Title

Impact of traffic diversion with ATIS on travelers' safety

Abstract

This study investigates the potential impact of diverting traffic from freeways under incident conditions to arterials with Advanced Traveler Information Systems (ATIS). Accident prediction models are developed for freeways and arterials. Traffic safety was calculated utilizing a simple network composed of a freeway and a parallel arterial and intended to represent a realistic traffic corridor in Orlando, Flor. It was found that the overall traffic safety (expressed as the probability that no accident is observed during a specific time period) was reduced on the network as a result of diverting traffic from the freeway to the arterial up to the critical percentage of vehicles equipped with ATIS which is sufficient to congest the parallel arterial. When the percentage of vehicles equipped with ATIS exceeds the critical fraction, (Pcr), safety remained fairly unchanged since traffic equilibrium has been reached. The safety improvement on the freeway was almost constant, though. A variety of incident scenarios were simulated using a traffic diversion model, and regression techniques were used to model the network safety as a function of network and incident parameters. It was found that the increase in percentage of vehicles equipped with ATIS may reduce the overall safety on the network when traffic is diverted from freeways to less safe arterials. Since the developed accident models were based on data from the Orlando area, the results of this study may not be applicable to other locations. It is important to conduct a similar type of analysis on a more complicated large scale network to see if the impact of ATIS on traffic safety reported in this paper can be generalized. © 1998 Elsevier Science Ltd. All rights reserved.

Publication Date

4-1-1998

Publication Title

Computers and Industrial Engineering

Volume

34

Issue

2-4

Number of Pages

547-558

Document Type

Article

Personal Identifier

scopus

Socpus ID

0032041370 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0032041370

This document is currently not available here.

Share

COinS