A Smartphone-Based Data Collection Method for Roadway Lighting measurements

Tuesday, June 10, 2025

4:45 PM – 6:00 PM MT

Primary Author(s)

Amin Golkarfard (he/him/his)

Graduate Research Assistant
University of Louisville
Louisville, KY, United States

Presenter(s)

Amin Golkarfard (he/him/his)

Graduate Research Assistant
University of Louisville
Louisville, KY, United States

Co-Author(s)

Sajjad Karimi

Graduate Research Assistant
University of Louisville
Louisville, KY, United States

Presenter(s)

Sajjad Karimi

Graduate Research Assistant
University of Louisville
Louisville, KY, United States

Co-Author(s)

Ganesh Rangali

Master's student
University of Louisville
Louisville, KY, United States
Robert Kluger, n/a

Associate professor
University of Louisville
Louisville, Kentucky, United States

Presenter(s)

Robert Kluger, n/a

Associate professor
University of Louisville
Louisville, Kentucky, United States

Submitter(s)

Sajjad Karimi

Graduate Research Assistant
University of Louisville
Louisville, KY, United States

Abstract: In several studies, adequate road lighting has been identified as an important factor in road safety at night. As a result of proper lighting, drivers are able to see obstacles, pedestrians, and other vehicles. To maintain and ensure the effectiveness of roadway lighting systems in this regard, luminance measurements are necessary. Data collection of luminance is traditionally performed manually with handheld light meters, which require personnel to collect luminance measurements at points along a road section. The process is labor intensive, time consuming, and dangerous for the personnel who perform it. This paper presents a smartphone-based data collection method that overcomes these limitations to collect roadway lighting data. In this proposed method, by calibrating a smartphone camera, an Opto-Electronic Conversion Function (OECF) is generated that facilitates the conversion of pixel values into accurate luminance measurements. By mounting a calibrated smartphone on a car, video of roadway lighting conditions is recorded and then analyzed to determine luminance values. With the help of GPS data collected by the smartphone, luminance values are mapped to their geographical locations. The proposed method allows for safe field personnel data collection over long distances, especially in locations where traditional methods are unsafe or impractical. As part of a collaboration with the Kentucky Transportation Cabinet, the system has been tested at two Louisville interchanges: I-64 at 22nd Street and I-264 at Bank Street, with results showing improved data collection speed and safety compared to manual methods.

Learning Objectives:

Attendees can expect to learn the following from this session:

Upon completion, participant will be able to develop a smartphone-based data collection method that leverages camera calibration and GPS synchronization for efficient and safe roadway lighting measurements.
Upon completion, participant will be able to establish an Opto-Electronic Conversion Function (OECF) curve for smartphone cameras to convert pixel intensity values into accurate luminance measurements.
Upon completion, participant will be able to effectively improve data collection speed and safety compared to traditional manual luminance measurement techniques.