Technical Papers
Mar 23, 2015

Signal Progression Impacts on Transit Buses As Travel Time Probes

Publication: Journal of Transportation Engineering
Volume 141, Issue 8

Abstract

With the deployment Automatic Vehicle Location systems to monitor transit vehicles (and other fleet vehicles), there have been several efforts in recent years that seek to leverage these data to also obtain arterial travel times for the private vehicle population. The fleet vehicle data capture the traffic conditions, but they also capture behavior unique to the fleet, e.g., servicing passengers at a bus stop. There are several strategies used in conventional practice to eliminate the biases that occur in the vicinity of the bus stop. While investigating the benefits of using a perception sensor to identify ambient traffic conditions around the bus and correct for transit operations, the present work revealed that even a perfect correction for local conditions resulted in large deviation between the travel time measured from the bus and the actual travel time experienced by the surrounding private vehicles. This research uncovered a fundamental issue affecting almost all systems that use buses as arterial travel time probes: the fact that transit operations inevitably pull the bus out of the traffic signal progression no matter what corrections are made locally at the bus stop. The impact at subsequent traffic signals far downstream of a bus stop can be much larger than the local effects at the bus stop itself. This point is an important finding for any system that seeks to use transit vehicle probes to estimate the private vehicle travel times. To date the literature has made little consideration of the signal progression biases relative to the private vehicles that occur far beyond the bus stop. Finally, though the focus the present work is buses, the basic findings should apply to other fleets used as travel time probes as well if the given fleet behavior differs from the private automobiles.

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Go to Journal of Transportation Engineering
Journal of Transportation Engineering
Volume 141Issue 8August 2015

History

Received: Apr 4, 2014
Accepted: Jan 22, 2015
Published online: Mar 23, 2015
Published in print: Aug 1, 2015
Discussion open until: Aug 23, 2015

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Authors

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Douglas Thornton [email protected]
Cyber Embedded Engineer, Battelle Memorial Institute, 505 King Ave., Columbus, OH 43201. E-mail: [email protected]
Benjamin Coifman [email protected]
Associate Professor, Joint appointment with the Dept. of Civil, Environmental, and Geodetic Engineering and the Dept. of Electrical and Computer Engineering, Ohio State Univ., Hitchcock Hall 470, 2070 Neil Ave., Columbus, OH 43210 (corresponding author). E-mail: [email protected]

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