Connected Cruise Control Based on Adaptive Dynamic Programming Considering Inertial Delay

In this paper, we study the connected vehicular system, where the connected cruise control (CCC) vehicle is mixed into the flow of conventional vehicles, we assume all the vehicles can transmit motional information by vehicle-to-vehicle communication. Considering the inertial delay of the longitudinal vehicle dynamics for the multi-vehicle system, an optimal control problem is formulated to guarantee that the whole vehicles in the platooning drive at the same speed at the same time maintaining the desired headway between adjacent vehicles. By employing the adaptive dynamic programming (ADP) technology, an optimal controller is obtained for the CCC vehicle only relying on online state and input data. Numerical results illustrate that the inertial delay is very important for the control of a platoon system.

[1]  Zhong-Ping Jiang,et al.  Output-feedback adaptive optimal control of interconnected systems based on robust adaptive dynamic programming , 2016, Autom..

[2]  Charles Desjardins,et al.  Cooperative Adaptive Cruise Control: A Reinforcement Learning Approach , 2011, IEEE Transactions on Intelligent Transportation Systems.

[3]  Nathan van de Wouw,et al.  Design and experimental evaluation of cooperative adaptive cruise control , 2011, 2011 14th International IEEE Conference on Intelligent Transportation Systems (ITSC).

[4]  Vicente Milanés Montero,et al.  Cooperative Adaptive Cruise Control in Real Traffic Situations , 2014, IEEE Transactions on Intelligent Transportation Systems.

[5]  Luigi del Re,et al.  A model predictive Cooperative Adaptive Cruise Control approach , 2013, 2013 American Control Conference.

[6]  Zhong-Ping Jiang,et al.  Data-Driven Adaptive Optimal Control of Connected Vehicles , 2017, IEEE Transactions on Intelligent Transportation Systems.

[7]  R. Horowitz,et al.  Control design of an automated highway system , 2000, Proceedings of the IEEE.

[8]  Jianqiang Wang,et al.  Model Predictive Multi-Objective Vehicular Adaptive Cruise Control , 2011, IEEE Transactions on Control Systems Technology.

[9]  D. Kleinman On an iterative technique for Riccati equation computations , 1968 .

[10]  Le Yi Wang,et al.  Platoon Control of Connected Vehicles from a Networked Control Perspective: Literature Review, Component Modeling, and Controller Synthesis , 2018 .

[11]  Andrew G. Barto,et al.  Adaptive linear quadratic control using policy iteration , 1994, Proceedings of 1994 American Control Conference - ACC '94.

[12]  Kazutaka Adachi,et al.  Design of a headway distance control system for ACC , 2001 .

[13]  Petros A. Ioannou,et al.  Evaluation of ACC vehicles in mixed traffic: lane change effects and sensitivity analysis , 2005, IEEE Transactions on Intelligent Transportation Systems.

[14]  J. Hedrick,et al.  String stability of interconnected systems , 1995, Proceedings of 1995 American Control Conference - ACC'95.

[15]  Gábor Stépán,et al.  Traffic jams: dynamics and control , 2010, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[16]  Feng Gao,et al.  Practical String Stability of Platoon of Adaptive Cruise Control Vehicles , 2011, IEEE Transactions on Intelligent Transportation Systems.

[17]  Le Yi Wang,et al.  Communication Information Structures and Contents for Enhanced Safety of Highway Vehicle Platoons , 2014, IEEE Transactions on Vehicular Technology.

[18]  Richard S. Sutton,et al.  Introduction to Reinforcement Learning , 1998 .

[19]  Jiang Zhong-Ping,et al.  Connected cruise control for a platoon of human-operated and autonomous vehicles using adaptive dynamic programming , 2017, 2017 36th Chinese Control Conference (CCC).

[20]  Masayoshi Tomizuka,et al.  Smooth motion control of the adaptive cruise control system by a virtual lead vehicle , 2011 .

[21]  Ge Guo,et al.  Autonomous Platoon Control Allowing Range-Limited Sensors , 2012, IEEE Transactions on Vehicular Technology.

[22]  Nick McKeown,et al.  Automated vehicle control developments in the PATH program , 1991 .

[23]  Zhong-Ping Jiang,et al.  Sampled-data-based adaptive optimal output-feedback control of a 2-degree-of-freedom helicopter , 2016 .

[24]  Steven E. Shladover,et al.  Effects of Adaptive Cruise Control Systems on Highway Traffic Flow Capacity , 2002 .

[25]  Zhong-Ping Jiang,et al.  Adaptive optimal control of connected vehicles , 2015, 2015 10th International Workshop on Robot Motion and Control (RoMoCo).

[26]  Gábor Orosz,et al.  Connected cruise control: modelling, delay effects, and nonlinear behaviour , 2016 .

[27]  Charles A. Desoer,et al.  Longitudinal control of a platoon of vehicles with no communication of lead vehicle information: a system level study , 1993 .