Lane-Changing Trajectory Optimization to Minimize Traffic Flow Disturbance in a Connected Automated Driving Environment

2019 ◽  
Author(s):  
Gihyeob An ◽  
Alireza Talebpour
Keyword(s):  
Traffic Flow ◽  
Trajectory Optimization ◽  
Automated Driving ◽  
Flow Disturbance ◽  
Lane Changing

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.

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 A Division Method of Determining the Early-Warning Zone on an Expressway for Automated Vehicles

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Jiawen Wang ◽  
Shaobo Li ◽  
Yining Lu ◽  
Lubang Wang
Keyword(s):  
Cellular Automaton ◽  
Early Warning ◽  
Cellular Automaton Model ◽  
Mixed Traffic ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Traffic Incidents ◽  
Lane Changing ◽  
Automatic Driving ◽  
Urban Expressway

Using a cellular automaton model, this paper studied the evolution mechanism of traffic incidents affecting the capacity of urban expressway under the mixed traffic environment of manual driving and automatic driving. It showed that the length of the automated-driving early-warning zone could affect the capacity of expressway. Specifically, the early-warning zone is divided into an accelerate lane-changing area, a decelerate lane-changing area, and a forced lane-changing area. The areas vary according to the distance between the vehicle and the location of incident. Based on the study, this paper establishes a codirectional two-lane cellular automaton model. The analysis showed that the capacity of the urban expressway varies under different combinations of early-warning area length and division ratio of early-warning zone. In the case of two-lane reduction caused by traffic incidents, the capacity of the expressway is optimized when the length of early-warning zone is between 450 and 600 m, and the ratio of accelerate zone, decelerate zone, and forced zone to the length of early-warning zone is, respectively, 75%, 10%, and 15%. In addition, this study showed that the capacity will rise with the increase in automated vehicles.

scholarly journals Trajectory optimization and state selection for urban automated driving

2018 ◽  
Vol 23 (4) ◽  
pp. 474-480 ◽  
Author(s):  
Keisuke Yoneda ◽  
Toshiki Iida ◽  
TaeHyon Kim ◽  
Ryo Yanase ◽  
Mohammad Aldibaja ◽  
...  
Keyword(s):  
Trajectory Optimization ◽  
Automated Driving ◽  
Selection For ◽  
State Selection

scholarly journals Research on Mandatory Lane-Changing Behavior in Highway Weaving Sections

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
Wei Hao ◽  
Zhaolei Zhang ◽  
Zhibo Gao ◽  
Kefu Yi ◽  
Li Liu ◽  
...  
Keyword(s):  
Traffic Flow ◽  
Traffic Accidents ◽  
Driving Behavior ◽  
Heterogeneous Traffic ◽  
Psychological Characteristics ◽  
Distribution Characteristics ◽  
Mixed Traffic ◽  
Lane Changing ◽  
Headway Distribution ◽  
Analysis Models

As the accident-prone sections and bottlenecks, highway weaving sections will become more complicated when it comes to the mixed-traffic environments with connected and automated vehicles (CAVs) and human-driven vehicles (HVs). In order to make CAVs accurately identify the driving behavior of manual-human vehicles to avoid traffic accidents caused by lane changing, it is necessary to analyze the characteristics of the mandatory lane-changing (MCL) process in the weaving area. An analytical MCL method based on the driver’s psychological characteristics is proposed in this study. Firstly, the driver’s MLC pressure concept was proposed by leading in the distance of the off-ramp. Then, the lane-changing intention was quantified by considering the driver’s MLC pressure and tendentiousness. Finally, based on the lane-changing intention and the headway distribution of the target lane, an MLC positions probability density model was proposed to describe the distribution characteristics of the lane-changing position. Through the NGSIM data verification, the lane-changing analysis models can objectively describe the vehicle lane-changing characteristics in the actual scenarios. Compared with the traditional lane-changing model, the proposed models are more interpretable and in line with the driving intention. The results show significant improvements in the lane-changing safe recognition of CAVs in heterogeneous traffic flow (both CAVs and HVs) in the future.

Necessity of Automated Vehicle Control Customization: Experimental Results during Lane Changing

2018 ◽  
Vol 2672 (22) ◽  
pp. 1-9
Author(s):  
Naohisa Hashimoto ◽  
Simon Thompson ◽  
Shin Kato ◽  
Ali Boyali ◽  
Sadayuki Tsugawa
Keyword(s):  
Vehicle Control ◽  
Experimental Results ◽  
Single Type ◽  
Automated Driving ◽  
Lane Changing ◽  
Automated Vehicle ◽  
Vehicle Trajectories ◽  
Significant Difference ◽  
The Subject ◽  
Automated Vehicle Control

This study investigated the necessity of automated vehicle control customization for individual drivers via a lane-changing experiment involving 35 subjects and an automated minivan. The experiment consisted of two automated driving conditions: one in which the subject was unable to override vehicle controls, the other with the option to override when the subject felt it was necessary. The automated vehicle drove at a speed of 40 km/h along three kinds of planned paths for lane changing, generated by Bezier curves; the distance required for lane changing was varied to obtain the preferred path of each subject. Various data obtained during driving, including vehicle trajectories and steering angles produced by subjects were logged. After automated driving, a questionnaire was administered to each subject. The experimental data showed that there was a statistically significant difference between comfort when the vehicle drove along the subject’s preferred path, and when it drove along other paths. The results of the questionnaire indicated that 46% of the subjects preferred the planned path that most closely resembled their own. In addition, quantitative analysis of driving data found that approximately 69% of the subjects preferred an automated driving control that resembled their own. However, it was also observed that certain subjects were open to multiple types of automated vehicle control. The experimental results indicate that drivers will not necessarily accept a single type of automated vehicle control, therefore customization will be necessary to improve acceptance of automated driving.

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