Multiple-Interval Freeway Traffic Flow Forecasting:

作者: Michael J. Demetsky , Brian L. Smith

DOI: 10.3141/1554-17

关键词:

摘要: Freeway traffic flow forecasting will play an important role in intelligent transportation systems. The TRB Committee on Operations has included freeway its 1995 research program. Much of the past addressed short-term, single-interval predictions. Such limited models not support development longer-term operational strategies needed for such events as hazardous material incidents. A multipleinterval model been developed that predicts volumes 15-min intervals several hours into future. nonparametric regression modeling technique was chosen multiple-interval problem. possesses a number attractive qualities forecasting. It is intuitive and uses data base conditions to generate forecasts. can also be implemented generic algorithm easily calibrated at field locati...

参考文章(4)
Iwao Okutani, Yorgos J. Stephanedes, Dynamic prediction of traffic volume through Kalman filtering theory Transportation Research Part B-methodological. ,vol. 18, pp. 1- 11 ,(1984) , 10.1016/0191-2615(84)90002-X
Gary A. Davis, Nancy L. Nihan, Nonparametric Regression and Short‐Term Freeway Traffic Forecasting Journal of Transportation Engineering-asce. ,vol. 117, pp. 178- 188 ,(1991) , 10.1061/(ASCE)0733-947X(1991)117:2(178)
Yorgos J Stephanedes, Roger A Plum, Panos G Michalopoulos, IMPROVED ESTIMATION OF TRAFFIC FLOW FOR REAL-TIME CONTROL (DISCUSSION AND CLOSURE) Transportation Research Record. ,(1981)
M. C. Jones, R. L. Eubank, Spline Smoothing and Nonparametric Regression Journal of The Royal Statistical Society Series A-statistics in Society. ,vol. 152, pp. 119- 120 ,(1989) , 10.2307/2982831