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.

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.

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.

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.

scholarly journals ANALYSIS OF HEXAPOD ROBOT LOCOMOTION

2010 ◽  
Vol 2 (1) ◽  
pp. 36-39 ◽  
Author(s):  
Tomas Luneckas
Keyword(s):  
Inverse Kinematics ◽  
Robot Control ◽  
Control Method ◽  
Servo Control ◽  
Control Methods ◽  
Control Parameters ◽  
Hexapod Robot ◽  
Robot Locomotion ◽  
Tripod Gait ◽  
And Control

Hexapod robot locomotion is analyzed. Trajectory forming method for one leg is introduced. Servo angles are expressed using geometric inverse kinematics method. Forming of tripod gait is described and a diagram representing it is presented. Servo control parameters are defined to ensure fluent and versatile robot control. Several servo control methods are presented. After testing robot movement using different servo control methods, gait generation is corrected and control method that meets servo control parameters is chosen.

A Coordinative Steering Control Method Based on PID Compensation for an Electric Vehicle

2014 ◽  
Vol 644-650 ◽  
pp. 475-484
Author(s):  
Hao Qiu ◽  
Song Feng Liang
Keyword(s):  
Electric Vehicle ◽  
Control Method ◽  
Mathematic Model ◽  
Steering System ◽  
Control Parameters ◽  
Matlab Simulation ◽  
Steering Control ◽  
Control Effect ◽  
Excellent Control ◽  
And Control

This paper presents a coordinating steering control method in an Electric Vehicle with Four-in-Wheel-Motors Drive and Four-Wheel Independent Steering. This control method applied a PID compensation to solve the absonant steering problem. This research builds a mathematic model for the control system and uses the Matlab simulation to verify the feasibility and control effect. Then it is applied in a real car environment for further experiment in which the paper studies the control effect with varied control parameters. According to the analysis of the experiment, a practical solution for steering System is proposed with excellent control effect.

scholarly journals Intelligent and Hybrid Control Method of a 3-DOF Robot Used for Hip, Knee and  Ankle Rehabilitation

2020 ◽  
Author(s):  
wahab aminiazar ◽  
Rasoul Farahi
Keyword(s):  
Control Method ◽  
Hybrid Control ◽  
Robot Manipulator ◽  
Specific Area ◽  
Inverse Kinematic ◽  
Control Parameters ◽  
Safety Factors ◽  
Adaptive Controls ◽  
Planar Robot ◽  
And Control

Abstract Background: There is an increasing trend in using robots for medical purposes. One specific area is rehabilitation. Rehabilitation is one of the non-drug treatments in community health which means the restoration of the abilities to maximize independence. It is a prolonged work and costly labor. On the other hand, by using the flexible and efficient robots in rehabilitation area, this process will be more useful for handicapped patients.Methods: In this study, a rule-based intelligent control methodology is proposed to mimic the behavior of a healthy limb in a satisfactory way by a 3-DOF planar robot. Inverse kinematic of the planar robot will be solved by neural networks and control parameters will be optimized by genetic algorithm, as rehabilitation progress.Results: The results of simulations are presented by defining a physiotherapy simple mode on desired trajectory. MATLAB/Simulink is used for simulations. The system is capable of learning the action of the physiotherapist for each patient and imitating this behaviour in the absence of a physiotherapist that can be called robotherapy.Conclusions: In this study, a therapeutic exercise planar 2-DOF robot is designed and controlled for lower-limb rehabilitation. The robot manipulator is controlled by combination of hybrid and adaptive controls. Some safety factors and stability constraints are defined and obtained. The robot is stopped when the safety factors are not satisfied. Kinematics of robot is estimated by an MLP neural network and proper control parameters are achieved using GA optimization

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