Prediction of Un-safety Driving Status in Automotive Vehicle Based on Hidden Markov

• Autorzy: Yu D. , Ma J. , Yang J.

Warianty tytułu

PL

Przewidywanie niebezpiecznej sytuacji pojazdu samochodowego bazujące na ukrytym modelu Markova

• Języki publikacji: EN

Abstrakty

EN

Based on Hidden Markov Model, a new prediction method on driving status is advanced. In which, the velocity of following car, the velocity difference and distance headway is input as observation variables, the driving status is output as hidden variable. First the probability of observation status needed is calculated by forward algorithm, then the probability of observation status and driving status appeared together is calculated, at last, the prediction value of driving status could be got by conditional probability. The warning character of the prediction method could be evaluated not only by the accuracy but also by a new index [delta]ATp, which could show the degree of warning time at p probability. The results of simulation show that the method is right, which is in agreement with the result of eye movement checking method named PERCLOS, and it could complete the predictionprediction: when P%= 30%, �[delta]ATp = 2min7 sec, when P%= 40%,[delta]ATp = 1min51 sec; when; when P%= 50%, �[delta]ATp = 56 sec, when P%= 60%, [delta]ATp = 34 sec.

PL

Bazując na ukrytym modelu Markova przedstawiono nową metodę przewidywania status pojazdu. Jako obserwowalne zmiany podaje się szybkość pojazdu z tyłu, odległość a jako zmienne ukryte status pojazdu.

Słowa kluczowe

EN

traffic engineering; driving status; HMM; prediction; probability

PL

inżynieria ruchu; prawdopodobieństwo; przewidywanie

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2012
• Tom: R. 88, nr 1b
• Strony: 115--118
• Opis fizyczny: Bibliogr. 12 poz., rys., wykr.

Twórcy

autor

Yu D.

autor

Ma J.

autor

Yang J.

• Engineer Research Center of Catastrophic Prophylaxis and Treatment of Road & Traffic Safety, Ministry of Education and works at School of Traffic Transportation Engineering, Changsha University of Science & Technology, Hunan, China,

Bibliografia

• [1] Guoqing Xiao, Baozhi Chen. Study on the Mechanism of Human Error and Its Reliability [J]. China Safety Science Journal, 2001,11(1): 22-26. Guoqing Xiao, Baozhi Chen. Study on the Mechanism of Human Error and Its Reliability [J]. China Safety Science Journal, 2001,11 (1): 22-26.
• [2] PERCLOS:A Valid Psychophysiological Measure of Alertness As Assessed by Psychomotor Vigilance, Washington,Office of Motor Carriers,1998.
• [3] Xiaoming Li, Chunfang Yue. Research on Detecting the Driving Condition of the Motor Vehicle Drivers [J]. Sci-Tech Information Development & Economy ,2008,18(3):130-133. Xiaoming Li, Chunfang Yue. Research on Detecting the Condition of the Motor Vehicle Driving Drivers [J]. Sci-Tech Information Development & Economy , 2008,18 (3) :130-133.
• [4] JIN Jian. Reliability evaluation on driver reaction characteristics [C]. International Conference on Transportation Engineering. San Diego: ASCE, 2007: 586-589. [4] JIN Jian. Reliability evaluation on driver reaction characteristics [C]. International Conference on Transportation Engineering. San Diego: ASCE, 2007: 586-589.
• [5] Qiufeng Yang, Weihua Gui. Eye location novel algorithm for fatigue driver [J]. Computer Engineering and Applications, 2008,44(6):20 － 24. Qiufeng Yang, Weihua Gui. Eye location novel algorithm for fatigue driver [J]. Computer Engineering and Applications, 2008,44 (6): 20 - 24.
• [6] Dianye Zhang. Intelligent Traffic Safety Theory and Technology [M]. Chendu: Dianye Zhang. Intelligent Traffic Safety Theory and Technology [M]. Chendu:
• [7] Xiangjun Han, Yanrong Liang, Yong Guan. Research on Embedded Driving Fatigue Monitoring System Based on DSP [J]. Journal of Highway and Transportation Research and Development , 2007,24(1):147 － 150. Xiangjun Han, Yanrong Liang, Yong Guan. Research on Embedded Driving Fatigue Monitoring System Based on DSP [J]. Journal of Highway and Transportation Research and Development , 2007,24 (1): 147 - 150.
• [8] LE Baum and T.Petrie. Statistical inference for probability functions of finite status Markov chains, Ann. Math. Stat. vol. 37,pp.155-160, 1996. [8] LE Baum and T. Petrie. Statistical inference for probability functions of finite status Markov chains, Ann. Math. Stat. Vol. 37, pp.155-160, 1996.
• [9] LAL SKL, CRAIG A. A critical review of the psychophysiology of driver fatigue [J].Biological Psychology, 2001, 55(3): 173-194.
• [10] Pin Zhou, zhaoxinfen. MATLAB Mathematical Statistics Analysis [M]. Beijing: National Defence Industrial Press, 2009. Pin Zhou, zhaoxinfen. MATLAB Mathematical Statistics Analysis [M]. Beijing: National Defence Industrial Press, 2009.
• [11] Chunli Liu, Shuzhong Chen. Hidden Markov model and its use in face recognition [J]. Computer Application and Software, 2004,21(04):68-70. Chunli Liu, Shuzhong Chen. Computer Application and Software, 2004,21 (04) :68-70.
• [12] Dong Zhan-xun, Sun Shou-qian, Wu Qun. Study of correlation between heart rate variability and driving fatigue [J]. Journal of Zhejiang University (Engineering Science, 2010,44(1):73-76.