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First published January 2004

Evaluation of Automated Work Zone Information Systems

Abstract

Motorists traveling through work zones are faced with both routine and unexpected tasks of driving coupled with additional distractions provided by the work zone. This can create conflicts despite significant applications of work zone traffic-control devices. When one or more through-traffic lanes are closed and traffic volumes exceed the capacity of merge points or of the reduced number of lanes, congestion can lead to the formation of queues, which result in delays and increased potential for crashes. An automated work zone information system (AWIS) may be implemented at a work zone to notify approaching motorists of changing traffic conditions, such as slowdowns or backups. Research was conducted at rural work zones in Arkansas on I-40, where two lanes of traffic in a direction were reduced to one lane. The objectives were to compare the displays of an AWIS with field observations of traffic conditions and to determine at what volume backups were forming. AWIS was compared with field observations for two traffic speeds, 30 and 50 mph. At 30 mph, the speed at which the system was programmed to identify a backup, AWIS concurred with the field observations 92% of the time. For a perceived backup speed of 50 mph, the system indicated a backup about 88% of the time. Backups formed at short-term flow rates as low as 800 to 900 passenger car equivalents per hour, which is lower than the capacities reported in the literature (1,100 to over 2,000 vehicles per hour).

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References

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Article first published: January 2004
Issue published: January 2004

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© 2004 National Academy of Sciences.
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Authors

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Melissa S. Tooley
Mack-Blackwell Rural Transportation Center, University of Arkansas, 4190 Bell Engineering Center, Fayetteville, AR 72701
J. L. Gattis
Mack-Blackwell Rural Transportation Center, University of Arkansas, 4190 Bell Engineering Center, Fayetteville, AR 72701
Rajeshkumar Janarthanan
Department of Civil Engineering, University of Arkansas, 4190 Bell Engineering Center, Fayetteville, AR 72701
Lynette K. Duncan
Center for Statistical Consulting, University of Arkansas, 301 Science-Engineering Building, Fayetteville, AR 72701

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