Increasing Traffic Safety with Real-Time Edge Analytics and 5G

Abstract

Despite advances in vehicle technology and road modernization, traffic accidents are a huge global issue, causing deaths and injuries, especially among pedestrians and cyclists. This often happens due to pedestrians and cyclists in drivers' blind spots or distractions delaying drivers' reactions. Therefore, timely warning drivers about critical situations is important to increase traffic safety. New edge computing and communication technologies have been proposed to reduce latency in critical IoT systems. However, state-of-the-art solutions either do not focus on traffic safety or do not consider low-latency requirements in this context. We propose InTraSafEd5G (Increasing Traffic Safety with Edge and 5G) to address these issues. InTraSafEd5G performs real-time edge analytics to detect critical situations and deliver early warnings to drivers. After describing our design choices, we provide a prototype implementation and evaluate its performance in a real-world setup. The evaluation shows that InTraSafEd5G can (i) detect critical situations in real-time and (ii) notify affected drivers in 108.73ms on average using 5G, which is within expected latency requirements of road safety IoT applications. Our solution shows a promising step towards increasing overall traffic safety and supporting decision-making in critical situations.