Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/6505
標題: 新型全速度域模糊適應巡航控制器之系統設計與實現
Novel System Design and Implementation of An All-Speed Fuzzy Adaptive Cruise Controller
作者: 陳建次
Chen, Chien-Tzu
關鍵字: Fuzzy;模糊控制;Adaptive cruise control;ACC;Stop&Go;適應性巡航
出版社: 電機工程學系所
引用: [1] F. Sanchez, M. Seguer, A. Freixa, P. Andreas, K. Sochaski and R. Holze, “From Adaptive Cruise Control to Active Safety Systems”, Automotive & Transportation Technology Congress & Exhibition October 1-3, 2001. [2] Adaptive Cruise Control, http://www.i-car.com. [3] J.E. Naranjo, C. Gonzalez, J. Reviejo, R. Garcia, and T. de pedro, “Adaptive Fuzzy Control for Inter-Vehicle Gap Keeping”, IEEE Transactions on Intelligent Transportation system, Vol. 4, No.3, pp. 132-142, sep.2003. [4] Pin-Huan Shi, ” Design and implementation of an FPGA-based Intelligent Cruise Control System”, the thesis of National Chiao Tung University, 2005. [5] M. Person, F. Botling, E. Hesslow and R. Johnsson, “Stop & go controller for adaptive cruise control”, Proceeding of the 1999 IEEE International Conference on Control Application, Vol.2, pp. 1692-1697, 1999. [6] D. Ward, T. Bertram and M. Hiller, “Vehicle Dynamics Simulation for the Development of an Extended Adaptive Cruise Control” [7] Jun-Wei Chen, ”Fuzzy Neural Networks based Adaptive Cruise Control”, the thesis of National Chiao Tung University, 2002. [8] B. Riley, G. Kuo, B. Schwartz and J. Zumberge, “Development of a Controlled Braking Strategy For Vehicle Adaptive Cruise Control”, SAE 2000 World Congress March 6-9, 2000. [9] T. lijima, A. Higashimata, S. Tange, K. Mizoguchi, H, Kamiyama, K. Iwasaki and K. Egawa, “Development of an Adaptive Cruise Control System with Brake Actuation”, 2000 SAE World Congress March 6-9, 2000. [10] D. Littlejohn, T. Fornari, G. Kuo, B. Fulmmer, A. Mooradian,K. Shipp, J. Elliott and K. Lee, “Performance, Robustness, and Durability of an Automatic Brake System for Vehicle Adaptive Cruise Control”, 2004 SAE World Congress March 8-11, 2004. [11] W. Prestl, T. Sauer, J. Steinle and O. Tshchernoster, “The BMW Active Cruise Control ACC”, 2000 SAE World Congress March 6-9, 2000. [12] “ISO 15622: Transport information and control systems-Adaptive Cruise Control systems-Performance requirements and test procedures”, 2002. [13] “SAE J2399: Adaptive Cruise Control (ACC) Operating Characteristics and User Interface”, 2003. [14] G. R. Widmann, M. K. Daniels, L. Hamilton, L. Humm, B. Riley, J K. Schiffmann, D E. Schnelker and W. H. Wishshon, “Comparison of Lidar- Based and Radar-Based Adaptive Cruise Control Systems”, 2000 SAE World Congress March 6-9, 2000. [15] S. Miyahara, “New Algorithm for multiple Object Dection in FM-CW Radar”, 2004 SAE Word Congress March 8-11, 2004. [16] L. Hamilton, L. Humm, m. Daniels and H. Yen, “The role of Vision Sensors in Future Intlligent Vehicles”, Future transportation technology Conference, Auguset 20-21, 2001. [17] R. Dixit, L. Rafaelli, “Radar Requirements and Architecture Trades for Automotive Applications”, IEEE, 1997. [18] Ramzi Abou-Jaude, “ACC Radar Sensor technology, test Requirements, and test Solution”, IEEE, 2003. [19] Anouck R. Girard, Stephen Spry, and J. Karl Hedrick, “Intelligent Cruise-Control Applications”, IEEE Robotics & Automation Magazine, pp. 22-28, March 2005. [20] I-CAR ADVANTAGE [Online].”Adaptive Cruise Control” Available:http://www.i-car.com [21] M Richardson, D Corrigan, P king, I Smith, P barber, K J Burnham, ”Application of control system simulation in the automotive industry”, The Institution of Electrical Engineers, 2000. [22] R. Holve, P. Protzel, K. Naab, “Generating Fuzzy Rules for the Acceleration Control of an Adaptive Cruise Control System”, IEEE, pp. 451-445, 1996. [23] D. Maurel, M. Parent and S. donikian, “Influence of ACC in Stop&Go Mode on Traffic Flow”, Future Transportation Technology Conference and Exposition, August 17-19, 1999. [24] S.Furagaki, H. Kuroda, T. Minowa, M. Kayano, T. Yoshikawa, H. Takenaga, K. Nakamura and K. Takano, “An Adaptive Cruise Control Using Wheel Torque Management Technique”, International Congress and Exposition, February 23-26, 1998. [25] P. Fancher, R. Ervin, S. Bogard, ”A Field Operational Test of Adaptive Cruise Control : System Operability in naturalistic Use”, International Congress and Exposition, February 23-26,1998. [26] J. Robinson, D. K. Paul, J. Bird, D. Dawson. T. Brown, D. Spencer and B. Prime, “A Millimetric Car Radar Front End for Automotive Cruise Control”, IEE, Savoy Place, London WC2R OBL, Uk, 1998. [27] R. Rajamani and C. Zhu, “Semi-Autonomous Adaptive Cruise Control Systems”, IEEE, 2002. [28] M. A. Goodrich, E. R. Boer, H. Inoue, ”A Characterization of Dynamic Human Braking Behavior with Implications for ACC design”, IEEE, 1999. [29] J. Wang and R. Rajamani, “Should Adaptive Cruise-Control Systems be Designed to Maintain a Constant Time Gap Between Vehicles?”, IEEE,2004. [30] W. D. Jones,” Keeping Cars”, IEEE SPECTRUM, September 2001. [31] C. Y. Lee and J. J. Lee, ”Object Recognition Algorithm for Adaptive Cruise Control of Vehicles Using Laser Scanning Sensor”, IEEE Intelligent transportation Systems, October1-3, 2000. [32] A. R. Girard, S. Spry, and J. K. Hedrick, ”Intelligent Cruise-Control applications”, IEEE, 2001.
摘要: 
整合先進感測器與自動控制技術為車輛科技運用趨勢,其目的為提供駕駛輔助與提昇車輛安全,其中具備雷達(77 GHz)偵測與動力、煞車控制,適用於高速公路環境(車速:40kph以上)之適應性巡航系統(ACC),已從實驗室研發進入到配備於市售量產車輛階段,而結合影像辨識或近距雷達(24GHz),可適用於市區環境低速(車速:40kph以下)跟車甚至停止的Stop&Go系統為下一波主流,此類系統透過前方即時車距與本車車速之資訊,無論前車於定速、加速或減速之行駛情況,目的能洽當的控制動力與煞車力輸出,使與前車保持一安全距離之自動定距跟車巡航,除情況緊急而系統研判煞車力不足有碰撞之危險,系統發出警示駕駛者必需介入控制外,於一般正常情況下均可達縱向自動駕駛的功能。
本論文目的為設計全速度域(車速:0~120kph)使用之適應性巡航系統,以單一控制器達成涵蓋ACC與Stop&Go之使用範圍。於車輛縱向控制設計,我們運用真空泵的特性,控制從引擎進氣導入的負壓源,達油門與煞車踏板行程控制的目的,此種設計可避免需介入引擎管理( EMS)與ABS煞車控制單元之技術障礙。本試驗平台由一部SUV車改裝而成,於前方保險桿裝置有一具雷射測距雷達,並擷取車上ABS車速資訊,以及裝置有監控油門與煞車作動行程之感測器。控制器利用模糊控制理論做設計,由前車速所推算之安全距離與實際距離差值,以及相對車速等2因子作為輸入,輸出則為調變真空泵氣壓差之PWM訊號,運用Simulink編寫邏輯控制程式,並透過高階控制器的使用,快速展現於實車試驗上,從記錄器收錄車輛動態行為資訊,修正控制器參數之研判。
於試驗安全考量上,先使用虛擬ACC與Stop&Go之前車情境,計算前後車之相對距離與相對車速,進行實車控制器的調校,之後再進行2車實際跟隨之控制試驗。根據實驗之結果,證實本論之縱向控制設計可符合安全與舒適的要求,以及適用於全速度域環境之條件。

This combination of advanced sensing and automatic control is a tendency for recent vehicle technology and application, aiming at assisting the driver and improving vehicle safety. To date, adaptive cruise controllers (ACC) incorporating radar (77GHz), engine management and electronic hydraulic have been proven effective for highway environments with required speed up to 40 km per hour. Having been successfully examined and tested in laboratory environments, such ACCs are now becoming mass products which can be installed on several kinds of commercial vehicles. Be shown suitable for low-speed urban environments with the speed less than 40 km per hour, stop & go controllers integrating with image recognition or short-ranging radar may become next main-streaming products in automobile electronics market. On the basis of the real-time relative distance (between the preceding vehicle and the host vehicle) and the present speed of the host vehicle, such ACC and stop & go controllers aim at providing the host vehicle appropriate power outputs and braking to maintain a safe and desired distance of car-following with the preceding vehicle . All these two controllers achieve automatic driving in the longitudinal direction at normal conditions, but give alarms to ask driver's intervention to steer the host vehicle in case of emergency that the controllers are in the danger of insufficient braking to avoid car collision.
The objective of the thesis is to design an all-speed adaptive cruise control system with car-following speed ranging from 0 to 120 kph. This novel controller covers the main functions of conventional ACC and stop & go controllers. For vehicular longitudinal control, we use vacuum boosters to control the throttle and the braking pedal, thus circumventing the technical difficulties of using engine management system and anti-brake system. Modified by a commercial SUV, the experimental car is equipped with a lidar on the bumper, a speed sensor mounted at the shaft of a wheel, and two sensors for measuring the opening of the throttle and the position of the braking pedal. A fuzzy controller is synthesized by inputting the difference of the actual relative distance and the safe distance obtained from the preceding vehicle, and the relative speed, and outputting the PWM signal to control the output force of the vacuum booster. With the use of the high-level controller, the fuzzy control law is easily and rapidly implemented using Simulink for the experimental car, and the controller's parameters can be changed and updated by analyzing the collected data from the relative distance from the lidar, the speed of the host vehicle, the opening of the throttle and the position of the braking pedal.
For the sake of safe testing, experimental results are conducted by virtually simulating the various possible car-following conditions for the ACC and stop & go controllers, thereby obtaining virtually relative distance and speed to tune the controller's parameters and make sure the safety of the controller. Afterwards, the realistic car following experiments are then performed to confirm that the proposed all-speed longitudinal control design is capable of achieving the requirements of comfort and safety and giving a satisfactory performance at all-speed conditions.
URI: http://hdl.handle.net/11455/6505
其他識別: U0005-1808200614474700
Appears in Collections:電機工程學系所

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