scholarly journals Control Design, Stability Analysis, and Traffic Flow Implications for Cooperative Adaptive Cruise Control Systems with Compensation of Communication Delay

2020 ◽  
Vol 2674 (8) ◽  
pp. 638-652
Author(s):  
Yu Zhang ◽  
Yu Bai ◽  
Jia Hu ◽  
Meng Wang
Keyword(s):  
Traffic Flow ◽  
Local Stability ◽  
Adaptive Cruise Control ◽  
Control Design ◽  
Communication Delay ◽  
Cruise Control ◽  
String Stability ◽  
Cooperative Adaptive Cruise Control ◽  
Time Gap ◽  
Traffic Flow Stability

Communication delay is detrimental to the performance of cooperative adaptive cruise control (CACC) systems. In this paper, we incorporate communication delay explicitly into control design and propose a delay-compensating CACC. In this new CACC system, the semi-constant time gap (Semi-CTG) policy, which is modified on the basis of the widely-used CTG policy, is employed by a linear feedback control law to regulate the spacing error. The semi-CTG policy uses historical information of the predecessor instead of its current information. By doing so, communication delay is fully compensated, which leads to better stability performance. Three stability properties—local stability, string stability, and traffic flow stability—are analyzed. The local stability and string stability of the proposed CACC system are guaranteed with the desired time gap as small as the communication delay. Both theoretical analysis and simulation results show that the delay-compensating CACC has better string stability and traffic flow stability than the widely-used CACC system. Furthermore, the proposed CACC system also shows the potential for improving traffic throughput and fuel efficiency. Robustness of the proposed system against uncertainties of sensor delay and vehicle dynamics is also verified with simulation.

Intelligent Cruise Control Systems and Traffic Flow Behavior

1999 ◽  
Author(s):  
Darbha Swaroop ◽  
K. R. Rajagopal
Keyword(s):  
Control Systems ◽  
Traffic Flow ◽  
Adaptive Cruise Control ◽  
Flow Behavior ◽  
Flow Stability ◽  
Traffic Density ◽  
Cruise Control ◽  
String Stability ◽  
Control Laws ◽  
Traffic Flow Stability

Abstract In analogy to the flow of fluids, it is expected that the aggregate density and the velocity of vehicles in a section of a freeway adequately describe the traffic flow dynamics. The conservation of mass equation together with the aggregation of the vehicle following dynamics of controlled vehicles describes the evolution of the traffic density and the aggregate speed of a traffic flow. There are two kinds of stability associated with traffic flow problems — string stability (or car-following stability) and traffic flow stability. We make a clear distinction between traffic flow stability and string stability, and such a distinction has not been recognized in the literature, thus far. String stability is stability with respect to intervehicular spacing; intuitively, it ensures the knowledge of the position and velocity of every vehicle in the traffic, within reasonable bounds of error, from the knowledge of the position and velocity of a vehicle in the traffic. String stability is analyzed without adding vehicles to or removing vehicles from the traffic. On the other hand, traffic flow stability deals with the evolution of traffic velocity and density in response to the addition and/or removal of vehicles from the flow. Traffic flow stability can be guaranteed only if the velocity and density solutions of the coupled set of equations is stable, i.e., only if stability with respect to automatic vehicle following and stability with respect to density evolution is guaranteed. Therefore, the flow stability and critical capacity of any section of a highway is dependent not only on the vehicle following control laws and the information used in their synthesis, but also on the spacing policy employed by the control system. Such a dependence has practical consequences in the choice of a spacing policy for adaptive cruise control laws and on the stability of the traffic flow consisting of vehicles equipped with adaptive cruise control features on the existing and future highways. This critical dependence is the subject of investigation in this paper. This problem is analyzed in two steps: The first step is to understand the effect of spacing policy employed by the Intelligent Cruise Control (ICC) systems on traffic flow stability. The second step is to understand how the dynamics of ICC system affects traffic flow stability. Using such an analysis, it is shown that cruise control systems that employ a constant time headway policy lead to unacceptable characteristics for the traffic flows.

Should Adaptive Cruise Control (ACC) Systems Be Designed to Maintain a Constant Time-Gap Between Vehicles?

2001 ◽  
Author(s):  
Junmin Wang ◽  
Rajesh Rajamani
Keyword(s):  
Boundary Conditions ◽  
Traffic Flow ◽  
Adaptive Cruise Control ◽  
Constant Time ◽  
Cruise Control ◽  
Unconditionally Stable ◽  
Time Gap ◽  
Traffic Flow Stability ◽  
The Stability ◽  
Gap Spacing

Abstract This paper addresses the stability of traffic flow on a highway when the vehicles operate under an adaptive cruise control (ACC) system. ACC systems are commonly designed to maintain a constant time-gap between vehicles during vehicle following. Previous researchers in literature have produced contradictory results on whether the traffic flow is stable when the constant time gap spacing policy is used. This paper resolves the contradiction and shows that the boundary conditions used at the inlets and exits influence traffic flow stability in the case of the constant time-gap policy. Further, the paper shows that it is possible to design an unconditionally stable spacing policy, i.e. a spacing policy which guarantees traffic stability under all boundary conditions. The practical implications of instability are shown through traffic simulation results. The advantages of an unconditionally stable spacing policy over the constant time-gap policy are demonstrated. The answer to the question “Should ACC systems be designed to maintain a constant time gap between vehicles?” is NO. It is quite easy to develop alternate spacing policies with superior stability properties.

Smart Driving System for Improving Traffic Flow

2017 ◽  
Vol 7 (7) ◽  
pp. 236
Author(s):  
Rajesh Kumar Gupta ◽  
L. N. Padhy ◽  
Sanjay Kumar Padhi
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Urban Areas ◽  
Adaptive Cruise Control ◽  
Human Perception ◽  
Cruise Control ◽  
Driving System ◽  
V2v Communication ◽  
Traffic Conditions ◽  
Cooperative Adaptive Cruise Control

Traffic congestion on road networks is one of the most significant problems that is faced in almost all urban areas. Driving under traffic congestion compels frequent idling, acceleration, and braking, which increase energy consumption and wear and tear on vehicles. By efficiently maneuvering vehicles, traffic flow can be improved. An Adaptive Cruise Control (ACC) system in a car automatically detects its leading vehicle and adjusts the headway by using both the throttle and the brake. Conventional ACC systems are not suitable in congested traffic conditions due to their response delay.  For this purpose, development of smart technologies that contribute to improved traffic flow, throughput and safety is needed. In today’s traffic, to achieve the safe inter-vehicle distance, improve safety, avoid congestion and the limited human perception of traffic conditions and human reaction characteristics constrains should be analyzed. In addition, erroneous human driving conditions may generate shockwaves in addition which causes traffic flow instabilities. In this paper to achieve inter-vehicle distance and improved throughput, we consider Cooperative Adaptive Cruise Control (CACC) system. CACC is then implemented in Smart Driving System. For better Performance, wireless communication is used to exchange Information of individual vehicle. By introducing vehicle to vehicle (V2V) communication and vehicle to roadside infrastructure (V2R) communications, the vehicle gets information not only from its previous and following vehicle but also from the vehicles in front of the previous Vehicle and following vehicle. This enables a vehicle to follow its predecessor at a closer distance under tighter control.

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.

Evaluation of Driver Car-Following Behavior Models for Cooperative Adaptive Cruise Control Systems

2017 ◽  
Vol 2622 (1) ◽  
pp. 84-95 ◽  
Author(s):  
Mizanur Rahman ◽  
Mashrur Chowdhury ◽  
Kakan Dey ◽  
M. Rafiul Islam ◽  
Taufiquar Khan
Keyword(s):  
Vehicle Dynamics ◽  
Adaptive Cruise Control ◽  
User Acceptance ◽  
Evaluation Framework ◽  
Cruise Control ◽  
String Stability ◽  
Maximum Acceleration ◽  
Car Following ◽  
Cooperative Adaptive Cruise Control ◽  
Behavior Models

A cooperative adaptive cruise control (CACC) system targeted to obtain a high level of user acceptance must replicate the driving experience in each CACC vehicle without compromising the occupant’s comfort. “User acceptance” can be defined as the safety and comfort of the occupant in the CACC vehicle in terms of acceptable vehicle dynamics (i.e., the maximum acceleration or deceleration) and string stability (i.e., the fluctuations in the vehicle’s position, speed, and acceleration). The primary objective of this study was to develop an evaluation framework for the application of a driver car-following behavior model in CACC system design to ensure user acceptance in terms of vehicle dynamics and string stability. The authors adopted two widely used driver car-following behavior models, ( a) the optimum velocity model (OVM) and ( b) the intelligent driver model (IDM), to prove the efficacy of the evaluation framework developed in this research for CACC system design. A platoon of six vehicles was simulated for three traffic flow states (uniform speed, speed with constant acceleration, and speed with constant deceleration) with different acceleration and deceleration rates. The maximum acceleration or deceleration and the sum of the squares of the errors of the follower vehicle speed were measured to evaluate user acceptance in terms of vehicle dynamics and string stability. Analysis of the simulation results revealed that the OVM performed better at modeling a CACC system than did the IDM in terms of acceptable vehicle dynamics and string stability.

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