01152855

Component

This paper presents a framework to estimate link travel times using available data from neighboring links. The spatial covariance between the travel times of nearby (neighbor) links in a network is used for this purpose. This can be a solution to the problem of partial network coverage caused by having a small sample of probe vehicles or a limited number of detectors. Two clues are used for real-time travel time estimation; historical travel time data and online travel time data from neighbor links. In the absence of online travel time data from neighbor links, one may rely on historical records only. However, in case the two types of data are available, a data fusion scheme should be applied to make use of the two clues. Real-life travel time data were collected and used to validate the proposed framework. The prediction accuracy was assessed using error measurements and the results were satisfactory. A microsimulation model for downtown Vancouver was developed using VISSIM to analyze the impact of probe vehicle sample size on the proposed methodology. Six market penetration levels were tested under five different demand scenarios. As expected, the estimation accuracy of the proposed method improved with higher market penetration levels. The methodology provided reasonable estimation even with small probe samples after introducing a threshold to filter outlier predictions.

01147878

10-0394

English

16p

2010

Transportation Research Board 89th Annual Meeting

DVD

Figures (6) ; References (25) ; Tables (1)

Data fusion; Highway operations; Microsimulation; Probe vehicles; Real time information; Traffic data; Traffic estimation; Travel time

Vancouver (Canada)

Data and Information Technology; Highways; Operations and Traffic Management; I73: Traffic Control

Transportation Research Board Annual Meeting 2010 Paper #10-0394

TRIS, TRB

Jan 25 2010 10:13AM