The Release Characteristics and Selection Model for Vehicle Lane Changing of the Quadruple Left-Turn Traffic Flow at Signalized Intersection

2018 ◽  
Author(s):  
Yan Jiang
Keyword(s):  
Traffic Flow ◽  
Selection Model ◽  
Signalized Intersection ◽  
Lane Changing ◽  
Left Turn

Research on traffic flow characteristics at signal intersection

2017 ◽  
Vol 31 (26) ◽  
pp. 1750238 ◽  
Author(s):  
Jun-Wei Zeng ◽  
Sen-Bin Yu ◽  
Yong-Sheng Qian ◽  
Xu-Ting Wei ◽  
Xiao Feng ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Flow Characteristics ◽  
Driving Behavior ◽  
Signalized Intersection ◽  
Flow Density ◽  
Two Dimensional ◽  
Cellular Automata Model ◽  
Left Turn ◽  
Traffic Flow Characteristics ◽  
Research Objects

Based on the cautious driving behavior and the principle of the vehicles at left-side having priority to pass in the intersection, a two-dimensional cellular automata model for planar signalized intersection (NS-STCA) is established. The different turning vehicles are regarded as the research objects and the effect of the left-turn probability, signal cycle, vehicle flow density on traffic flow at the intersection is investigated.

Modeling Capacity of Through Movement at Signalized Intersection Affected by Short Left-Turn Bay under Different Signal Settings

2021 ◽  
pp. 036119812110064
Author(s):  
Zihang Wei ◽  
Yunlong Zhang ◽  
Xiaoyu Guo ◽  
Xin Zhang
Keyword(s):  
Cycle Length ◽  
Signalized Intersections ◽  
Signalized Intersection ◽  
Essential Factor ◽  
Highway Capacity ◽  
Left Turn ◽  
Highway Capacity Manual ◽  
Proposed Model ◽  
Vehicle Demand ◽  
The One

Through movement capacity is an essential factor used to reflect intersection performance, especially for signalized intersections, where a large proportion of vehicle demand is making through movements. Generally, left-turn spillback is considered a key contributor to affect through movement capacity, and blockage to the left-turn bay is known to decrease left-turn capacity. Previous studies have focused primarily on estimating the through movement capacity under a lagging protected only left-turn (lagging POLT) signal setting, as a left-turn spillback is more likely to happen under such a condition. However, previous studies contained assumptions (e.g., omit spillback), or were dedicated to one specific signal setting. Therefore, in this study, through movement capacity models based on probabilistic modeling of spillback and blockage scenarios are established under four different signal settings (i.e., leading protected only left-turn [leading POLT], lagging left-turn, protected plus permitted left-turn, and permitted plus protected left-turn). Through microscopic simulations, the proposed models are validated, and compared with existing capacity models and the one in the Highway Capacity Manual (HCM). The results of the comparisons demonstrate that the proposed models achieved significant advantages over all the other models and obtained high accuracies in all signal settings. Each proposed model for a given signal setting maintains consistent accuracy across various left-turn bay lengths. The proposed models of this study have the potential to serve as useful tools, for practicing transportation engineers, when determining the appropriate length of a left-turn bay with the consideration of spillback and blockage, and the adequate cycle length with a given bay length.

ANALYSIS OF THE INFLUENCE OF LANE CHANGING ON TRAFFIC-FLOW DYNAMICS BASED ON THE CELLULAR AUTOMATON MODEL

2011 ◽  
Vol 22 (03) ◽  
pp. 271-281 ◽  
Author(s):  
SHINJI KUKIDA ◽  
JUN TANIMOTO ◽  
AYA HAGISHIMA
Keyword(s):  
Boundary Condition ◽  
Cellular Automaton ◽  
Numerical Simulations ◽  
Traffic Flow ◽  
Flow Dynamics ◽  
Open Boundary ◽  
Open Boundary Condition ◽  
Lane Changing ◽  
Basic Characteristics ◽  
Conventional Models

Many cellular automaton models (CA models) have been applied to analyze traffic flow. When analyzing multilane traffic flow, it is important how we define lane-changing rules. However, conventional models have used simple lane-changing rules that are dependent only on the distance from neighboring vehicles. We propose a new lane-changing rule considering velocity differences with neighboring vehicles; in addition, we embed the rules into a variant of the Nagel–Schreckenberg (NaSch) model, called the S-NFS model, by considering an open boundary condition. Using numerical simulations, we clarify the basic characteristics resulting from different assumptions with respect to lane changing.

scholarly journals The Departure Characteristics of Traffic Flow at the Signalized Intersection

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Zhaowei Qu ◽  
Yan Xing ◽  
Hongyu Hu ◽  
Yuzhou Duan ◽  
Xianmin Song ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Wave Model ◽  
Wave Theory ◽  
Signalized Intersection ◽  
Departure Process ◽  
Dispersion Process ◽  
Spatiotemporal Model ◽  
Quantitative Calculation ◽  
Traffic Wave ◽  
Motion Characteristics

The motion characteristics of the leading vehicle and the following vehicles of the traffic flow at the typical urban intersections are qualitatively analyzed through the kinematical equation and the traffic wave theory. Then, the motion characteristic of the whole traffic flow during the dispersion process is also studied. Based on the spatiotemporal model of kinematics in the departure process and traffic wave model in the dispersion process proposed, the change of the leading vehicle of the departure process and the time of the following vehicles reaching to the stable speed as well as the relationship between the green time and the departure vehicle number at the intersection are acquired. Furthermore, according to the qualitative analysis and the quantitative calculation of the departure traffic flow at the signalized intersection, the dispersion characteristic of traffic flow at the signalized intersection was studied and analyzed, which provides reliable theoretical basis for traffic signal setting at the intersection.

Modeling of cooperative adaptive cruise control vehicle and its effect on traffic flow

2021 ◽  
pp. 2250022
Author(s):  
Jianzhong Chen ◽  
Yang Zhou ◽  
Jing Li ◽  
Huan Liang ◽  
Zekai Lv ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Cooperative Control ◽  
Adaptive Cruise Control ◽  
Cruise Control ◽  
Lane Changing ◽  
Vehicle Communication ◽  
Traffic Efficiency ◽  
Vehicle To Vehicle ◽  
Road Capacity ◽  
Cooperative Adaptive Cruise Control

In this paper, an improved multianticipative cooperative adaptive cruise control (CACC) model is proposed based on fully utilizing multivehicle information obtained by vehicle-to-vehicle communication. More flexible, effective and practical spacing strategy is embedded into the model. We design a new lane-changing rule for CACC vehicles on the freeway. The rule considers that CACC vehicles are more inclined to form a platoon for coordinated control. Furthermore, we investigate the effect of CACC vehicles on two-lane traffic flow. The results demonstrate that introducing CACC vehicles into mixed traffic and forming CACC platoon to cooperative control can improve traffic efficiency and enhance road capacity to a certain extent.

scholarly journals Traffic Characteristics for A Freeway Normal Section at Baghdad City

2018 ◽  
Vol 7 (4.20) ◽  
pp. 283
Author(s):  
Jalal T. S. Al-Obaedi ◽  
Muhanad Al-temimy ◽  
Amal Ali
Keyword(s):  
Traffic Flow ◽  
Research Work ◽  
Distribution Data ◽  
Lane Changing ◽  
Traffic Characteristics ◽  
Traffic Lane ◽  
Video Recordings ◽  
Negative Exponential Distribution ◽  
Headway Distribution ◽  
Negative Exponential

Traffic characteristics at highway sections are usually varying based on many factors including type of highways, geometric design and drivers’ behavior at a given area (country).  This paper focuses on finding the characteristics for traffic on selected normal freeway section at Baghdad city.  Video recordings and speed gun are used to collect data from a basic freeway section within Mohammed Al-Qassim freeway that represents the busiest freeway at the city.  The estimated characteristics include the distribution of traffic among the available lanes, desired speed of traffic, lane-changing frequency, and headway distribution.  For traffic distribution, it is found that traffic concentrates more in off side lane compared with other lanes for moderate to high flow rates.  Regression models have been developed based on the available lane distribution data.  The lane found to be increased with the increasing of traffic flow and the desired speeds found to be normally distributed.  Examining the headway data shows that the shifted negative exponential distribution can be used to represent the headway distribution for low to intermediate traffic flow only.  The findings of this work provides a good database for traffic characteristics for Iraqi highways as little effort has been given in previous research work.  

A Second Order Traffic Flow Model with Lane Changing

2019 ◽  
Vol 81 (3) ◽  
pp. 1429-1445
Author(s):  
Jiah Song ◽  
Smadar Karni
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Second Order ◽  
Lane Changing ◽  
Traffic Flow Model

scholarly journals Deep Reinforcement Learning Based Left-Turn Connected and Automated Vehicle Control at Signalized Intersection in Vehicle-to-Infrastructure Environment

Information ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 77 ◽  
Author(s):  
Juan Chen ◽  
Zhengxuan Xue ◽  
Daiqian Fan
Keyword(s):  
Reinforcement Learning ◽  
Control Method ◽  
Signalized Intersection ◽  
Signal Control ◽  
Left Turn ◽  
Automated Vehicle ◽  
Whole Process ◽  
Policy Gradient ◽  
Experience Replay ◽  
Automated Vehicle Control

In order to solve the problem of vehicle delay caused by stops at signalized intersections, a micro-control method of a left-turning connected and automated vehicle (CAV) based on an improved deep deterministic policy gradient (DDPG) is designed in this paper. In this paper, the micro-control of the whole process of a left-turn vehicle approaching, entering, and leaving a signalized intersection is considered. In addition, in order to solve the problems of low sampling efficiency and overestimation of the critic network of the DDPG algorithm, a positive and negative reward experience replay buffer sampling mechanism and multi-critic network structure are adopted in the DDPG algorithm in this paper. Finally, the effectiveness of the signal control method, six DDPG-based methods (DDPG, PNRERB-1C-DDPG, PNRERB-3C-DDPG, PNRERB-5C-DDPG, PNRERB-5CNG-DDPG, and PNRERB-7C-DDPG), and four DQN-based methods (DQN, Dueling DQN, Double DQN, and Prioritized Replay DQN) are verified under 0.2, 0.5, and 0.7 saturation degrees of left-turning vehicles at a signalized intersection within a VISSIM simulation environment. The results show that the proposed deep reinforcement learning method can get a number of stops benefits ranging from 5% to 94%, stop time benefits ranging from 1% to 99%, and delay benefits ranging from −17% to 93%, respectively compared with the traditional signal control method.

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