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

Area of Science:

• Traffic Engineering
• Transportation Safety
• Wireless Communication Technology

Background:

• Driver cell phone use is a significant factor contributing to increased crash risk.
• Identifying high-risk locations for driver distraction is crucial for implementing effective safety strategies.
• Current methods for quantifying in-vehicle cell phone use can be limited.

Purpose of the Study:

• To outline a novel data collection process for quantifying driver cell phone use at signalized intersections.
• To evaluate the efficacy of a software-defined radio (SDR) device in detecting active cell phone signals from vehicles.
• To establish a method for informing operational and enforcement strategies based on driver behavior.

Main Methods:

• A baseline observation of 9,699 vehicles at a specific intersection was conducted.
• A custom-built software-defined radio (SDR) device was deployed to detect active cell phone signals in a sample of 4,000 vehicles.
• Concurrent visual observation and motion detection cameras were used to confirm cell phone use and distraction.

Main Results:

• The SDR device detected active cellular devices in 6.1% of vehicles during the a.m. peak and 7.6% during the p.m. peak.
• Visual verification confirmed that 57% (a.m.) and 67% (p.m.) of SDR-detected phones were associated with actual driver distraction.
• The study demonstrated the SDR's capability to identify and quantify driver cell phone activity.

Conclusions:

• Quantified driver cell phone use data can justify traffic signal timing adjustments, such as extending all-red or yellow times.
• The data enables the identification of intersections requiring enhanced enforcement measures.
• This method allows for near-term quantification of the impact of safety campaigns and legislation, preceding crash data analysis.