (flow rate, carry capability, lane changing frequency, and lane usage). We expect that our results could be useful for traffic management.

scholarly journals A Cellular Automata Traffic Flow Model considering Bus Lane Changing Behavior with Scheduling Parameters

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Zun-dong Zhang ◽  
Yan-fang Yang ◽  
Wenjiao Qi ◽  
Abderrahim Chariete ◽  
Xing-xiang Lin
Keyword(s):  
Cellular Automata ◽  
Traffic Flow ◽  
Flow Model ◽  
Flow Density ◽  
Mixed Traffic ◽  
Lane Changing ◽  
Traffic Flow Model ◽  
Mixed Traffic Flow ◽  
Bus Lane ◽  
Bus Stops

According to different driving behavioral characteristics of bus drivers, a cellular automata traffic model considering the bus lane changing behavior with scheduling parameters is proposed in this paper. Traffic bottleneck problems caused by bus stops are simulated in multiple lanes roads with no-bay bus stations. With the mixed traffic flow composed of different bus arrival rate, flow-density graph, density distribution graph, and temporal-spatial graph are presented. Furthermore, the mixed traffic flow characteristics are analyzed. Numerical experiment results show that the proposed model can generate a variety of complicated realistic phenomena in the traffic system with bus stops and provide theoretical basis for better using of traffic flow model.

Multi-Lane Lane-Changing Model under the Influence of Heavy Vehicles

2013 ◽  
Vol 838-841 ◽  
pp. 2117-2120
Author(s):  
Xiao Fang Yang ◽  
Jian Rong Wang ◽  
Xin Zhu Wang
Keyword(s):  
Traffic Flow ◽  
Empirical Data ◽  
Mixed Traffic ◽  
Heavy Vehicles ◽  
Lane Changing ◽  
Mixed Traffic Flow ◽  
Traffic Conditions ◽  
Preceding Vehicle

This paper presents a new lane-changing model of multi-lane mixed traffic flow. The influences of heavy vehicles on lane-changing are analyzed. An improved accumulated speed benefit model is proposed in which drivers generate lane-changing intentions based on accumulated speed benefit of preceding vehicle in target lane over the preceding vehicle in current lane, not just relative to the speed and desired speed of subject vehicle. Drivers may accelerate or decelerate during lane-changing due to different traffic conditions. Simulations show that with the increase in the proportion of heavy vehicles, lane changing frequency first increases and then decreases. The model is validated with empirical data.

A refined and dynamic cellular automaton model for pedestrian–vehicle mixed traffic flow

2016 ◽  
Vol 27 (05) ◽  
pp. 1650053 ◽  
Author(s):  
Mianfang Liu ◽  
Shengwu Xiong
Keyword(s):  
Cellular Automaton ◽  
Traffic Flow ◽  
Model Simulation ◽  
Mixed Traffic ◽  
Forward Movement ◽  
Lane Changing ◽  
Mixed Traffic Flow ◽  
Interactive Behavior ◽  
Proposed Model ◽  
Traffic Conflict

Mixed traffic flow sharing the “same lane” and having no discipline on road is a common phenomenon in the developing countries. For example, motorized vehicles (m-vehicles) and nonmotorized vehicles (nm-vehicles) may share the m-vehicle lane or nm-vehicle lane and pedestrians may share the nm-vehicle lane. Simulating pedestrian-vehicle mixed traffic flow consisting of three kinds of traffic objects: m-vehicles, nm-vehicles and pedestrians, can be a challenge because there are some erratic drivers or pedestrians who fail to follow the lane disciplines. In the paper, we investigate various moving and interactive behavior associated with mixed traffic flow, such as lateral drift including illegal lane-changing and transverse crossing different lanes, overtaking and forward movement, and propose some new moving and interactive rules for pedestrian–vehicle mixed traffic flow based on a refined and dynamic cellular automaton (CA) model. Simulation results indicate that the proposed model can be used to investigate the traffic flow characteristic in a mixed traffic flow system and corresponding complicated traffic problems, such as, the moving characteristics of different traffic objects, interaction phenomenon between different traffic objects, traffic jam, traffic conflict, etc., which are consistent with the actual mixed traffic system. Therefore, the proposed model provides a solid foundation for the management, planning and evacuation of the mixed traffic flow.

Analysis of an extended two-lane lattice hydrodynamic model considering mixed traffic flow and self-stabilization effect

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ting Wang ◽  
Rongjun Cheng ◽  
Hongxia Ge
Keyword(s):  
Numerical Simulation ◽  
Traffic Flow ◽  
Lattice Hydrodynamic Model ◽  
Mixed Traffic ◽  
Lane Changing ◽  
Content Type ◽  
Mixed Traffic Flow ◽  
Stabilization Effect ◽  
Self Stabilization ◽  
The Stability

Purpose The purpose of this paper is to explore the impact of the mixed traffic flow, self-stabilization effect and the lane changing behavior on traffic flow stability. Design/methodology/approach An extended two-lane lattice hydrodynamic model considering mixed traffic flow and self-stabilization effect is proposed in this paper. Through linear analysis, the stability conditions of the extended model are derived. Then, the nonlinear analysis of the model is carried out by using the perturbation theory, the modified Kortweg–de Vries equation of the density of the blocking area is derived and the kink–antikink solution about the density is obtained. Furthermore, the results of theoretical analysis are verified by numerical simulation. Findings The results of numerical simulation show that the increase of the proportion of vehicles with larger maximum speed or larger safe headway in the mix flow are not conducive to the stability of traffic flow, while the self-stabilization effect and lane changing behavior is positive to the alleviation of traffic congestion. Research limitations/implications This paper does not take into account the factors such as curve and slope in the actual road environment, which will have more or less influence on the stability of traffic flow, so there is still a certain gap with the real traffic environment. Originality/value The existing two-lane lattice hydrodynamic models are rarely discussed in the case of mixed traffic flow. The improved model proposed in this paper can better reflect the actual traffic, which can also provide a theoretical reference for the actual traffic governance.

A Cellular Automata Asymmetric Lane-Changing Model with Mixed Traffic

2014 ◽  
Vol 1030-1032 ◽  
pp. 1937-1940
Author(s):  
Jian Hui Zhu
Keyword(s):  
Computer Simulation ◽  
Cellular Automata ◽  
Traffic Flow ◽  
Mixed Traffic ◽  
Lane Changing ◽  
Mixed Traffic Flow ◽  
Road Characteristics

Considered the influence of buses on cars’ change lanes and lane-changing of buses, this paper built an asymmetric cellular automata lane changing model under mixed traffic flow based on symmetric two-lane cellular automata lane-changing model and studied driveway occupancy and road characteristics with related parameters. Computer simulation showed that bus ratio has significant impact on lane-changing probability of vehicles.

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