Potential of Low-Frequency Automated Vehicle Location Data for Monitoring and Control of Bus Performance

Abstract

The potential of low-frequency bus localization data for the monitoring and control of bus system performance is investigated in this paper. It is shown that data with a sampling rate as low as 1 min, when processed appropriately, can provide ample information. Accurate estimates of stop arrival and departure times are obtained; these estimates in turn allow the analysis of headways and travel times. A three-parameter gamma family of distributions is fitted for headways at the stops along a bus line. The evolution of the parameters demonstrates critical points on the line where bus bunching is significantly increased. Moreover, this analysis allows differentiating problems associated with varying passenger demand from uncertainties associated with traffic conditions. Furthermore it is shown that expected travel time and travel time variability can be calculated from low-frequency localization data. Finally, the way in which the results can be used to calibrate a simulation model that can test bus control strategies is presented. The methods are applied and validated to data obtained from Bus Route Number 1 in Boston, Massachusetts.