摘要
在对高速公路事件延误进行实时预测时,首先需要精确预测出事件发生期间的交通流量和通行能力、事件持续时间及车辆到达事件点的时间等参数.事实上,用于确定这些参数的信息是非常复杂的,得到的这些参数值是模糊的,而其变化范围是可以精确确定的.充分考虑上述参数的模糊特性及事件发生期间的交通流量和通行能力的模糊关系,运用α截集表示车辆到达离去曲线,建立了交通事件延误模糊预测模型.利用2001年6月16日发生在美国210-E高速公路的交通事件验证了该模型的可行性,并分析了事件发生期间交通流量、通行能力及事件持续时间的模糊度变化对延误预测结果的影响.
First of all, we should forecast the volume, the capacity during the incident happening, the duration of the incident, the arriving time of vehicles and, etc. when we want to forecast incident delay. In fact, these parameters are fuzzy because of their complexity, yet their change range is highly certain. The paper considers well enough the fuzzy characteristic of these parameters, the fuzzy relationship between the volume and the capacity during the incident, and uses a-cut set to denote the curve of the vehicle arriving-departure and founds the fuzzy forecasting model of incident delay. It validates the model with the traffic incident on 210-E freeway of USA on 2001 - 06 - 16 and analyes the effect on the forecasting result of the delay when the fuzziness of the volume, the capacity during the incident and the duration of the incident change.
出处
《同济大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2005年第11期1458-1463,共6页
Journal of Tongji University:Natural Science
基金
高等学校博士学科点专项科研基金资助项目(2000024707)
关键词
事件延误
模糊算法
到达离去曲线
模糊度
incident delay
fuzzy arithmetic
curve of vehicle arriving-departure
fuzziness
