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Enhanced AHS Safety Through the Integration of Vehicle Control and Communication

Author

Listed:
  • Hedrick, J. K.
  • Sengupta, R.
  • Xu, Q.
  • Kang, Y.
  • Lee, C.

Abstract

We comparatively assess the influence of adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC) systems on highway traffic behaviors. The primary goal is to study the design and implementation of vehicle-vehicle/roadside-vehicle communication, which enhances an ACC system to a CACC one. In addition, the impact of market penetration of ACC/CACC vehicles and controller aggression are also evaluated. Two simulation works are presented. The microscopic work simulates a single ACC/CACC vehicle using MATLAB/SIMULINK. A cut-in scenario and a braking scenario are tested. Vehicle-vehicle communication saves control effort in the former scenario, while shows little effect in the latter. In the macroscopic work we simulate ACC/CACC controlled highway merging with SHIFT language. The results show beneficial effects of communication in terms of braking effort, average velocity, waiting-to-merge queue length, and main lane traffic shock wave caused by merging. The higher the market penetration of controlled vehicles the better the system performs. The aggressiveness of controller has mixed influence, which provides a tradeoff between efficiency and safety. We study the wireless communication among highway vehicles. A vehicle- vehicle Location-Based Broadcast (LBB) communication protocol is designed to meet highway safety applications' communication requirements. The analytical expressions of the performance of the protocol in terms of probability of transmission failure and channel occupancy are derived with commonly satisfied assumptions. The optimal relation between the performance and design parameters is obtained from the expressions. The sensitivity of the protocol performance is tested for various communication conditions as well as highway traffic conditions. Feasible combinations of the communication and highway traffic parameters are found for certain requirements on protocol performance. The analysis is conducted in accordance to the communication condition in the newly-assigned 5.9 GHz Dedicated Short Range Communication (DSRC) spectrum. More experiments are done to find out the factors that influence the slip measurements in order to refine our results of friction coefficient estimation. To obtain the circumferential velocity of the wheel, the exact tire radius is needed. The change in the spring constant based on tire air pressure is obtained, and also the increase in tire radius due to the faster velocity is considered. The normal force applied on each wheel due to the vehicle pitch motion resulting from acceleration and deceleration is also estimated using static vehicle model. Brake torque sensor and accelerometer are used to find the normal force. Using the estimated normal force and road force, the tire-road friction coefficient is obtained. The characteristics of the friction coefficient and slip curve are studied on different road conditions with the refined slip measurements. An originally proposed slip-based controller does not seem to work very well in an practical situation due to actuator time delay. However, experimental results show that the existing nonlinear controller with the limited slip assumption shows good performance even in an emergency braking situation. Therefore, instead of using different control algorithm, this research focuses on the control strategies dedicated to emergency situation for the platoon. In order to integrate the benefits from the communication and friction coefficient estimation technique, a safe control strategy is considered in the situation when the platoon of vehicles needs to decelerate rapidly. It is assumed that we have the knowledge of friction coefficients between road and tire and our vehicles are equipped with proper communication methods. Then, the theoretical bounds for the reference trajectory accelerations are calculated that do not cause the actuator saturation using linear vehicle and controller model.

Suggested Citation

  • Hedrick, J. K. & Sengupta, R. & Xu, Q. & Kang, Y. & Lee, C., 2003. "Enhanced AHS Safety Through the Integration of Vehicle Control and Communication," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt0b9833wb, Institute of Transportation Studies, UC Berkeley.
  • Handle: RePEc:cdl:itsrrp:qt0b9833wb
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    References listed on IDEAS

    as
    1. Godbole, Datta N. & Lygeros, John, 2000. "Safety and Throughput Analysis of Automated Highway Systems," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt6767x8n2, Institute of Transportation Studies, UC Berkeley.
    2. Lee, Duke, 2001. "Wireless Token Ring Protocol," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt316112zf, Institute of Transportation Studies, UC Berkeley.
    3. Hedrick, J. K. & Uchanski, M. & Xu, Q., 2001. "Enhanced AHS Safety Through the Integration of Vehicle Control and Communication," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt938545qc, Institute of Transportation Studies, UC Berkeley.
    4. Roger R. Stough (ed.), 2001. "Intelligent Transport Systems," Books, Edward Elgar Publishing, number 2214.
    5. Bose, Arnab & Ioannou, Petros, 1999. "Analysis of Traffic Flow with Mixed Manual and Semi-automated Vehicles," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt60t6z2mn, Institute of Transportation Studies, UC Berkeley.
    6. Lygeros, John & Lynch, Nancy, 2000. "Conditions for Safe Deceleration of Strings of Vehicles," Institute of Transportation Studies, Research Reports, Working Papers, Proceedings qt306410hv, Institute of Transportation Studies, UC Berkeley.
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