Jin I. Ge

Optimal Control of Connected Vehicle Systems With Communication Delay and Driver Reaction Time

In this paper, linear quadratic regulation is used to obtain an optimal design of connected cruise control (CCC). We consider vehicle strings where a CCC vehicle receives position and velocity signals through wireless vehicle-to-vehicle communication from multiple vehicles ahead. Communication delay, driver reaction time, and heterogeneity of vehicles are considered. The optimal feedback law is obtained by minimizing a cost function defined by headway and velocity errors and the acceleration of the CCC vehicle on an infinite horizon. We show that, by decomposing the optimization problem, the feedback gains can be obtained recursively as signals from vehicles farther ahead become available, and that the gains decay exponentially with the number of cars between the source of the signal and the CCC vehicle. Such properties allow graceful degradation of CCC performance under imperfect communication. The effects of the cost function on the head-to-tail string stability are also investigated and the robustness against variations in human parameters is tested. The analytical results are verified by numerical simulations at the nonlinear level. The results allow us to significantly reduce the complexity of CCC design.

Stability of Connected Vehicle Platoons With Delayed Acceleration Feedback

Wireless vehicle-to-vehicle communication technologies such as the dedicated short range communication (DSRC) may be used to assist drivers in sensing and responding to impalpable information such as the precise acceleration of vehicles ahead. In this paper, we investigate the impact of delayed acceleration feedback on traffic flow using a nonlinear car-following model. It is shown that acceleration feedback can improve the stability of uniform traffic flow, though excessive acceleration feedback leads to undesired high frequency oscillations. Additionally, time delays in the communication channel may shrink the stable domain by introducing mid-frequency oscillations. Finally, we show that one may stabilize vehicle platoons using delayed acceleration feedback even in cases when finite driver reaction time would destabilize the system. Our results may lead to more robust cruise control systems with increased driver comfort in connected vehicle environment.© 2013 ASME

Optimal control of connected vehicle systems

In this paper, linear quadratic tracking (LQT) is used to optimize the control gains for connected cruise control (CCC). We consider a vehicle string where the CCC vehicle at the tail receives position and velocity signals through wireless vehicle-to-vehicle (V2V) communication from other vehicles ahead (that are not equipped with CCC). An optimal feedback law is obtained by minimizing a cost function defined by headway and velocity errors and the acceleration of the CCC vehicle on an infinite horizon. We show that the feedback gains can be obtained recursively as signals from vehicles farther ahead become available, and that the gains decay exponentially with the number of cars between the source of the signal and the CCC vehicle. The effects of the cost function on the head-to-tail string stability are investigated and the robustness against variations in human parameters is tested. The analytical results are verified by numerical simulations.

To Delay or Not to Delay—Stability of Connected Cruise Control

The dynamics of connected vehicle systems are investigated where vehicles exchange information via wireless vehicle-to-vehicle (V2V) communication. In particular, connected cruise control (CCC) strategies are considered when using different delay configurations. Disturbance attenuation (string stability) along open chains is compared to the linear stability results using ring configuration. The results are summarized using stability diagrams that allow one to design the control gains for different delay values. Critical delay values are calculated and trade-offs between the different strategies are pointed out.

Estimation of feedback gains and delays in connected vehicle systems

In this paper, we present different parameter estimation methods that may be used to identify the dynamics of human-driven vehicles in connected vehicle systems. By exploiting the information received via wireless vehicle-to-vehicle communication from two consecutive vehicles ahead, the estimation algorithms identify the driver reaction time and feedback gains simultaneously. We compare the algorithms in terms of convergence rate and estimation accuracy, and present a systematic way to improve both performance measures. The estimated parameters can then be used in connected cruise control algorithms that incorporate the transmitted signals in a vehicles longitudinal motion control.

Connected cruise control design using probabilistic model checking

In this paper, we synthesize a connected cruise controller with performance guarantee using probabilistic model checking, for a vehicle that receives motion information from several vehicles ahead through wireless vehicle-to-vehicle communication. We model the car-following dynamics of the preceding vehicles as Markov chains and synthesize the connected cruise controller as a Markov decision process. We show through simulations that such a design is robust against imperfections in communication.