Test and Evaluate a Bluetooth Based In-Vehicle Message System to Alert Motorists in Work Zones

Principal Investigator:

Chen-Fu Liao, Senior Systems Engineer, Mechanical Engineering

Project Summary:

The vehicle-to-infrastructure (V2I) technology collects traffic data from vehicles and then provides advisory information to the vehicles that informs the drivers of safety and mobility related conditions. The safe and efficient traffic flow in a work zone is a major concern for transportation agencies. In order to reduce risky behavior around work zones, we have developed a prototype system to investigate the feasibility of using in-vehicle messages to increase drivers' awareness of safety-critical and pertinent work zone information. Our previous effort focused on an inexpensive technology based on Bluetooth Low Energy (BLE) tags that can be deployed in or ahead of the work zone. A smartphone app was developed to trigger non-distracting, auditory-visual messages in a smartphone mounted in a vehicle within range of the BLE work zone tags. Messages associated with BLE tags around the work zone can be updated remotely in real time and as such may provide significantly improved situational awareness about dynamic conditions at work zones, such as awareness of workers on site, changing traffic conditions, or hazards in the environment. Our experiment results indicate that while travelling at 70 MPH, the smartphone app is able to successfully detect a long-range BLE tag placed over 400 feet away on a traffic barrel on a roadway shoulder. We propose to further refine our prototype system to be ready for deployment by, (1) incorporating the recommended in-vehicle message elements and user interface from a human factors study recently completed by the HumanFIRST Laboratory, (2) integrating a sustainable power source for deploying the BLE tag, and (3) testing the app on multiple smartphones to evaluate the automatic launch and Bluetooth scanning features. We will then implement the refined system in a work zone and collect data to evaluate and validate system performance over a long period and under different traffic conditions.

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