SBIR Phase I: SmartNet Applications for Mobility and Safety (SAMS)

This Small Business Innovation Research (SBIR) Phase I project will pursue an innovation that can dramatically improve traffic mobility and safety. This study is based on an open wireless sensor network platform that supports many sensing modes, and time-stamps all measurements. The sensing modalities include magnetic sensors that detect vehicles; new micro-radar sensors that detect bicycles, pedestrians and parked vehicles; GPS-based sensors that locate vehicles; conflict monitoring cards that measure traffic signal phase; and environmental sensors that can be added as they become cheaper. The proposed concept can be incrementally deployed to augment sensing capability and coverage area; it can be deployed over all major arterials in a city within one month. Being time-synchronous, different data sources can be combined to develop innovative applications about intersection safety, arterial delay and emissions, signal coordination, transit priority, vehicle location, and parking availability. Today, this information is unavailable (e.g. intersection safety) or needs special purpose systems (e.g. pedestrian presence. The broader impact/commercial potential of this project will benefit city administrations. Poor intersection control causes 5 to 10 percent of traffic delay on major roads. Congestion costs the peak-period traveler 38 hours of travel time and 26 gallons of fuel annually. 36 percent of crashes are intersection-related. Faced with this high cost of poor road management, city administrations are looking to analyze data to efficiently deliver transportation services. This "analytics" approach brings rich dividends through improved mobility and safety. However, collecting the data to implement this approach today is prohibitively expensive. Existing intersection safety products are primarily Red Light Enforcement (RLE) cameras. RLE is controversial. An Insurance Institute of Highway Safety (IIHS) report states: More than 25 percent of drivers oppose red light cameras; they believe that cameras can make mistakes, are used to generate revenue for governments rather than for safety; lead to more crashes because drivers speed up to beat the red light or stop suddenly and are rear-ended; or invade privacy.