To improve the forecasting reliability of travel time, the time-varying confidence interval of travel time on arterials is forecasted using an autoregressive integrated moving average and generalized autoregressive co...To improve the forecasting reliability of travel time, the time-varying confidence interval of travel time on arterials is forecasted using an autoregressive integrated moving average and generalized autoregressive conditional heteroskedasticity （ARIMA-GARCH） model. In which, the ARIMA model is used as the mean equation of the GARCH model to model the travel time levels and the GARCH model is used to model the conditional variances of travel time. The proposed method is validated and evaluated using actual traffic flow data collected from the traffic monitoring system of Kunshan city. The evaluation results show that, compared with the conventional ARIMA model, the proposed model cannot significantly improve the forecasting performance of travel time levels but has advantage in travel time volatility forecasting. The proposed model can well capture the travel time heteroskedasticity and forecast the time-varying confidence intervals of travel time which can better reflect the volatility of observed travel times than the fixed confidence interval provided by the ARIMA model.展开更多
In order to ensure on-time arrival when travelersmake their trips, the stochastic network assignment modelunder uncertainty of travel time is investigated. First, basedon travelers＇ route choice behavior, the reliabl...In order to ensure on-time arrival when travelersmake their trips, the stochastic network assignment modelunder uncertainty of travel time is investigated. First, basedon travelers＇ route choice behavior, the reliable travel timeconfidence level （RTTCL）, which is the probability that a triparrives within the shortest average travel time plus theacceptable travel time difference, is defined. Then, areliability-based user equilibrium （RUE） model, whichhypothesizes that for each OD pair no traveler can improvehis/her RTTCL by unilaterally changing routes, is built.Since the traditional traffic assignment algorithms are notfeasible to solve the RUE model, a quasi method of successiveaverage （QMSA） is developed. Using Nguyen-Dupuis andSioux Falls networks, the model and the algorithm are tested.The results show that the QMSA algorithm can rapidlyconverge to a high accuracy for solving the proposed RUEmodel, and the RUE model can provide a good response totravelers＇ behavior in the stochastic network.展开更多
研究老年人的活动空间有助于更好理解老年人的出行行为,对于提高城市交通系统对社会老龄化的适应性,促进交通公平具有重要意义.采用2016年中国昆明市的居民出行调查数据和建成环境数据,对老年人活动空间的测度和影响因素进行研究.借助...研究老年人的活动空间有助于更好理解老年人的出行行为,对于提高城市交通系统对社会老龄化的适应性,促进交通公平具有重要意义.采用2016年中国昆明市的居民出行调查数据和建成环境数据,对老年人活动空间的测度和影响因素进行研究.借助地理信息系统(geographic information system,GIS)可视化与分析工具,利用标准置信椭圆法对老年人活动空间进行测度,并对其分布特征和群体性差异进行统计分析,基于序次logit模型探究老年人活动空间的影响因素.结果表明,超过一半的老年人活动空间分布在以住址为中心的5 km2范围内,并表现出显著的群体性差异.公园密度、交叉口密度、道路网密度、商场密度、到公交站最近距离、年龄、性别、家庭结构及家庭年收入对老年人的活动空间均有显著影响.展开更多
基金The National Natural Science Foundation of China(No.51108079)
文摘To improve the forecasting reliability of travel time, the time-varying confidence interval of travel time on arterials is forecasted using an autoregressive integrated moving average and generalized autoregressive conditional heteroskedasticity （ARIMA-GARCH） model. In which, the ARIMA model is used as the mean equation of the GARCH model to model the travel time levels and the GARCH model is used to model the conditional variances of travel time. The proposed method is validated and evaluated using actual traffic flow data collected from the traffic monitoring system of Kunshan city. The evaluation results show that, compared with the conventional ARIMA model, the proposed model cannot significantly improve the forecasting performance of travel time levels but has advantage in travel time volatility forecasting. The proposed model can well capture the travel time heteroskedasticity and forecast the time-varying confidence intervals of travel time which can better reflect the volatility of observed travel times than the fixed confidence interval provided by the ARIMA model.
基金The National Natural Science Foundation of China(No.51608115,51578150,51378119)the Natural Science Foundation of Jiangsu Province(No.BK20150613)+2 种基金the Scientific Research Foundation of Graduate School of Southeast University(No.YBJJ1679)the Scientific Innovation Research of College Graduates in Jiangsu Province(No.KYLX15_0150)the China Scholarship Council(CSC)Program
文摘In order to ensure on-time arrival when travelersmake their trips, the stochastic network assignment modelunder uncertainty of travel time is investigated. First, basedon travelers＇ route choice behavior, the reliable travel timeconfidence level （RTTCL）, which is the probability that a triparrives within the shortest average travel time plus theacceptable travel time difference, is defined. Then, areliability-based user equilibrium （RUE） model, whichhypothesizes that for each OD pair no traveler can improvehis/her RTTCL by unilaterally changing routes, is built.Since the traditional traffic assignment algorithms are notfeasible to solve the RUE model, a quasi method of successiveaverage （QMSA） is developed. Using Nguyen-Dupuis andSioux Falls networks, the model and the algorithm are tested.The results show that the QMSA algorithm can rapidlyconverge to a high accuracy for solving the proposed RUEmodel, and the RUE model can provide a good response totravelers＇ behavior in the stochastic network.
文摘研究老年人的活动空间有助于更好理解老年人的出行行为,对于提高城市交通系统对社会老龄化的适应性,促进交通公平具有重要意义.采用2016年中国昆明市的居民出行调查数据和建成环境数据,对老年人活动空间的测度和影响因素进行研究.借助地理信息系统(geographic information system,GIS)可视化与分析工具,利用标准置信椭圆法对老年人活动空间进行测度,并对其分布特征和群体性差异进行统计分析,基于序次logit模型探究老年人活动空间的影响因素.结果表明,超过一半的老年人活动空间分布在以住址为中心的5 km2范围内,并表现出显著的群体性差异.公园密度、交叉口密度、道路网密度、商场密度、到公交站最近距离、年龄、性别、家庭结构及家庭年收入对老年人的活动空间均有显著影响.
