Provide alternative solutions

The road safety challenge lies within slowly moving unstable terrain in the vicinity of roads, railways and waterways that is not monitored at all. Dismantling of parts of the mass would result in severe damage to the infrastructure and vehicles/persons passing by.

Roadside workers are among the most exposed and least protected road users in Europe. Every day, road maintenance crews, recovery operators and temporary workers perform their duties only a few meters away from live traffic.

According to the Spanish Traffic Authority (DGT), seven roadside workers were killed on interurban roads in Spain in 2024: five tow-truck operators and two road maintenance and conservation workers. Similar risks exist across Europe wherever temporary roadworks, lane closures or roadside interventions take place.

Research by RACE-GOODYEAR and Ponle Freno-AXA has shown that a significant proportion of pedestrian fatalities on roads occur during signaling and roadside intervention activities, particularly in low-visibility conditions and on high-speed roads.

The underlying challenge is operational blindness. Temporary work zones have traditionally been protected through physical signage and manual reporting. Control centres often have limited real-time visibility of the exact location and status of roadside operations. If a cone is displaced, knocked over or removed, there is no automatic notification. Drivers only become aware of the hazard when they physically see the work zone, sometimes too late to react safely.

Our initiative addresses this challenge by transforming temporary roadside hazards into digital, real-time traffic events that can be shared instantly across the connected mobility ecosystem.

To warn road users of a danger on a road section, for instance following an accident, and to divert the traffic in a safe direction, traditionally wind-powered torches made of wax material are used. This solution implies some relevant road safety problems. First, exposure and risks for operators, on one side of being hit by vehicles while torches are placed on the road surface and turned on, on the other side of being wounded by open flames. Furthermore, damage of the asphalt on which torches are placed during use, compromising its useful time, and lack of practicality since they are made of fibrous materials and wax and can’t be extinguished even if no longer needed.
Every year road workers and emergency operators are injured or killed while deploying temporary warning devices in live traffic environments. Flash-Led was conceived to eliminate this exposure by enabling remote deployment of warning systems and significantly improving operator safety.
The present invention relates to a road signalling system aimed to substitute the traditional use of wind-powered torches, allowing an effective signalling of danger and/or obstruction and/or traffic channelling, ensuring the complete operators safety, avoiding infrastructure damages and, furthermore, informing road users through road navigation platforms. The solution includes n. 4 electric movable elements signalling with high visibility LEDs, remotely controlled by an operator from a plurality of possible schemes and arranged in an easily transportable container, which can reports the danger to users through platforms like Google/Waze etc.

Young and inexperienced drivers are a key target group for road safety because safe driving requires more than passing a formal test. It requires understanding rules, recognising risks, building long-term knowledge and applying that knowledge under pressure. Traditional theory education can be limited by fixed course times, uneven learner engagement, fragmented communication and a lack of real-time visibility into individual weaknesses. As a result, some learners only discover knowledge gaps shortly before the exam or after they enter traffic as licensed drivers. DriveHero addresses this challenge by moving the driving school process into a digital, data-supported and learner-centred environment. The platform helps learners prepare more consistently, at their own pace and with targeted support. Its AI assistant, Aurum, provides 24/7 guidance, while analytics and reporting help driving instructors identify where learners need additional explanation or practice. By making learning more personalised, transparent and accessible, DriveHero aims to improve theory knowledge, increase exam readiness and contribute to safer behaviour among new drivers.

ASPI acknowledges the need to build an integrated ecosystem encompassing infrastructure, vehicles, traffic management, and data governance.
On a motorway network, one of the most critical risks arises from the coexistence of live traffic and maintenance worksites, which exposes two groups of people to hazard every day: road users and site operators. Managing this overlap across an infrastructure of around 3,000 km calls for an innovative and systemic approach.
The “Advanced Traffic Mobility Management System” project therefore, stems from the clear goal of structurally reducing risk exposure by acting in an integrated manner on planning and information, such as:
optimizing the planning of roadworks by scheduling them in time windows with lower traffic volume, to reduce interference between traffic flows and operational activities; strengthening user information through advanced tools to anticipate traffic conditions and enable safer, more informed mobility choices.
The initiative is fully aligned with the EU’s Vision Zero-zero road deaths by 2050 and halving deaths and serious injuries by 2030.

Urban environments present significant safety challenges for commercial vehicle operators, particularly when vulnerable road users (VRUs) such as pedestrians and cyclists interact with large vehicles. While existing regulations and safety systems have improved protection, important gaps remain.

Most current side-detection systems are designed primarily to detect cyclists travelling at speed and focus on straight-line scenarios. However, many serious incidents occur when vehicles move off or turn, particularly involving slow-moving pedestrians, older people, children, and other vulnerable road users. Existing systems can also generate excessive false alarms, causing drivers to become desensitised to warnings and reducing their effectiveness.

Radar Predict Plus was developed to address these challenges. By combining radar technology with AI-powered camera analytics, the system accurately identifies vulnerable road users while filtering out irrelevant objects and minimising unnecessary alerts. It provides targeted warnings only when a genuine risk exists, helping drivers stay focused and respond effectively.

The initiative addresses a critical safety gap by improving protection in real-world operating conditions, particularly at low speeds and during manoeuvres where vulnerable road users are most at risk.