SPECK SIGNED

Project "SPECK" data sheet

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 Partnership

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 Project objective

Traffic accidents involving Vulnerable Road Users (VRUs) remain one of the major causes of serious road traffic injuries and deaths worldwide and cost the EU an estimated €120 billion annually. Statistics show that more than one-third of VRU involved accidents take place on uncontrolled (zebra) crossings. A zebra crossing is a type of crossing where there is nothing to tell drivers when to stop and VRUs when to go. One of the potential measures to minimise such accidents is to improve communication between road users through the use of cooperative intelligent transport systems. These technologies can be integrated within infrastructures, and within the vehicles themselves, to create a sort of cyber-dialogue (V2X) between the driving machine and its surroundings. By equipping roadside infrastructure with communication devices and sensors, they can be used to monitor and predict traffic dynamics as well as warn road users when their trajectories are conflicting. However, the real-life technical requirements for such devices have remained more than challenging. Bercman has cracked this problem and developed an intelligent roadside unit which utilises narrow artificial intelligence (AI) algorithms coupled with sensor fusion techniques to predict and avoid situation-based traffic conflicts. It can increase VRU safety near uncontrolled crossings by employing warning signals and active safety measures to prevent accidents from ever happening. Our target group includes urban municipalities with more than 50 000 residents looking to modernise their infrastructure and gain smart city status. We address the global intelligent transport system market, estimated to reach over €46 billion by 2025. By scaling up rapidly, our objective is to reach €39 million in sales revenues by 2025. During the Phase-1 study, Bercman will conduct a comprehensive feasibility study that includes the commercialisation aspect of the innovation, and update its business plan accordingly.