Artificial Intelligence Based Detection Technologies Were Implemented to Improve Safety in Southern Nevada.
Nevada, United States
Leveraging Technology to Improve Roadway and Work Zone Safety in Nevada
Summary Information
Artificial Intelligence (AI) based platforms and real time data analyses have the ability to detect roadway crashes at a higher rate, and thereby facilitate faster validation which leads to reduced emergency response. The Regional Transportation Commission of Southern Nevada (RTC), together with the Nevada Highway Patrol (NHP) and Nevada DOT (NDOT) launched an AI-based platform in collaboration with a technology company in 2018 that allowed crash locations to be reported in real time. The pilot study was initiated on a six-mile, high-risk segment of I-15 in Nevada so that preventative efforts and patrols could be deployed. The AI platform aimed to reduce emergency response time during traffic crashes by eliminating the time required to dial for help using services like 311 and 911. Stemming from the positive findings from the initial pilot, the RTC decided to partner again with NHP and NDOT to expand its study area and deployed five additional Strategic Traffic Management Sites (STMS) in October 2019. In addition, the RTC started testing various technologies to detect work zones in real time, allowing them to broadcast the location of static barricade equipment—including cones, barrels, and signs—as well as construction vehicles and workers.
METHODOLOGY
The AI platform was used to analyze real-time data collected from a variety of sources including in-vehicle navigation devices, road-side traffic detectors, a smartphone navigation app and other telematics providers. With the help of AI technology, it became possible to combine real-time data with predictive analytics to help identify areas that were at a high-risk for collision, dangerous driving conditions and traffic congestion.
FINDINGS
- AI based road safety technology uncovered 20 percent more crashes than previously reported.
- The AI based detection program enabled the RTC and its law enforcement partners to reduce response time to crashes on average by nine to ten minutes. This also helped in preventing traffic jams and mitigating the likelihood of an injury leading to fatality.
- Understanding based on data instead of anecdotal references enabled emergency response institutions to deploy traffic patrols and devise abatement efforts more efficiently in order to prevent crashes, speeding and improve safety at high-risk locations.
- The results showed that in the 6-mile stretch of I-15 used as the initial pilot area, 91 percent of drivers traveling over the speed limit of 65 miles per hour reduced their speed below the limit, thereby reducing the number of primary crashes by 17 percent.
