Investigate the Effectiveness of Using Bluetooth Low Energy (BLE) Technology to Trigger In-Vehicle Messages at Work Zones
Chen-Fu Liao, Senior Systems Engineer, Civil, Environmental and Geo-Engineering
- Max Donath, Professor, Mechanical Engineering
Project Summary:According to work zone injury and fatality data published by the Federal Highway Administration, in 2010 there were more than 87,600 crashes in work zones, resulting in 576 deaths and 37,476 injuries. More than 20,000 workers are injured in work zones each year, with 12 percent of those due to traffic incidents. The situation got worse in 2012; 609 out of 33,561 road fatalities were in work zones. Challenges to work zone safety and mobility are also exacerbated by the growing issue of distracted driving.
This project is one of three components of a work zone safety research effort investigating the effectiveness of using in-vehicle messages to calibrate drivers' understanding of the work zone in order to reduce risky behavior associated with distraction. This component is examining an inexpensive new technology based on Bluetooth Low Energy (BLE) tags that can be deployed in or ahead of work zones. These tags can trigger spoken and contextual messages in existing smartphones located in vehicles passing by the tag. Such messages can be updated remotely in real time, and as such may provide significantly improved awareness about dynamic conditions at the work zones such as awareness of workers on site, changing traffic conditions, or hazards in the environment.
Key technical issues this research will address are the maximum Bluetooth scanning rate on a smartphone, the Bluetooth and data communication latency, power consumption on smartphone and Bluetooth tags, repeatability of Bluetooth communication at high speed, the Bluetooth signal attenuation in different environments, and how such a smartphone app could be activated requiring no intervention by the driver.
- Start date: 04/2015
- Project Status: Completed
- Research Area: Transportation Safety and Traffic Flow