Control of Connected and Autonomous Vehicles with Cut-in Movement using Spring Mass Damper System

2018 ◽  
Vol 2672 (20) ◽  
pp. 133-143 ◽  
Author(s):  
Soohyuk Bang ◽  
Soyoung Ahn
Keyword(s):  
Autonomous Vehicles ◽  
Recovery Time ◽  
Control Method ◽  
Control Model ◽  
Lane Change ◽  
Control Parameters ◽  
Traffic Conditions ◽  
Disturbance Propagation ◽  
Simulation Based ◽  
Mass Damper

This paper proposes a theoretical framework to control a platoon of connected and autonomous vehicles (CAVs) in the presence of cut-in movements. The control method is developed based on the spring–mass–damper (SMD) system concept and aims to improve the platoon efficiency and stability after a cut-in movement (e.g., lane change and merging from on-ramp). The method seeks to resolve a disturbance created by a cut-in vehicle by systematically setting two control parameters, spring constant and damping coefficient, of the SMD-based control model based on the prevailing traffic conditions. The control method is evaluated through a simulation based on the changes in speed and spacing, recovery time to reach the desired speed, disturbance propagation, and platoon flow. The simulation result shows that the control method can effectively reduce the disturbance caused by a cut-in movement and improve platoon flow.

Mixed Traffic of Connected and Autonomous Vehicles and Human-Driven Vehicles: Traffic Evolution and Control using Spring-Mass-Damper System

2019 ◽  
Vol 2673 (7) ◽  
pp. 504-515 ◽  
Author(s):  
Soohyuk Bang ◽  
Soyoung Ahn
Keyword(s):  
Autonomous Vehicles ◽  
Control Method ◽  
Feasible Region ◽  
Control Parameters ◽  
Mixed Traffic ◽  
Traffic Dynamics ◽  
Acceleration Rate ◽  
Mass Damper ◽  
Spring Coefficient ◽  
And Control

This paper sheds light on mixed-traffic dynamics considering the differences in driving characteristics, namely acceleration/deceleration rate, desired speed, and response time, between connected and autonomous vehicles (CAVs) and human-driven vehicles (HDVs). In light traffic, these differences were found to induce platoon formations, headed by vehicles with a lower acceleration rate and propensity not to exceed the desired speed (HDV in this study). Platoon formations lead to large inter-platoon spacing that can be utilized to accommodate cut-in vehicles. In a near-capacity condition, however, the differences in driving characteristics can induce voids and undermine traffic throughput when traffic is disturbed by merging vehicles. Based on these findings, a simple CAV control method is proposed based on the spring-mass-damper (SMD) system approach that directly considers the HDV behavior to mitigate disturbance propagation and throughput reduction. The main principle is to adjust the control parameters (lower spring coefficient and higher damping coefficient in the SMD control model) with an aim to control CAVs to absorb the cut-in impact (i.e., spacing shortage) before it reaches the first upstream HDV. A simulation experiment suggests the feasible region of the control parameters, subject to the recovery time, the number of controllable CAVs, and the cut-in impact.

Platooning Strategy for Connected and Autonomous Vehicles: Transition from Light Traffic

2017 ◽  
Vol 2623 (1) ◽  
pp. 73-81 ◽  
Author(s):  
Soohyuk Bang ◽  
Soyoung Ahn
Keyword(s):  
Autonomous Vehicles ◽  
Spring Constant ◽  
Low Flow ◽  
Control Parameters ◽  
Mass Damper ◽  
Acceleration And Deceleration ◽  
Formation And Evolution ◽  
The Given ◽  
Insight Into ◽  
Flow States

This study presents a strategy for platoon formation and evolution of connected and autonomous vehicles (CAVs) in free-flow traffic. The proposed strategy is based on swarm intelligence, which describes bird flocking, fish schooling, and so on, in natural and artificial systems. In this concept, CAVs behave according to some rules to move together as a platoon without collisions. The rules are expressed by a spring–mass–damper system: CAV platoon formation and evolution are controlled by the spring constant and damping coefficient. Valid domains of these control parameters were derived on the basis of physical vehicle properties (e.g., bounded acceleration and deceleration) for realistic control. Furthermore, various relationships—maximum (in which the spring constant was set at its maximum for the given flow), quadratic, and cubic—between the control parameters and traffic flow were examined with simulations to obtain insight into desirable control parameter settings. The results suggest that the most efficient platooning can be achieved by the maximum relationship between the spring constant and flow with critical damping. However, the cubic relationship coupled with overdamping is more desirable in low-flow states to allow more freedom for vehicles to change lanes.

Analysis and Control of Heterogeneous Connected and Autonomous Vehicles using a Spring-Mass-Damper System

2020 ◽  
Vol 2674 (8) ◽  
pp. 309-318
Author(s):  
Sookyuk Bang ◽  
Soyoung Ahn
Keyword(s):  
Equilibrium State ◽  
Autonomous Vehicles ◽  
Control Parameters ◽  
Heavy Vehicles ◽  
Heavy Duty ◽  
Passenger Cars ◽  
Lower Performance ◽  
Mass Damper ◽  
And Control ◽  
Heavy Duty Vehicles

This study analyzes the behavior of heterogeneous connected and autonomous vehicles (CAVs) and proposes the best vehicle sequence for optimal platoon throughput and platoon formation. A spring-mass-damper (SMD) system is adopted for control of CAVs, and the control parameters are formulated in relation to the physical capabilities of vehicles. To gain insight, we consider three types of vehicle: passenger cars, mini-vans, and heavy-duty vehicles. For each type, we investigate the maximum platoon throughput and the clustering time, defined as the time to reach the target equilibrium state. We further investigate different sequences of vehicle types in a platoon to identify the optimal vehicle order that maximizes the throughput and minimizes clustering time. Findings suggest that the highest performance vehicle (in relation to acceleration capability) should be placed as the leader of a platoon and that the number of passenger cars behind heavy vehicles (e.g., semi-trailers) should be minimized in the platoon. In addition, we examine how the proportions of lower performance vehicles affect throughput and clustering times. The result suggests that the higher the proportions, the lower the throughput and the longer the clustering time. The lowest performance vehicle had the greatest effect.

scholarly journals Lane-Change Model and Tracking Control for Autonomous Vehicles on Curved Highway Sections in Rainy Weather

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Tao Peng ◽  
Li-li Su ◽  
Zhi-wei Guan ◽  
Hai-jing Hou ◽  
Jun-kai Li ◽  
...  
Keyword(s):  
Autonomous Vehicles ◽  
Tracking Control ◽  
Control Method ◽  
Lane Change ◽  
Highway Traffic ◽  
Rainy Weather ◽  
Adverse Weather ◽  
Tracking Controller ◽  
The Impact ◽  
Change System

In this study, we propose an adaptive path planning model and tracking control method for collision avoidance and lane-changing manoeuvres on highways in rainy weather. Considering the human-vehicle-road interaction, we developed an adaptive lane change system that consists of an intelligent trajectory planning and tracking controller. Gaussian distribution was introduced to evaluate the impact of rain on the pavement characteristics and deduce adaptive lane-change trajectories. Subsequently, a score-based decision mechanism and multilevel autonomous driving mode that considers safety, comfort, and efficiency were proposed. A tracking controller was designed using a linearised model predictive control method. Finally, using simulated scenarios, the feasibility and effectiveness of the proposed method were demonstrated. The results obtained herein are a valuable resource that can be used to develop an intelligent lane change system for autonomous vehicles and can help improve highway traffic safety and efficiency in adverse weather conditions.

scholarly journals Vehicle-In-The-Loop (VIL) and Scenario-In-The-Loop (SCIL) Automotive Simulation Concepts from the Perspectives of Traffic Simulation and Traffic Control

2019 ◽  
Vol 20 (2) ◽  
pp. 153-161 ◽  
Author(s):  
Márton Tamás Horváth ◽  
Qiong Lu ◽  
Tamás Tettamanti ◽  
Árpád Török ◽  
Zsolt Szalay
Keyword(s):  
Traffic Control ◽  
Autonomous Vehicles ◽  
Traffic Simulation ◽  
Hardware In The Loop ◽  
Traffic Dynamics ◽  
Traffic Conditions ◽  
Novel Approach ◽  
Simulation Based ◽  
Hybrid Concept ◽  
Real Traffic

Abstract As highly automated and autonomous vehicles (AVs) become more and more widespread, inducing the change of traffic dynamics, significant changes occur in traditional traffic control. So far, automotive testing has been done mostly in real-world or pure virtual simulation environment. However, this practice is quite obsolete as testing in real traffic conditions can be quite costly, moreover purely simulation based testing might be inadequate for specific goals. Accordingly, a hybrid concept of the Vehicle-inthe-Loop (ViL) was born recently, in accordance with the Hardware-in-the-Loop concept, i.e. in the ViL concept the vehicle is the 'hardware' within the simulation loop. Furthermore, due to the development of software capabilities, a novel approach, the Scenarioin-the-Loop (SciL) concept evolves based on the ViL approach. The paper defines the main purposes and conditions related to implementing ViL and SciL concepts from the perspective of traffic simulation and traffic control.

The human-like trajectory planning for autonomous vehicles based on optimal control in a test track environment

2021 ◽  
pp. 095440702110090
Author(s):  
Xing Xu ◽  
Minglei Li ◽  
Feng Wang ◽  
Ju Xie ◽  
Xiaohan Wu ◽  
...  
Keyword(s):  
Optimal Control ◽  
Autonomous Vehicles ◽  
Optimal Trajectory ◽  
Control Method ◽  
Autonomous Vehicle ◽  
Trajectory Data ◽  
Test Track ◽  
Optimal Control Method ◽  
The Future ◽  
On The Road

A human-like trajectory could give a safe and comfortable feeling for the occupants in an autonomous vehicle especially in corners. The research of this paper focuses on planning a human-like trajectory along a section road on a test track using optimal control method that could reflect natural driving behaviour considering the sense of natural and comfortable for the passengers, which could improve the acceptability of driverless vehicles in the future. A mass point vehicle dynamic model is modelled in the curvilinear coordinate system, then an optimal trajectory is generated by using an optimal control method. The optimal control problem is formulated and then solved by using the Matlab tool GPOPS-II. Trials are carried out on a test track, and the tested data are collected and processed, then the trajectory data in different corners are obtained. Different TLCs calculations are derived and applied to different track sections. After that, the human driver’s trajectories and the optimal line are compared to see the correlation using TLC methods. The results show that the optimal trajectory shows a similar trend with human’s trajectories to some extent when driving through a corner although it is not so perfectly aligned with the tested trajectories, which could conform with people’s driving intuition and improve the occupants’ comfort when driving in a corner. This could improve the acceptability of AVs in the automotive market in the future. The driver tends to move to the outside of the lane gradually after passing the apex when driving in corners on the road with hard-lines on both sides.

Experimental Investigation into Driver Behavior along Curved and Parallel Diverging Terminals of Exit Interchange Ramps

2021 ◽  
pp. 036119812199742
Author(s):  
Alberto Portera ◽  
Marco Bassani
Keyword(s):  
Design Stage ◽  
Lane Change ◽  
Age And Gender ◽  
Traffic Conditions ◽  
Current Design ◽  
The Difference ◽  
Safety Countermeasures ◽  
And Gender ◽  
Set Up ◽  
Curve Radius

Current design manuals provide guidance on how to design exit ramps to facilitate driving operations and minimize the incidence of crashes. They also suggest that interchanges should be built along straight roadway sections. These criteria may prove ineffective in situations where there is no alternative to terminals being located along curved motorway segments. The paper investigates driving behavior along parallel deceleration curved terminals, with attention paid to the difference in impact between terminals having a curvature which is the same sign as the motorway segment (i.e., continue design), and those having an opposite curvature (i.e., reverse design). A driving simulation study was set up to collect longitudinal and transversal driver behavioral data in response to experimental factor variations. Forty-eight drivers were stratified on the basis of age and gender, and asked to drive along three randomly assigned circuits with off-ramps obtained by combining experimental factors such as motorway mainline curve radius (2 values), terminal length (3), curve direction (2), and traffic conditions (2). The motorway radius was found to be significant for drivers’ preferred speed when approaching the terminal. Terminal length and traffic volume do not have a significant impact on either longitudinal or transversal driver outputs. However, the effect of curve direction was found to be significant, notably for reverse terminals which do not compel drivers to select appropriate speeds and lane change positions. This terminal type can give rise to critical driving situations that should be considered at the design stage to facilitate the adoption of appropriate safety countermeasures.

Intelligent control of complex traffic conditions based on machine learning

2021 ◽  
pp. 1-12
Author(s):  
Zhe Li
Keyword(s):  
Machine Learning ◽  
Simulation Model ◽  
Traffic Simulation ◽  
Learning Algorithms ◽  
Control Model ◽  
Machine Learning Algorithms ◽  
Transmission Model ◽  
Cell Transmission Model ◽  
Traffic Conditions ◽  
Simulation Control

 In order to improve the simulation effect of complex traffic conditions, based on machine learning algorithms, this paper builds a simulation model. Starting from the macroscopic traffic flow LWR theory, this paper introduces the process of establishing the original CTM mathematical model, and combines it with machine learning algorithms to improve it, and establishes the variable cell transmission model VCTM ordinary transmission, split transmission, and combined transmission mathematical expressions. Moreover, this paper establishes a road network simulation model to calibrate related simulation parameters. In addition, this paper combines the actual needs of complex traffic conditions analysis to construct a complex traffic simulation control model based on machine learning, and designs a hybrid microscopic traffic simulation system architecture to simulate all relevant factors of complex road conditions. Finally, this paper designs experiments to verify the performance of the simulation model. The research results show that the simulation control model of complex traffic conditions constructed in this paper has certain practical effects.

Sign in / Sign up

Export Citation Format

Share Document