广西大学学报(自然科学版)
廣西大學學報(自然科學版)
엄서대학학보(자연과학판)
JOURNAL OF GUANGXI UNIVERSITY (NATURAL SCIENCE EDITION)
2014年
6期
1234-1239
,共6页
于广鹏%谭德荣%田厚杰%吕长民
于廣鵬%譚德榮%田厚傑%呂長民
우엄붕%담덕영%전후걸%려장민
智能交通%主动防碰撞%驾驶倾向%反应时间%模糊推理
智能交通%主動防踫撞%駕駛傾嚮%反應時間%模糊推理
지능교통%주동방팽당%가사경향%반응시간%모호추리
intelligent transportation%active collision%driving tendency%reaction time%fuzzy infer-ence
为进一步完善汽车主动防碰撞预警系统,建立了一种基于模糊推理的驾驶员反应时间修正方法。该方法以驾驶员的实时反应时间为研究对象,通过实时采集驾驶员的加油频率、深加油比例、制动频率、深制动比例等数据,利用所建立的模糊推理规则判断出一个适应于当前驾驶员动态驾驶倾向的实时反应时间,然后对Berkeley算法进行修正,计算出车辆行驶所需要的安全车距,并在驾驶模拟器上进行了对比分析。经模拟实验验证,本方法所确定的15名驾驶员的理论平均反应时间为1.0000 s,方差为0.0417,而实际平均反应时间为1.0077 s,方差为0.0469,并且根据理论反应时间所确定的预警距离与根据实际反应时间所确定的预警距离比较接近。可见本方法能在一定程度上提高安全预警算法的准确性,能够充分考虑驾驶员的实时驾驶特性,降低预警系统的虚警率。
為進一步完善汽車主動防踫撞預警繫統,建立瞭一種基于模糊推理的駕駛員反應時間脩正方法。該方法以駕駛員的實時反應時間為研究對象,通過實時採集駕駛員的加油頻率、深加油比例、製動頻率、深製動比例等數據,利用所建立的模糊推理規則判斷齣一箇適應于噹前駕駛員動態駕駛傾嚮的實時反應時間,然後對Berkeley算法進行脩正,計算齣車輛行駛所需要的安全車距,併在駕駛模擬器上進行瞭對比分析。經模擬實驗驗證,本方法所確定的15名駕駛員的理論平均反應時間為1.0000 s,方差為0.0417,而實際平均反應時間為1.0077 s,方差為0.0469,併且根據理論反應時間所確定的預警距離與根據實際反應時間所確定的預警距離比較接近。可見本方法能在一定程度上提高安全預警算法的準確性,能夠充分攷慮駕駛員的實時駕駛特性,降低預警繫統的虛警率。
위진일보완선기차주동방팽당예경계통,건립료일충기우모호추리적가사원반응시간수정방법。해방법이가사원적실시반응시간위연구대상,통과실시채집가사원적가유빈솔、심가유비례、제동빈솔、심제동비례등수거,이용소건립적모호추리규칙판단출일개괄응우당전가사원동태가사경향적실시반응시간,연후대Berkeley산법진행수정,계산출차량행사소수요적안전차거,병재가사모의기상진행료대비분석。경모의실험험증,본방법소학정적15명가사원적이론평균반응시간위1.0000 s,방차위0.0417,이실제평균반응시간위1.0077 s,방차위0.0469,병차근거이론반응시간소학정적예경거리여근거실제반응시간소학정적예경거리비교접근。가견본방법능재일정정도상제고안전예경산법적준학성,능구충분고필가사원적실시가사특성,강저예경계통적허경솔。
In order to further improve the automobile active collision warning system, a driver reac-tion time correction method based on fuzzy inference was established. This method takes the drivers’ real-time response time as the research object. By real-time collecting the drivers’ accelerating fre-quency, deep accelerated ratio, braking frequency and deep braking ratio, the established fuzzy in-ference rules were used to determine a real-time response time adapted to the drivers’ current dynam-ic driving tendency, and then to modify the Berkeley algorithm to calculate the vehicle’s safety dis-tance. Finally, comparative analysis was carried on the driving simulator. It has been verified by simulation experiments that the average responding time of 15 drivers was 1. 000 0 s, and the vari-ance was 0. 041 7, while the average actual responding time was 1. 007 7 s, and the variance was 0. 046 9 . The warning distance predicted by the theory reaction time and actual reaction time were very close. Obviously, to some extent, this method could improve the accuracy of the warning algo-rithm, could give full consideration to the driver’s real-time driving characteristics, and could reduce the false alarm rate of the warning system.