Performance Analysis and Metrics Development for Roadway Striping Operation Using Telematics Technology

Abstract

This study utilized telematics technology to automatically collect data that could then be used to improve striping performance without the need for additional staff or equipment. This paper presents the telematics data collection and implementation in two areas: (1) providing performance analyses using telematics data and (2) developing performance metrics for future performance measurement. Striping is a continuous maintenance operation for all roadway O&M managers and it requires substantial resources and financial investment if good or excellent striping condition is to be maintained. Striping mileage per day was used to represent productivity in this study. The average striping mileage in 2012 comprised only 15–25% of the total average driving miles per day. The utilization analysis indicated that centerline trucks were utilized at significantly higher levels than edgeline trucks, although the overall utilization ratio only ranged between 20 and 30%. Three levels of productivity metrics were developed from normal distribution probability density functions and appropriate parameters obtained from the Monte Carlo simulation results. Measured in terms of striping miles per day, low productivity was taken to be any value less than or equal to 30%, medium productivity any value more than 30% and less than or equal to 70%, and high productivity any value over 70%. As a result of the study, performance analyses revealed that there was sufficient room for improvement and several recommendations were made. Multiple operational scenarios reveal that productivity and utilization can be increased up to 47 percent while eliminating several striping trucks. Performance metrics were provided using Monte Carlo and triangular distribution.