A dynamic lane-changing trajectory planning model for automated vehicles

2018 ◽  
Vol 95 ◽  
pp. 228-247 ◽  
Author(s):  
Da Yang ◽  
Shiyu Zheng ◽  
Cheng Wen ◽  
Peter J. Jin ◽  
Bin Ran
Keyword(s):  
Trajectory Planning ◽  
Planning Model ◽  
Automated Vehicles ◽  
Lane Changing

scholarly journals Accelerated Lane-Changing Trajectory Planning of Automated Vehicles with Vehicle-to-Vehicle Collaboration

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Haijian Bai ◽  
Jianfeng Shen ◽  
Liyang Wei ◽  
Zhongxiang Feng
Keyword(s):  
Boundary Conditions ◽  
Simulation Model ◽  
Trajectory Planning ◽  
Polynomial Method ◽  
Vehicle Model ◽  
Automated Vehicles ◽  
Lane Changing ◽  
Cooperative Strategies ◽  
Vehicle To Vehicle ◽  
Changing Process

Considering the complexity of lane changing using automated vehicles and the frequency of turning lanes in city settings, this paper aims to generate an accelerated lane-changing trajectory using vehicle-to-vehicle collaboration (V2VC). Based on the characteristics of accelerated lane changing, we used a polynomial method and cooperative strategies for trajectory planning to establish a lane-changing model under different degrees of collaboration with the following vehicle in the target lane by considering vehicle kinematics and comfort requirements. Furthermore, considering the shortcomings of the traditional elliptical vehicle and round vehicle models, we established a rectangular vehicle model with collision boundary conditions by analysing the relationships between the possible collision points and the outline of the vehicle. Then, we established a simulation model for the accelerated lane-changing process in different environments under different degrees of collaboration. The results show that, by using V2VC, we can achieve safe accelerated lane-changing trajectories and simultaneously satisfy the requirements of vehicle kinematics and comfort control.

scholarly journals Lane‐changing trajectory planning method for automated vehicles under various road line‐types

2020 ◽  
Vol 2 (1) ◽  
pp. 14-23 ◽  
Author(s):  
Ying Wang ◽  
Chong Wei ◽  
Erjian Liu ◽  
Shurong Li
Keyword(s):  
Trajectory Planning ◽  
Planning Method ◽  
Automated Vehicles ◽  
Lane Changing

A dynamic trajectory planning method for lane-changing maneuver of connected and automated vehicles

2021 ◽  
pp. 095440702098271
Author(s):  
Xiao Liu ◽  
Jun Liang ◽  
Junwei Fu
Keyword(s):  
Trajectory Planning ◽  
Planning Method ◽  
Reference Trajectory ◽  
Automated Vehicles ◽  
Lane Changing ◽  
Planning Strategy ◽  
V2v Communication ◽  
Starting Point ◽  
Trajectory Tracking Controller ◽  
Dynamic Trajectory

This paper describes a dynamic trajectory planning method for lane-changing maneuver of connected and automated vehicles (CAVs). The proposed dynamic lane-changing trajectory planning (DLTP) model adopts vehicle-to-vehicle (V2V) communication to generate an automated lane-changing maneuver with avoiding potential collisions and rollovers during the lane-changing process. The novelty of this method is that the DLTP model combines a detailed velocity planning strategy and considers more complete driving environment information. Besides, a lane-changing safety monitoring algorithm and a lane-changing starting-point determination algorithm are presented to guarantee the lane-changing safety, efficiency and stability of automated vehicles. Moreover, a trajectory-tracking controller based on model predictive control (MPC) is introduced to make the automated vehicle travel along the reference trajectory. The field traffic data from NGSIM are selected as the target dataset to simulate a real-world lane-changing driving environment. The simulations are performed in CarSim-Simulink platform and the experimental results show that the proposed method is effective for lane-changing maneuver.

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.

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