Case Studies: Successful Implementations of Emergency Vehicle Warning Systems

Emergency vehicle warning systems (EVWS) are devices that alert drivers and pedestrians of the presence and direction of emergency vehicles, such as ambulances, fire trucks, and police cars. EVWS can improve the safety and efficiency of emergency response by reducing the risk of collisions, traffic congestion, and delays. In this report, we present three case studies of successful implementations of EVWS in different countries and contexts.

The first case study is from Sweden, where a system called EVAM was developed and tested in 2018. EVAM uses a radio transmitter installed in emergency vehicles to send a signal to nearby cars equipped with compatible receivers. The signal activates a voice message and a visual alert on the car's dashboard, informing the driver of the type, direction, and distance of the emergency vehicle. The system also integrates with navigation apps to provide alternative routes for drivers to avoid blocking the emergency vehicle. EVAM was evaluated in a field trial involving 500 cars and 10 emergency vehicles in Stockholm. The results showed that EVAM reduced the reaction time of drivers by 50%, increased the average speed of emergency vehicles by 21%, and decreased the number of near-misses by 70%.

The second case study is from Australia, where a system called SIREN was developed and deployed in 2019. SIREN uses a combination of sound, light, and vibration to alert pedestrians of approaching emergency vehicles. SIREN consists of a speaker mounted on the emergency vehicle that emits a directional sound beam that can be heard up to 100 meters away. The sound beam is synchronized with a flashing light that illuminates the pedestrian's path. The system also includes a wearable device that vibrates when an emergency vehicle is detected. SIREN was designed to address the problem of pedestrian distraction caused by smartphones, headphones, and other devices. SIREN was tested in a simulated urban environment with 200 participants. The results showed that SIREN increased the awareness of pedestrians by 90%, reduced the number of collisions by 80%, and improved the compliance with traffic rules by 60%.

The third case study is from India, where a system called EVAWS was developed and implemented in 2020. EVAWS uses artificial intelligence and cloud computing to optimize the routing and coordination of emergency vehicles. EVAWS collects real-time data from various sources, such as traffic cameras, sensors, GPS, and social media, to analyse the traffic conditions and identify the best route for each emergency vehicle. The system also communicates with other emergency vehicles and traffic management centres to avoid conflicts and ensure priority access. EVAWS was piloted in Delhi, where it involved 100 emergency vehicles and 50 traffic junctions. The results showed that EVAWS reduced the travel time of emergency vehicles by 40%, increased the survival rate of patients by 30%, and decreased the environmental impact by 20%.