Quantifying driver cell phone use at signalized intersections using software-defined radio

Abstract

Objective: This article outlines a data collection process that quantifies driver cell phone use using a software-defined radio (SDR) at a signalized intersection. Cell phone use while driving has been shown to be factor that increases the risk of a crash incident. Both operational and enforcement strategies can be applied at locations where high driver cell phone use is identified.

Methods: A baseline driver cell phone use observation was made at the intersection, where 9,699 vehicles were observed at the intersection of Carlton Road and State Route 31 (Pennington Road) in Ewing, New Jersey. An SDR cell phone detection device created as part of this study was then deployed at the same intersection to determine whether the SDR device could detect an active cell phone signal. The identification of vehicle cell phone activity using the SDR was conducted a sample of 4,000 vehicles. A visual observation, along with a motion detection camera, was made alongside the SDR to visually confirm cell phones use.

Results: Of the 4,000 vehicles sampled using the SDR cell phone detection device, 6.1% of the a.m. peak travel time and 7.6% of the p.m. peak travel time had an active cellular device. A concurrent visual field verification of driver cell phone use showed that approximately 57% (a.m. peak) and 67% (p.m. peak) of the SDR-detected cell phones were visually confirmed to be associated with distracted cell phone use.

Conclusions: Once characterized, the frequency of driver cell phone use can be used to justify changes to signal timing protocols. These adjustments could include extending the signal’s “all-red time” or holding “yellow time” longer in order to properly clear the intersection. These data can also be used to identify locations that may require more enforcement measures to dissuade driver cell phone use. Furthermore, the impact of anti–cell phone campaigns or new laws can be quantified by measuring before and after cell phone use in the near term rather than waiting for crash studies at intersections to be completed and analyzed.

Keywords:

• Distraction
• driver behavior
• ITS
• countermeasures

Additional information

Funding

The authors thank the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Foundation–Ministry of Education of Brazil for providing funding for our undergraduate researchers: Pedro Gilberto A. Furlanetto, Yasmine S. dos S. Silva, Liliane da Silva Costa, Ricardo H. F. Alves, Jhenifer Mesquita de Araujo, and Lucas J. Marini. The contents of this article reflect the views of the authors, who are responsible for the facts and the accuracy of the data presented herein, and do not necessarily reflect the official views or policies of the sponsoring organizations. These contents do not constitute a standard, specification, or regulation.