01658981

Component

Understanding driving behaviors is essential for improving safety and mobility of transportation systems. Data is usually collected via simulator-based studies or naturalistic driving studies. Those techniques allow for understanding relations between demographics, road conditions and safety. On the other hand, they are very costly and time consuming. Thanks to the smartphone data, the authors have an opportunity to substantially complement more traditional data collection techniques with data extracted from phone sensors, such as GPS, accelerometer gyroscope and camera. The authors developed statistical models that provided insight into driver behavior in the San Francisco metro area based on tens of thousands of driver logs. The authors used a novel data source to support their work. The authors used cell phone sensor data drawn from five hundred drivers in San Francisco to understand the speed of traffic across the city as well as the maneuvers of drivers in different areas. Specifically, the authors clustered drivers based on the way they drove around the city. The authors looked at driver norms by street and flagged driving behaviors that deviated from the norm.

This paper was sponsored by TRB committee ABJ30 Standing Committee on Urban Transportation Data and Information Systems.

18-02747

English

14p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; Maps; References (30)

Behavior; Data collection; Driving; Global Positioning System; Smartphones; Traffic flow; Traffic speed

San Francisco (California)

Highways; Safety and Human Factors

Transportation Research Board Annual Meeting 2018 Paper #18-02747

TRIS, TRB, ATRI

Jan 8 2018 10:39AM