城市工况下车距控制系统的研究
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摘要
随着汽车工业的发展,私家车迅速进入人们的生活,给城市交通带来了很大的负担,在城市交通工况下,车流较长,车速较慢,行驶工况频繁更换,在较近的车距条件下,车辆必须要能够根据前方车辆行驶状态及时改变本车的行驶状态。由此,提出城市工况下的车距控制系统。
城市工况下车距控制系统的功能是通过控制车辆的加速度变化量来控制车辆的起步、停车、加减速以及巡航行驶,从而减轻驾驶员由于频繁改变车辆行驶状态而带来的疲劳感。
论文对城市工况下的车距控制系统做了整体分析,对信息感知部分比较重要的测速测距传感器做了比较和选择,在已有的驾驶员预瞄决策模型的基础上,针对城市工况复杂性、时变性等特点,提出了城市工况下最优预瞄加速度模型,并对模型建立了评价体系;在对最优预瞄加速度模型进行详细论证的基础上,又针对加速度与节气门开度、制动踏板力之间难以直接建立数学关系这一特点,运用适当的模糊规则,建立了模糊控制器,对节气门和制动踏板进行控制,实现了加速度的动态修正;同时又对车辆这一复杂的非线性系统,在机理分析基础上建立了适合于控制应用的车辆动力学模型、发动机及制动器模型,并对模型进行了建模仿真分析及论证。
论文在已有的最优预瞄加速度决策算法、以及决策点的评价指标的基础上,重点研究了城市工况下最优预瞄加速度决策算法、以及决策点的评价指标,针对城市工况的特点建立了不同的仿真模型,最后将各章节搭建的系统集成为Simulink工作条件下的仿真模块,在Matlab/Simulink软件环境下对系统进行动态仿真,通过仿真结果对系统的合理性和算法的有效性进行了验证。
With the development of automobile industry, many people have had their own vehicles. Because of that, it makes a heavy traffic burden. Because of the characteristics of the urban traffic, which has higher traffic flow, low speed and flexible vehicle driving behaviors, the driving state of the vehicles must be changed frequently, so distance control system of urban traffic is put forward.
The function of distance control system of urban traffic is using the acceleration of the vehicle to make the vehicle start, stop, accelerate, decelerate and cruise, so that the system can alleviate weariness of drivers which is caused by changing the driving state of the vehicle frequently.
At first, the thesis makes a analysis on the whole distance control system of urban traffic, choose the right the important sensor of the information catching part, which is used to measure speed and distance. And then on the base of the known driver prediction algorithm, best acceleration prediction model of distance control system of urban traffic and the assessment system of it have been set up. The thesis built two fuzzy controllers to control throttle and braking pedal in order to carry on the dynamic revision of acceleration which is from the prediction algorithm of acceleration. Then the thesis built a complicated vehicle dynamics model, engine model and brake model, which are used to make simulations later.
On the base of the known the best prediction algorithm of acceleration and the assessment part, the thesis researched emphatically in the best prediction algorithm of acceleration of distance control system of urban traffic. According to different working conditions, the thesis builds different models, and gets them together to make simulation analysis using Matlab/Simulink software and uses these simulation results to prove that the distance control system of urban traffic is timely, logical and effectual.
城市工况下车距控制系统的功能是通过控制车辆的加速度变化量来控制车辆的起步、停车、加减速以及巡航行驶,从而减轻驾驶员由于频繁改变车辆行驶状态而带来的疲劳感。
论文对城市工况下的车距控制系统做了整体分析,对信息感知部分比较重要的测速测距传感器做了比较和选择,在已有的驾驶员预瞄决策模型的基础上,针对城市工况复杂性、时变性等特点,提出了城市工况下最优预瞄加速度模型,并对模型建立了评价体系;在对最优预瞄加速度模型进行详细论证的基础上,又针对加速度与节气门开度、制动踏板力之间难以直接建立数学关系这一特点,运用适当的模糊规则,建立了模糊控制器,对节气门和制动踏板进行控制,实现了加速度的动态修正;同时又对车辆这一复杂的非线性系统,在机理分析基础上建立了适合于控制应用的车辆动力学模型、发动机及制动器模型,并对模型进行了建模仿真分析及论证。
论文在已有的最优预瞄加速度决策算法、以及决策点的评价指标的基础上,重点研究了城市工况下最优预瞄加速度决策算法、以及决策点的评价指标,针对城市工况的特点建立了不同的仿真模型,最后将各章节搭建的系统集成为Simulink工作条件下的仿真模块,在Matlab/Simulink软件环境下对系统进行动态仿真,通过仿真结果对系统的合理性和算法的有效性进行了验证。
With the development of automobile industry, many people have had their own vehicles. Because of that, it makes a heavy traffic burden. Because of the characteristics of the urban traffic, which has higher traffic flow, low speed and flexible vehicle driving behaviors, the driving state of the vehicles must be changed frequently, so distance control system of urban traffic is put forward.
The function of distance control system of urban traffic is using the acceleration of the vehicle to make the vehicle start, stop, accelerate, decelerate and cruise, so that the system can alleviate weariness of drivers which is caused by changing the driving state of the vehicle frequently.
At first, the thesis makes a analysis on the whole distance control system of urban traffic, choose the right the important sensor of the information catching part, which is used to measure speed and distance. And then on the base of the known driver prediction algorithm, best acceleration prediction model of distance control system of urban traffic and the assessment system of it have been set up. The thesis built two fuzzy controllers to control throttle and braking pedal in order to carry on the dynamic revision of acceleration which is from the prediction algorithm of acceleration. Then the thesis built a complicated vehicle dynamics model, engine model and brake model, which are used to make simulations later.
On the base of the known the best prediction algorithm of acceleration and the assessment part, the thesis researched emphatically in the best prediction algorithm of acceleration of distance control system of urban traffic. According to different working conditions, the thesis builds different models, and gets them together to make simulation analysis using Matlab/Simulink software and uses these simulation results to prove that the distance control system of urban traffic is timely, logical and effectual.
引文
1周堪. 2007年全国道路交通事故情况分析.交通安全周刊, 2008, (1): 1~3
2 James R Sayer. Intelligent cruise control-issue for consideration. SAE, 1996, 16(67): 1544~1546
3张甜,陈德海.一种车辆防碰撞预警及自动刹车系统.江西理工大学学报. 2006, 6(27): 1~3
4 Hermann Winner, Stefan witte, Werner Uhler, et al. Adaptive Cruise Control System Aspects and Development Trends. SAE, 1996, 1(10): 1412~1421
5 Jean-philippe Lauffenburger, Jerome Baujon, Michel Basser, et al. The N.A.I.C.C. Project: a Navigation Aided Intelligent Cruise Control System. SAE. 2000, 1(1300): 365~372
6 Konghui Guo, Feng Pan. Driver Model Based On the Preview Optimal Artificial Neural Network. AVEC. 2002, (20024590)
7 Salvucci, D. D. Boer, E. R. &Liu. Toward an integrated model of driver behavior in a cognitive architecture. Transportation Research Record. 2001
8 Dr. A. A. Oloufa, P. E, Dr. A. E. Radwan. Server-based Collision Avoidance using DGPS. 8th World Congress on Intelligent Transportation Systems. 2001, 9
9赵建顺,王玉泰.超声汽车防撞系统的研究.济南大学学报. 2001, (3): 25~28
10柳长立.日本未来汽车的安全预警系统.汽车电器. 1999, (1): 3~5
11 Erez Dagan, Ofer Mano. Forward Collision Warning with a Single Camera. IEEE Intelligent Vehicles Symposium(IV2004). 2004
12 Yi K, Hong J. A Vehicle Control Algorithm for Stop-and-Go Cruise Control[C]. Proc Instn Mech Engrs. 2001
13 Dr. Greg Marsden, Prof. Mike McDonald. Towards an Understanding of Adaptive Cruise Control. Transportation Research Group. Transportation Research. 2001; 33~51
14谭胜.日产研发出车距控制辅助系统.轻型汽车技术. 2006, 5(201): 31
15侯德藻,王跃建,高峰等.基于模型匹配方法的汽车主动避撞下位控制系统的研究.汽车工程. 2003, 25(4): 399~402
16 Li Guo, Zhang Liangqi, Zhang Peng. An iterative learning PD Longitudinal controller for unmanned land vehicle. Controll theory and application. 1994,11(6): 713~719
17林粤彤,王飞跃,肖靖等.基于模糊神经网络的智能车辆个性自动驾驶系统的设计与实现.自动化学报. 2001, 27(4): 531~541
18刘禄江.汽车防撞毫米波雷达技术及临界报警探讨.汽车电器. 2005, (7):9
19李鹏.宽带毫米波雷达实时信号采集系统研究.国防科技大学硕士学位论文. 2006: 10~20
20邓继海.毫米波近程雷达目标反射特性测量研究.南京理工大学硕士学位论文. 2007: 30~37
21武畅. LFMCW雷达信号处理系统的DSP实现.电子科技大学硕士学位论文. 2006: 20~22
22高振海,管欣,郭孔辉.预瞄跟随理论和驾驶员模型在汽车智能驾驶研究中的应用.交通运输工程学报. 2002, 2(2): 63~66
23管欣,高镇海,郭孔辉.汽车预期轨迹驾驶员模糊决策模型及典型路况仿真.汽车工程. 2001, 23(1): 13~17
24邱君.智能辅助驾驶系统的控制算法及其实现.吉林大学硕士学位论文. 2001: 35~45
25朱永强.汽车自适应巡航系统的控制策略开发及行驶环境评估.吉林大学硕士学位论文. 2007: 14~16
26张立存.高速汽车弯道前方碰撞预警算法的研究.吉林大学硕士学位论文. 2004: 21~22
27陈守煜.系统模糊决策理论与应用.大连理工大学出版社,1994: 25~35
28 Kyongsu Yi, Sejin Lee, Young Do Kwon, et al. An Investigation of Intelligent Cruise Control Laws forPassenger Vehicles. Journal of Automobile Engineering. 2001, (2): 1~13
29 Ioannou P, Xu Z. . Throttle and Brake Control Systems for Automatic Vehicle Following. IVHS Journal. 1994, (1): 345~377
30邢建国.一类严格反馈非线性系统鲁棒控制及其在汽车巡航行驶控制中的应用.浙江大学博士学位论文. 2002: 96~99
31张国良,曾静,柯熙政,邓方林.模糊控制及其MATLAB应用.西安交通大学出版社, 2002: 12~13
32 Dr·Paul Venhovens, Dr·Karl Naab, Bartono Adiprasito. Stop and Go Cruise Control. FISITA World Automotive Congress. Seoul, Korea. 2000: 63~65
33王景武.汽车自适应巡航的最优预瞄加速度控制算法研究.吉林大学博士学位论文. 2004: 40~45
34王立新.模糊系统与模糊控制教程.清华大学出版社,2003: 5~10
35 MamdaniEH. Applications of fuzzy algorithms for sim-ple dynamic plant. IEEE Proc. 1974, (21): 1585-1588
36 Altrock, C. V., B. Krause, and H. J. Zimmermann. Advanced Fuzzy Logic Control of a Model Can in Extreme Situations. Fuzzy Sets and Systems. 1992, 48(2): 41~45
37 Aracil, J. , A. Olleror, and A. Garcia-Cerezo. Stability Indices for the Global Analysis of Expert Contral System. IEEE Trans. on Systems, Man, and Cybern. 1999, 19(5): 998~1007
38 Carvajal J. et a.l Fuzzy PID Controller Design, Performance evaluation, and stability analysis. Information-Science, 2000, (123): 249~270
39 SohlG A, Borrow J E. Experiments and Simulations on Nonlinear Nontrol of a Hydraulic Servo System. IEEE. Trans. Contr. Syst. Techno. 1999, 7(2): 238~247
40何仁,王永涛,赵迎生.汽车联合制动系统的性能仿真分析.兵工学报. 2007, 10(28): 1153~1157
41 HE Ren. Supplementary Brake Equipment of Automobile. Beijing: Chemical Industry Press. 2005:2~4
42詹军.用于自适应巡航控制的汽车纵向动力学模型的建立.吉林大学学报. 2006, 2(36): 157~160
43程军.汽车防抱死制动系统的理论与实践.北京理工大学出版社, 1998: 37~38
44张元涛,谢昭莉,冯引安.汽车制动器试验制动管压伺服系统建模与仿真.现代制造工程. 2006, (11): 103~107
45 W van Winsum, A Heino. Choice of Time-headway in Car-following and Therole of Time-to-Collision Information in Braking. Ergonomics. 1996, (4): 579~592
2 James R Sayer. Intelligent cruise control-issue for consideration. SAE, 1996, 16(67): 1544~1546
3张甜,陈德海.一种车辆防碰撞预警及自动刹车系统.江西理工大学学报. 2006, 6(27): 1~3
4 Hermann Winner, Stefan witte, Werner Uhler, et al. Adaptive Cruise Control System Aspects and Development Trends. SAE, 1996, 1(10): 1412~1421
5 Jean-philippe Lauffenburger, Jerome Baujon, Michel Basser, et al. The N.A.I.C.C. Project: a Navigation Aided Intelligent Cruise Control System. SAE. 2000, 1(1300): 365~372
6 Konghui Guo, Feng Pan. Driver Model Based On the Preview Optimal Artificial Neural Network. AVEC. 2002, (20024590)
7 Salvucci, D. D. Boer, E. R. &Liu. Toward an integrated model of driver behavior in a cognitive architecture. Transportation Research Record. 2001
8 Dr. A. A. Oloufa, P. E, Dr. A. E. Radwan. Server-based Collision Avoidance using DGPS. 8th World Congress on Intelligent Transportation Systems. 2001, 9
9赵建顺,王玉泰.超声汽车防撞系统的研究.济南大学学报. 2001, (3): 25~28
10柳长立.日本未来汽车的安全预警系统.汽车电器. 1999, (1): 3~5
11 Erez Dagan, Ofer Mano. Forward Collision Warning with a Single Camera. IEEE Intelligent Vehicles Symposium(IV2004). 2004
12 Yi K, Hong J. A Vehicle Control Algorithm for Stop-and-Go Cruise Control[C]. Proc Instn Mech Engrs. 2001
13 Dr. Greg Marsden, Prof. Mike McDonald. Towards an Understanding of Adaptive Cruise Control. Transportation Research Group. Transportation Research. 2001; 33~51
14谭胜.日产研发出车距控制辅助系统.轻型汽车技术. 2006, 5(201): 31
15侯德藻,王跃建,高峰等.基于模型匹配方法的汽车主动避撞下位控制系统的研究.汽车工程. 2003, 25(4): 399~402
16 Li Guo, Zhang Liangqi, Zhang Peng. An iterative learning PD Longitudinal controller for unmanned land vehicle. Controll theory and application. 1994,11(6): 713~719
17林粤彤,王飞跃,肖靖等.基于模糊神经网络的智能车辆个性自动驾驶系统的设计与实现.自动化学报. 2001, 27(4): 531~541
18刘禄江.汽车防撞毫米波雷达技术及临界报警探讨.汽车电器. 2005, (7):9
19李鹏.宽带毫米波雷达实时信号采集系统研究.国防科技大学硕士学位论文. 2006: 10~20
20邓继海.毫米波近程雷达目标反射特性测量研究.南京理工大学硕士学位论文. 2007: 30~37
21武畅. LFMCW雷达信号处理系统的DSP实现.电子科技大学硕士学位论文. 2006: 20~22
22高振海,管欣,郭孔辉.预瞄跟随理论和驾驶员模型在汽车智能驾驶研究中的应用.交通运输工程学报. 2002, 2(2): 63~66
23管欣,高镇海,郭孔辉.汽车预期轨迹驾驶员模糊决策模型及典型路况仿真.汽车工程. 2001, 23(1): 13~17
24邱君.智能辅助驾驶系统的控制算法及其实现.吉林大学硕士学位论文. 2001: 35~45
25朱永强.汽车自适应巡航系统的控制策略开发及行驶环境评估.吉林大学硕士学位论文. 2007: 14~16
26张立存.高速汽车弯道前方碰撞预警算法的研究.吉林大学硕士学位论文. 2004: 21~22
27陈守煜.系统模糊决策理论与应用.大连理工大学出版社,1994: 25~35
28 Kyongsu Yi, Sejin Lee, Young Do Kwon, et al. An Investigation of Intelligent Cruise Control Laws forPassenger Vehicles. Journal of Automobile Engineering. 2001, (2): 1~13
29 Ioannou P, Xu Z. . Throttle and Brake Control Systems for Automatic Vehicle Following. IVHS Journal. 1994, (1): 345~377
30邢建国.一类严格反馈非线性系统鲁棒控制及其在汽车巡航行驶控制中的应用.浙江大学博士学位论文. 2002: 96~99
31张国良,曾静,柯熙政,邓方林.模糊控制及其MATLAB应用.西安交通大学出版社, 2002: 12~13
32 Dr·Paul Venhovens, Dr·Karl Naab, Bartono Adiprasito. Stop and Go Cruise Control. FISITA World Automotive Congress. Seoul, Korea. 2000: 63~65
33王景武.汽车自适应巡航的最优预瞄加速度控制算法研究.吉林大学博士学位论文. 2004: 40~45
34王立新.模糊系统与模糊控制教程.清华大学出版社,2003: 5~10
35 MamdaniEH. Applications of fuzzy algorithms for sim-ple dynamic plant. IEEE Proc. 1974, (21): 1585-1588
36 Altrock, C. V., B. Krause, and H. J. Zimmermann. Advanced Fuzzy Logic Control of a Model Can in Extreme Situations. Fuzzy Sets and Systems. 1992, 48(2): 41~45
37 Aracil, J. , A. Olleror, and A. Garcia-Cerezo. Stability Indices for the Global Analysis of Expert Contral System. IEEE Trans. on Systems, Man, and Cybern. 1999, 19(5): 998~1007
38 Carvajal J. et a.l Fuzzy PID Controller Design, Performance evaluation, and stability analysis. Information-Science, 2000, (123): 249~270
39 SohlG A, Borrow J E. Experiments and Simulations on Nonlinear Nontrol of a Hydraulic Servo System. IEEE. Trans. Contr. Syst. Techno. 1999, 7(2): 238~247
40何仁,王永涛,赵迎生.汽车联合制动系统的性能仿真分析.兵工学报. 2007, 10(28): 1153~1157
41 HE Ren. Supplementary Brake Equipment of Automobile. Beijing: Chemical Industry Press. 2005:2~4
42詹军.用于自适应巡航控制的汽车纵向动力学模型的建立.吉林大学学报. 2006, 2(36): 157~160
43程军.汽车防抱死制动系统的理论与实践.北京理工大学出版社, 1998: 37~38
44张元涛,谢昭莉,冯引安.汽车制动器试验制动管压伺服系统建模与仿真.现代制造工程. 2006, (11): 103~107
45 W van Winsum, A Heino. Choice of Time-headway in Car-following and Therole of Time-to-Collision Information in Braking. Ergonomics. 1996, (4): 579~592