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为了提高避险车道定位精度,从交通事故统计数据和道路条件与车辆状态2个方面深入分析了避险车道定位的影响因素,阐述了中心点三角白化权函数的原理,提出了基于中心点三角白化权函数的避险车道定位灰色评估模型,利用此模型对依托工程长下坡路段各单位路段的行车安全性进行综合评估与安全等级分类,并在分析评估结果的基础上确定设置避险车道的候选位置与设置次序。利用此模型对依托工程长下坡路段各单位路段的行车安全性进行综合评估与安全等级分类,将评定等级为“差”类路段确定为设置避险车道的候选路段;通过比较相邻候选路段的灰色综合聚类系数,确定在路段9和路段20末端设置避险车道。依托工程避险车道设置效果表明,通过本模型确定的避险车道位置合理。
In order to improve the positioning accuracy of hedging lane, the influencing factors of hedging lane positioning are analyzed in detail from two aspects of traffic accident statistics, road conditions and vehicle status. The principle of whitening weight function of center point is expounded. A gray evaluation model of the hedging lane alignment of the whitening weight function is proposed. Based on this model, the comprehensive evaluation and safety classification of the driving safety of each unit section of the long downhill section are classified. Based on the analysis and evaluation results, Candidate location and setting order. Based on this model, the comprehensive evaluation and safety classification of driving safety of each unit section of long downhill section are classified, and the section of “bad” rating is determined as the candidate section of safe haven lane. By comparing adjacent driving candidates’ The gray comprehensive clustering coefficient of the road section determines that the safe haven lane is set at the end of the road section 9 and the road section 20. Rely on the project set the effect of hedging lanes show that the safe haven lanes determined by this model is reasonable.