A Cruise Control Method for Connected Vehicle Systems Considering Side Vehicles Merging Behavior

On the basis of wireless vehicle-to-vehicle communication, this paper proposes a superior control strategy for the merging behavior of connected cruise control (CCC) considering the effect of time delays. A novel range policy that integrates the consideration of side-vehicle merging scene is established, based on which a general strategy is proposed focusing on the acceleration control and incorporating various information delays. In this portion, the time-delay effect for the plant stability and head-to-tail string stability of CCC is explored and analyzed in detail. The results demonstrate that the traffic efficiency, the driving safety, and the ride comfort of CCC vehicles can be improved by the proposed method. In addition, the sensitivity study regarding the controller gain and the platoon’s connectivity structure is exploited, which is proved to be of importance for system stability.

[1]  Gábor Orosz,et al.  DESIGNING NETWORK MOTIFS IN CONNECTED VEHICLE SYSTEMS: DELAY EFFECTS AND STABILITY , 2013 .

[2]  Gábor Orosz,et al.  Beyond-Line-of-Sight Identification by Using Vehicle-to-Vehicle Communication , 2018, IEEE Transactions on Intelligent Transportation Systems.

[3]  Dongbin Zhao,et al.  Full-range adaptive cruise control based on supervised adaptive dynamic programming , 2014, Neurocomputing.

[4]  Jun Tan,et al.  Development and evaluation of Cooperative Adaptive Cruise Controllers , 2015, 2015 IEEE International Conference on Mechatronics and Automation (ICMA).

[5]  Le Yi Wang,et al.  Influence of information flow topology on closed-loop stability of vehicle platoon with rigid formation , 2014, 17th International IEEE Conference on Intelligent Transportation Systems (ITSC).

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

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

[8]  Gábor Orosz,et al.  Digital Effects and Delays in Connected Vehicles: Linear Stability and Simulations , 2013 .

[9]  Dirk Helbing,et al.  Adaptive cruise control design for active congestion avoidance , 2008 .

[10]  Kyongsu Yi,et al.  A driver-adaptive stop-and-go Cruise control strategy , 2004, IEEE International Conference on Networking, Sensing and Control, 2004.

[11]  Fan Bai,et al.  Reliability Analysis of DSRC Wireless Communication for Vehicle Safety Applications , 2006, 2006 IEEE Intelligent Transportation Systems Conference.

[12]  Gábor Orosz,et al.  Dynamics of connected vehicle systems with delayed acceleration feedback , 2014 .

[13]  Gábor Orosz,et al.  Motif-Based Design for Connected Vehicle Systems in Presence of Heterogeneous Connectivity Structures and Time Delays , 2016, IEEE Transactions on Intelligent Transportation Systems.

[14]  H. Fritz,et al.  Longitudinal and lateral control of heavy duty trucks for automated vehicle following in mixed traffic: experimental results from the CHAUFFEUR project , 1999, Proceedings of the 1999 IEEE International Conference on Control Applications (Cat. No.99CH36328).

[15]  Zhili Sun,et al.  Applications of vehicular communications for reducing fuel consumption and CO2 emission: the state of the art and research challenges , 2012, IEEE Communications Magazine.

[16]  Rui Oliveira,et al.  Development of Platform-Independent System for Cooperative Automated Driving Evaluated in GCDC 2016 , 2018, IEEE Transactions on Intelligent Transportation Systems.

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

[18]  Hiok Chai Quek,et al.  Driving Profile Modeling and Recognition Based on Soft Computing Approach , 2009, IEEE Transactions on Neural Networks.

[19]  Jing Zhou,et al.  Range policy of adaptive cruise control vehicles for improved flow stability and string stability , 2005, IEEE Transactions on Intelligent Transportation Systems.

[20]  Petros A. Ioannou,et al.  A Comparision of Spacing and Headway Control Laws for Automatically Controlled Vehicles1 , 1994 .

[21]  Dongbin Zhao,et al.  Comprehensive comparison of online ADP algorithms for continuous-time optimal control , 2017, Artificial Intelligence Review.

[22]  Wenhu Qin,et al.  Research on a DSRC-Based Rear-End Collision Warning Model , 2014, IEEE Transactions on Intelligent Transportation Systems.

[23]  S. Li,et al.  Scalability limitation of homogeneous vehicular platoon under undirected information flow topology and constant spacing policy , 2015, 2015 34th Chinese Control Conference (CCC).

[24]  Takatsugu Hirayama,et al.  Integrated modeling of driver gaze and vehicle operation behavior to estimate risk level during lane changes , 2013, 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013).

[25]  Gábor Orosz,et al.  Stability and Frequency Response Under Stochastic Communication Delays With Applications to Connected Cruise Control Design , 2017, IEEE Transactions on Intelligent Transportation Systems.

[26]  Steven Lake Waslander,et al.  MPC based collaborative adaptive cruise control with rear end collision avoidance , 2014, 2014 IEEE Intelligent Vehicles Symposium Proceedings.

[27]  Hossein Nourkhiz Mahjoub,et al.  A Learning-Based Stochastic MPC Design for Cooperative Adaptive Cruise Control to Handle Interfering Vehicles , 2018, IEEE Transactions on Intelligent Vehicles.

[28]  Klaus C. J. Dietmayer,et al.  Continuous Driver Intention Recognition with Hidden Markov Models , 2008, 2008 11th International IEEE Conference on Intelligent Transportation Systems.

[29]  Shekhar Verma,et al.  Prediction of Lane Change Trajectories through Neural Network , 2010, 2010 International Conference on Computational Intelligence and Communication Networks.

[30]  Peter Seiler,et al.  Disturbance propagation in vehicle strings , 2004, IEEE Transactions on Automatic Control.

[31]  Dot Hs.  Evaluation of Lane Change Collision Avoidance Systems Using the National Advanced Driving Simulator , 2010 .

[32]  Henk Wymeersch,et al.  Design and Experimental Validation of a Cooperative Driving System in the Grand Cooperative Driving Challenge , 2012, IEEE Transactions on Intelligent Transportation Systems.

[33]  Hiren M. Mandalia,et al.  Using Support Vector Machines for Lane-Change Detection , 2005 .

[34]  Shin Kato,et al.  Energy ITS: another application of vehicular communications , 2010, IEEE Communications Magazine.

[35]  S. Ilgin Guler,et al.  Using connected vehicle technology to improve the efficiency of intersections , 2014 .

[36]  Qi Wang,et al.  Investigation of Discretionary Lane-Change Characteristics Using Next-Generation Simulation Data Sets , 2014, J. Intell. Transp. Syst..

[37]  Bart van Arem,et al.  The Impact of Cooperative Adaptive Cruise Control on Traffic-Flow Characteristics , 2006, IEEE Transactions on Intelligent Transportation Systems.

[38]  Christian Bonnet,et al.  A collision mitigation strategy for intelligent vehicles to compensate for human factors affecting manually driven vehicles , 2017, 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC).

[39]  G. Stépán.  Retarded dynamical systems : stability and characteristic functions , 1989 .

[40]  Derek Caveney,et al.  Cooperative Vehicular Safety Applications , 2010, IEEE Control Systems.