Fault Tolerant Control to Ensure String Stability of Cooperative Adaptive Cruise Control under Communication Interruption

Author(s):  
Guangming Nie ◽  
Zixu Hao ◽  
Feng Zhao ◽  
Yantao Tian
Author(s):  
Mizanur Rahman ◽  
Mashrur Chowdhury ◽  
Kakan Dey ◽  
M. Rafiul Islam ◽  
Taufiquar Khan

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.


Author(s):  
Anye Zhou ◽  
Siyuan Gong ◽  
Chaojie Wang ◽  
Srinivas Peeta

Vehicle-to-vehicle communications can be unreliable because of interference and information congestion, which leads to the dynamic information flow topology (IFT) in a platoon of connected and autonomous vehicles. Some existing studies adaptively switch the controller of cooperative adaptive cruise control (CACC) to optimize string stability when IFT varies. However, the difference of transient response between controllers can induce uncomfortable jerks at switching instances, significantly affecting riding comfort and jeopardizing vehicle powertrain. To improve riding comfort while maintaining string stability, the authors introduce a smooth-switching control-based CACC scheme with IFT optimization (CACC-SOIFT) by implementing a bi-layer optimization model and a Kalman predictor. The first optimization layer balances the probability of communication failure and control performance optimally, generating a robust IFT to reduce controller switching. The second optimization layer adjusts the controller parameters to minimize tracking error and the undesired jerk. Further, a Kalman predictor is applied to predict vehicle acceleration if communication failures occur. It is also used to estimate the states of preceding vehicles to suppress the measurement noise and the acceleration disturbance. The effectiveness of the proposed CACC-SOIFT is validated through numerical experiments based on NGSIM field data. Results indicate that the CACC-SOIFT framework can guarantee string stability and riding comfort in the environment of dynamic IFT.


2010 ◽  
Vol 39 ◽  
pp. 545-549
Author(s):  
Wen Shen Wang ◽  
Chen Huang

In order to ensure the safe and reliable operation of adaptive cruise control (ACC) system, the fault-tolerant control theory is used to design the feedback control for acc system and the control rule for sensor failure in the linear continuous system is described. On the basis of riccati equation, the design method and steps of fault-tolerant controller are given from the view of optimal control. By taking adaptive cruise control of a certain mini car as research object, the simulation calculation is carried out. By applying such fault-tolerant controller for the acc system, the simulation results show that the system has no sensitiveness to the sensor faults, and the method can satisfy the demand of fault-tolerant control.


Author(s):  
Xujie Wang ◽  
Yue Wang

This paper discusses the design of a human-aware cooperative adaptive cruise control (CACC) system that (i) takes into account driver comfort in autonomous cruise control, and (ii) provides assistive corrections to avoid driver errors. To incorporate driver characteristics into system controller design, two self-learning algorithms are used to estimate driver’s preferred time headway. We then develop a human-like blending control for CACC based on a model predictive control (MPC)-type method, which integrates the driver comfort, traffic efficiency, and fuel economy criteria. Furthermore, a driving assistance controller is developed to help human driver to maintain string stability in platoon. Simulation results show that (i) the human-like CACC design can significantly improve driving experience, and (ii) with the help of the assistive controller, string stability is satisfied for both exclusively autonomous CACC and when the CACC switches to manual driving in a platoon.


Author(s):  
Yu Zhang ◽  
Yu Bai ◽  
Jia Hu ◽  
Meng Wang

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.


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