Travel time information is a fundamental component in Advanced Traveler Information System. In this paper, we propose a short-term travel time estimation and prediction framework for long freeway corridor, considering measurements from vehicle detectors (VD) and floating car data (FCD). The modeling approach is based on a modified Nearest-Neighborhood (NN) model with threshold and a regression model capturing the within day variations. The advantages are that our approach allows for missing data without the need of data imputation in real-time, and is suitable for travel time prediction of long corridors. The validation analysis using an 88 km long section of freeway shows satisfactory results.
Short-term travel time estimation and prediction for long freeway corridor using NN and regression
01.09.2012
726077 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Reliable Real-Time Framework for Short-Term Freeway Travel Time Prediction
Online Contents | 2006
|Reliable Real-Time Framework for Short-Term Freeway Travel Time Prediction
British Library Online Contents | 2006
|Travel Time Prediction Model of Freeway Corridor Based on Real-Time Safety Reliability
DOAJ | 2020
|Freeway Short-Term Travel Time Prediction Based on Dynamic Tensor Completion
Transportation Research Record | 2019
|A space–time diurnal method for short-term freeway travel time prediction
Online Contents | 2014
|