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Article

Prioritizing Roadway Pavement Marking Maintenance Using Lane Keep Assist Sensor Data

1
Joint Transportation Research Program, College of Engineering, Lyles School of Civil Engineering, Purdue University, West Lafayette, IN 47907, USA
2
Ford Motor Company, MD 3135, 2101 Village Road Dearborn, Dearborn, MI 48121, USA
*
Author to whom correspondence should be addressed.
Sensors 2021, 21(18), 6014; https://doi.org/10.3390/s21186014
Submission received: 12 August 2021 / Revised: 2 September 2021 / Accepted: 3 September 2021 / Published: 8 September 2021
(This article belongs to the Special Issue Connected Vehicles in Intelligent Transportation Systems (ITS))

Abstract

There are over four million miles of roads in the United States, and the prioritization of locations to perform maintenance activities typically relies on human inspection or semi-automated dedicated vehicles. Pavement markings are used to delineate the boundaries of the lane the vehicle is driving within. These markings are also used by original equipment manufacturers (OEM) for implementing advanced safety features such as lane keep assist (LKA) and eventually autonomous operation. However, pavement markings deteriorate over time due to the fact of weather and wear from tires and snowplow operations. Furthermore, their performance varies depending upon lighting (day/night) as well as surface conditions (wet/dry). This paper presents a case study in Indiana where over 5000 miles of interstate were driven and LKA was used to classify pavement markings. Longitudinal comparisons between 2020 and 2021 showed that the percentage of lanes with both lines detected increased from 80.2% to 92.3%. This information can be used for various applications such as developing or updating standards for pavement marking materials (infrastructure), quantifying performance measures that can be used by automotive OEMs to warn drivers of potential problems with identifying pavement markings, and prioritizing agency pavement marking maintenance activities.
Keywords: pavement markings; lane detection; road maintenance; lane keep assist; LKA; advanced driver assistance systems; ADAS; connected and autonomous vehicles pavement markings; lane detection; road maintenance; lane keep assist; LKA; advanced driver assistance systems; ADAS; connected and autonomous vehicles

Share and Cite

MDPI and ACS Style

Mahlberg, J.A.; Sakhare, R.S.; Li, H.; Mathew, J.K.; Bullock, D.M.; Surnilla, G.C. Prioritizing Roadway Pavement Marking Maintenance Using Lane Keep Assist Sensor Data. Sensors 2021, 21, 6014. https://doi.org/10.3390/s21186014

AMA Style

Mahlberg JA, Sakhare RS, Li H, Mathew JK, Bullock DM, Surnilla GC. Prioritizing Roadway Pavement Marking Maintenance Using Lane Keep Assist Sensor Data. Sensors. 2021; 21(18):6014. https://doi.org/10.3390/s21186014

Chicago/Turabian Style

Mahlberg, Justin A., Rahul Suryakant Sakhare, Howell Li, Jijo K. Mathew, Darcy M. Bullock, and Gopi C. Surnilla. 2021. "Prioritizing Roadway Pavement Marking Maintenance Using Lane Keep Assist Sensor Data" Sensors 21, no. 18: 6014. https://doi.org/10.3390/s21186014

APA Style

Mahlberg, J. A., Sakhare, R. S., Li, H., Mathew, J. K., Bullock, D. M., & Surnilla, G. C. (2021). Prioritizing Roadway Pavement Marking Maintenance Using Lane Keep Assist Sensor Data. Sensors, 21(18), 6014. https://doi.org/10.3390/s21186014

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