A STATISTICAL ANALYSIS OF THE RELIABILITY OF USING RGS VEHICLE PROBES AS ESTIMATORS OF DYNAMIC O-D DEPARTURE RATES

A considerable amount of the current IVHS traffic modeling research is focused on developing accurate and efficient dynamic traffic assignment models. Such models, while initially deployed off-line, are envisioned to be ultimately executed on-line based on realtime traffic data. Critical to such on-...

Full description

Saved in:
Bibliographic Details
Published in:IVHS journal 1994-01, Vol.2 (1), p.21-44
Main Authors: Hellinga, Bruce, Aerde, Michel Van
Format: Article
Language:English
Subjects:
origin-destination demands
route-guidance systems
statistical sampling
vehicle probes
Citations: Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A considerable amount of the current IVHS traffic modeling research is focused on developing accurate and efficient dynamic traffic assignment models. Such models, while initially deployed off-line, are envisioned to be ultimately executed on-line based on realtime traffic data. Critical to such on-line applications of dynamic traffic assignments is the availability of real-time O-D data with known levels of accuracy. The practical and theoretical limitations of synthetic O-D generation techniques have led to an exploration of how such data could be derived from RGS equipped vehicles which act as probes by transmitting their origin and intended trip destination when they initiate a trip. This paper presents the details of an analytical approach to determining estimates of the mean of the population O-D demands and the reliability of such estimates Equations that quantify the reliability of the O-D estimates are developed based on statistical sampling theory. These equations are developed for a general network, and are illustrated in detail for a specific example network consisting of an integrated arterial and freeway corridor. On the basis of the example network, it was found that even for a 20% level of market penetration, the average root-mean-square error between the estimated and actual O-D departure rates is 35% of the average actual O-D. In general, it can be concluded that for levels of market penetration that can be expected to be achieved in the initial stages of RGS implementation, O-D demands estimated solely on probe vehicle data will he of insufficient quality to be of significant operational benefit.
ISSN:1065-5123
DOI:10.1080/10248079408903813