降雨量对OD行程时间可靠性影响分析

Analysis of Effects of Rainfall on Origin-destinationbased Travel Time Reliability

为详细研究降雨量对OD行程时间可靠性的影响,基于Uber出行共享的3年美国波士顿10对OD行程时间数据及WeatherUnderground网站提供的小时历史天气,构建了OD行程时间高斯混合模型(GMM).模型参数利用EM法进行求解,K值根据K-S检验后的P值(大于0.5000)进行确定,模型分位数利用二分法进行求解.提出一种基于缓冲指数(BI)的新指标缓冲指数变化率(BIVR)作为定量评估指标.结果表明:降雨会降低总体OD行程时间可靠性,降低效果随降雨量提高而增强,但增强效果并不明显;尽管可能性较低,但当降雨处于次要影响因素时可能提高可靠性;小雨天气可视为正常天气;雨天可靠性显著低于正常天气,居民在雨天(除小雨外)出行应预留更多时间.

With the purpose of investigating the effects of various rainfalls on the origin-destination(OD)-based travel time reliability(TTR)in detail,Gaussian mixture models of OD-based travel time were constructed based on three-year travel time data of ten OD pairs in Boston,USA,shared by Uber movement,and the hourly historical weather provided by WeatherUnderground website.And the model parameters,K-value and percentile-value were solved by expectation-maximum algorithm,the P-value(greater than 0.5000)after K-S test and bisection method,respectively.Additionally,buffer index variation ratio(BIVR)is proposed for quantitative analysis.The results show that:rain can reduce the overall ODTTR,and the reduction effect increases with the rainfall increase,but the gaps are unobvious;Despite lower probability,ODTTR may be improved when rain as a secondary factor;Light rain can be regarded as normal weather;The ODTTR of rainy days is significantly lower than that of normal weather,so residents should reserve more time for travel in rainy days(except light rain).