Robotaxis Will Start for Real in 2026: Europe’s Low‑Grip Safety Gap and the Easyrain Fix

Robotaxi3 2026

From Rain to Robotaxis: Why Europe’s 2026 Launch Needs a Low-Grip Safety Revolution

From London to Berlin, 2026 is shaping up as the year robotaxis move from pilot projects to paid, passenger‑carrying services. Policy momentum in the United Kingdom, an updated Level‑4 legal framework in Germany, and new industry alliances — notably Lyft teaming with Baidu — are setting the stage. Yet one unresolved hazard could limit scale and public trust: low‑grip conditions caused by heavy rain, standing water, snow and ice. This article reviews what’s coming in 2026, why adverse weather still defeats today’s autonomy stacks, and how Easyrain’s DAI, AIS and ERC systems can make robotaxis safer in Europe’s toughest climates.

2026: Europe’s Robotaxi Moment

The UK’s new legal framework for self‑driving services clears the way for paid operations as early as 2026, according to the government’s own roadmap (gov.uk). Germany, for its part, already permits Level‑4 operations in defined areas under its national law, enabling commercial services once operators secure approvals from federal and local authorities (BMDV).

Against that backdrop, ride‑hailing platforms are aligning with autonomy specialists. Lyft plans to deploy Baidu’s fully electric Apollo RT6 robotaxis in the UK and Germany starting in 2026 (pending regulatory sign‑off), building on its European footprint following the acquisition of FREENOW (Reuters; Lyft). Uber continues to expand AV integrations globally across multiple partners, while Waymo scales U.S. robotaxi service areas and Tesla explores ride‑hailing and autonomy initiatives.

Why Low‑Grip Is the Achilles’ Heel of Autonomy

Today’s autonomous driving stacks are excellent at perception and planning in fair weather. But they degrade when friction falls and visibility suffers. Cameras lose lane contrast under spray; lidar returns are attenuated and cluttered by rain and snow; radar is robust to precipitation but can lack spatial resolution. Critically, most stacks do not estimate available tire‑road friction in real time with the precision needed to adapt speed, following distance, and braking before grip collapses — especially on water‑logged surfaces that can trigger aquaplaning.

Independent testing underscores the gap. In controlled studies of production driver‑assistance systems, moderate to heavy rain significantly increased lane departures and collision rates, even at suburban speeds — a warning flag for any autonomy stack that inherits similar sensing and control assumptions (AAA). Regulators also continue to scrutinize AV performance in poor visibility and low‑adhesion scenarios, emphasizing that safe operation must extend beyond blue‑sky ODDs (NHTSA).

Europe’s climate compounds the challenge. Compared with Sun Belt U.S. cities, many European metros see frequent heavy rain, standing water, icy mornings, plowed‑snow residue, polished cobblestone, and road paint with variable micro‑texture — all of which reduce μ and confuse sensors. Without reliable prediction of low‑grip pockets ahead (puddles, black ice, slush), robotaxis risk late interventions, longer stopping distances, and emergency maneuvers on surfaces that may no longer support them.

A Practical Safety Path for 2026: Easyrain’s DAI + AIS + ERC

If Europe wants robotaxis that work year‑round, autonomy needs a dedicated low‑grip safety layer that predicts, prevents, and shares risk in real time. Easyrain’s technology suite provides that layer in three parts:

1) Predict the risk — DAI (Digital Advanced Information)

DAI is a family of predictive virtual sensors that infer road‑tire conditions from standard vehicle signals plus on‑board perception. It delivers an “early warning” μ‑risk map to the autonomy stack so it can adapt before grip collapses. Key modules include:

  • Aquaplaning: anticipates water‑film hazards in ruts and puddles to trigger speed and trajectory adaptations.
  • Snow & Ice: detects winter low‑μ conditions where cameras and lane markings are unreliable.
  • Ground: classifies surface types and micro‑texture to refine friction forecasts.
  • iTPMS & Tire Wear: monitor inflation and wear to keep tire performance within the ODD guardrails.
  • Wheel Misalignment: catches alignment issues that degrade stability and braking on slick surfaces.

2) Prevent the loss — AIS (Aquaplaning Intelligent Solution)

When heavy wet conditions appear, AIS provides an active safety intervention to defeat aquaplaning — a scenario where ABS/ESC cannot restore grip because the tire rides on a water film. AIS is engineered to remove the water film just ahead of the contact patch, restoring the tire‑road contact needed for steering and braking. For robotaxis, AIS adds a deterministic safeguard in the worst rain events that perception‑only stacks cannot reliably overcome.

3) Share and scale — ERC (Easyrain Cloud)

ERC aggregates vehicle‑borne low‑grip detections (from DAI/AIS and fleet signals) to build a live, privacy‑preserving risk map. This connected layer lets operators reroute fleets away from emerging aquaplaning hotspots, issue speed caps per road segment, and feed predictive analytics back into autonomy planning. As ERC density grows across cities, every robotaxi benefits from the first one that encounters the hazard.

How operators can integrate by 2026

  • Software‑first uplift: Integrate DAI virtual sensors into the ADS safety supervisor and motion planner to enable weather‑aware speed, headway and routing.
  • Hardware optioning: Specify AIS on vehicles destined for rain‑prone corridors and motorway ruts; validate actuation timing within the worst‑case puddle profiles in local ODDs.
  • Connected operations: Connect fleets to ERC so detections propagate city‑wide, improving predictions for all vehicles, all day.

Europe has the regulations and partnerships to start robotaxi services in 2026. To scale safely through the continent’s rain, slush and ice, operators need predictive low‑grip intelligence and an active countermeasure to aquaplaning. Easyrain’s DAI, AIS and ERC provide precisely that — a practical safety stack designed for real‑world Europe.

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Robotaxi Gaps on Low Grip: Environment and Real-World Constraints Set the Limits

Tesla autonomous vehicle struggling on snowy road

Navigating the Storm: How Robotaxis Can Conquer Low-Grip Conditions

The promise of autonomous vehicles, particularly robotaxis, has long captivated the automotive world. Imagine a future where urban mobility is seamless, efficient, and driver-free, available at the tap of an app. This vision is rapidly moving from concept to reality, with major players intensifying their global deployment efforts. However, a significant hurdle remains: the unpredictable and often treacherous nature of **robotaxi low grip weather** conditions. While impressive on clear, dry roads, current autonomous systems often falter when faced with rain, snow, or ice, raising critical questions about their safety and efficacy in such challenging environments.

The Robotaxi Revolution: A Global Race Towards Autonomy

The global robotaxi industry is currently in a pivotal phase, transitioning from limited pilot programs to full-scale commercialization. This shift is particularly evident in 2025, which is shaping up to be a key year for execution. Competition is fierce, with both U.S. and Chinese giants vying for market dominance.

U.S. companies like Waymo and Tesla typically adopt a technology-first, risk-averse strategy. Their approach prioritizes technical maturity and extensive safety validation, leading to a deliberately cautious pace of commercialization. As of 2025, Waymo operates in only four cities, and despite accumulating significant mileage, its commercialization progress has been slow. Tesla, for its part, has quietly initiated robotaxi testing in Austin with a pilot fleet and is preparing for an invitation-only rollout in San Francisco, with plans to expand to states like Nevada, Arizona, and Florida, pending regulatory approvals. This is according to industry analysis and news reports. Safety and compliance remain paramount, with regulatory agencies demanding thorough evaluations before granting wider approval.

In contrast, Chinese robotaxi firms are embracing a more aggressive, full-deployment mode. Companies like WeRide, Baidu’s Apollo Go, and Pony.ai are executing bold global expansion strategies, establishing a “three-front strategy” across the Middle East, Europe, and Southeast Asia. WeRide, for instance, launched the Middle East’s first fully autonomous Robotaxi fleet in Abu Dhabi and expanded into Dubai, even signing an MoU with Dubai’s Roads and Transport Authority (RTA) and Uber. This rapid expansion is underpinned by what analysts describe as globally competitive and mature technical solutions, coupled with strong cost advantages and deep operational experience in complex urban conditions. The industry is clearly moving towards a multipolar landscape, with 2025–2026 expected to be a crucial window for commercial scale-up.

Tesla Cybertruck Winter Testing in Robotaxi Low Grip Weather

The Achilles’ Heel: Robotaxi Low-Grip Conditions

Despite the rapid advancements, a critical vulnerability of autonomous vehicles, especially robotaxis, emerges when confronted with adverse weather. Rain, snow, and ice pose significant challenges that can render their sophisticated systems ineffective or, in some cases, even dangerous. More than 22% of crashes are weather-related, and severe weather amplifies the danger for autonomous vehicles. This is particularly true for **robotaxi low grip weather** scenarios.

Sensor Performance in Adverse Weather

The primary issue lies in how these conditions compromise sensor performance. Autonomous vehicles heavily rely on a suite of sensors, including cameras, LiDAR, and radar, to perceive their environment. This critical reliance is for their decision-making processes and understanding the environment. However, rain can obscure camera vision, scatter LiDAR beams, and cause radar signals to falter. A single raindrop on a camera lens can blur the field of view. Heavy rain can reduce image intensity and blur object edges, leading to a reported 20% to 65% decrease in object detection quality. Fog, though less frequent, can severely shrink vision. While radar is less susceptible, heavy snowfall can still decrease its effective range by up to 25%. These interferences directly impact the perception capabilities of autonomous driving systems, making it challenging for them to accurately identify lane markings, road signs, and other critical elements.

Real-World Limitations and Observations

Real-world observations underscore these limitations. Waymo vehicles, for example, have been documented pulling over during heavy rain, with reports indicating that thick rain can affect LiDAR performance. While some Waymo users report successful rides in heavy rain, suggesting continuous improvements, the general consensus is that snow, rain, and fog remain difficult for sensors to navigate. Companies like Mobileye also acknowledge that weather conditions such as fog, heavy rain, and heavy snow can adversely affect their system’s recognition and response capabilities. The challenge is not merely about reduced visibility; it’s about the fundamental degradation of the vehicle’s ability to “see” and interpret its surroundings, a problem that human drivers often compensate for intuitively.

Easyrain Solution for Robotaxi Low Grip Weather Safety

Beyond Perception: Robotaxi Control in Low-Grip Weather

Beyond the perception issues, maintaining vehicle control in low-grip conditions presents an even greater challenge. ADAS and autonomous setups can become unreliable or even dangerous in these scenarios. A prime example is aquaplaning, a phenomenon where a vehicle loses contact with the road surface due to a layer of water, leading to a complete loss of braking and steering control. This is difficult to predict using only visual or radar data, as the vehicle’s sensors may still “see” the road, but not “feel” the lack of grip underneath the tires.

The inability of autonomous systems to truly understand the friction level between tires and the road surface is a significant barrier to widespread adoption in all **robotaxi low grip weather** conditions. While cruise ships, for instance, employ sophisticated stabilization systems, advanced weather forecasting, and ballast tanks to navigate rough seas, autonomous vehicles on land require a different kind of “haptic sense” to adapt to rapidly changing road conditions. This proactive understanding of grip is essential for informed decisions, adjust their behavior, and ensure safety when the environment is far from perfect, as highlighted by weather-related challenges for self-driving cars.

A Paradigm Shift: Easyrain’s Ecosystem for Robotaxi Low-Grip Conditions Safety

Addressing these critical challenges requires innovative solutions that move beyond the limitations of current sensor technology. Easyrain, an automotive safety solutions company, is at the forefront of developing an ecosystem designed to give vehicles a “haptic sense” – the ability to feel the road and act preemptively, even when visibility is poor. Their approach combines virtual sensors with active safety systems and cloud connectivity to create a comprehensive solution for low-grip safety.

DAI – Digital Advanced Information: The Predictive Haptic Sense

Easyrain’s core innovation lies in its DAI platform, a software-based system of virtual sensors that provides comprehensive road and vehicle sensing capabilities without the need for additional physical hardware. This eliminates the costs and complexities associated with traditional sensors, offering OEMs a streamlined path to enhanced safety.

DAI’s virtual sensors leverage data from existing in-vehicle components (e.g., ABS, accelerometers) to detect various hazards in real-time, providing critical insights into road conditions. This includes:

  • Virtual Sensor Aquaplaning: Precisely identifies both partial and full aquaplaning events using a sophisticated three-level danger scheme, providing real-time alerts for either or both sides of the vehicle. This is a key part of Easyrain’s approach to low-grip safety and is detailed on the DAI Aquaplaning page. Its performance is consistent regardless of tire brand, pressure, or wear levels, and it operates autonomously without constant cloud connectivity.
  • Virtual Sensor Ground: Provides real-time information on the vehicle’s grip level, as part of DAI’s sensing capabilities.
  • Virtual Sensor Snow & Ice: Detects the presence of snow or ice on the road in real time, providing critical information for safe navigation in winter conditions. This is another vital component of Easyrain’s low-grip solutions, further explained on the DAI Snow & Ice page. This system can optimize Electronic Stability Control (ESC) logics and Adaptive Cruise Control (ACC) for snow and ice, and even facilitate V2X communication for road maintenance.
  • Virtual Sensor iTPMS (intelligent Tire Pressure Monitoring System): Eliminates the need for physical sensors by analyzing dynamic variations in vehicle behavior to accurately identify pressure drops, enhancing safety and efficiency. This is part of DAI’s virtual sensors, with more details on the iTPMS virtual sensor page.
  • Virtual Sensor Tire Wear: Continuously monitors tire wear with high precision (up to 0.8 mm), preventing blowouts or skidding, as part of Easyrain’s comprehensive safety solutions and DAI’s advanced sensing.
  • Virtual Sensor Wheel Misalignment: Detects any misalignment of the wheels, contributing to overall vehicle safety through DAI’s virtual sensors, with more details on the Wheel Misalignment virtual sensor page.

These virtual sensors provide predictive information to anticipate and prevent dangerous situations, which is crucial for autonomous navigation. DAI empowers OEMs to tailor ADAS and autonomous driving responses based on precise, real-time risk assessments, significantly enhancing ADAS performance and accuracy, particularly in challenging low-grip conditions. The platform is also remotely updatable via OTA updates, ensuring systems are always operating with the latest advancements.

AIS – Aquaplaning Intelligent Solution: The Active Solution Against Aquaplaning

Complementing the predictive capabilities of DAI is Easyrain’s AIS (Aquaplaning Intelligent Solution), the world’s first anti-aquaplaning system designed for both human-operated and autonomous vehicles. Unlike reactive systems, AIS is an active safety system that directly alters road conditions to prevent aquaplaning.

When the DAI Aquaplaning sensor detects a risk, it directly activates AIS. AIS then sprays high-pressure water jets from accumulators located ahead of the front tires. These jets break the water layer on the road, effectively removing excess water and restoring traction between the tire and the road surface, as detailed on the AIS product page. This proactive intervention yields remarkable safety improvements:

  • A measured 225% increase in lateral grip, boosting lateral acceleration from 2.0 m/s² to 4.5 m/s² at 80 km/h.
  • A 20% reduction in braking distance at motorway speeds on aquaplaning surfaces. For instance, at 120 km/h on 7 mm of water, the stopping distance decreased from 84 to 68 meters.

AIS enhances safety by maintaining contact between the tire and the road surface, ensuring optimal grip and enhancing stability and control. Its performance is independent of tire brand, model, or wear level, offering flexibility for vehicle manufacturers. This modular system works in synergy with existing ADAS, providing an additional layer of safety in critical aquaplaning scenarios.

Easyrain Cloud (ERC): Connected Mobility for Smarter Roads

The Easyrain ecosystem is further enhanced by the Easyrain Cloud (ERC), a platform that leverages unique data from Easyrain’s virtual sensors to provide unprecedented insights for enhancing automotive safety, improving proactive infrastructure management, and optimizing fleet operations.

ERC enables:

  • Real-time Aquaplaning Detection and Hazard Mapping: It uses data from equipped vehicles to create real-time hazard maps, identifying exact locations of low-grip risks such as black ice, snow, and potholes. This allows for immediate alerts to other vehicles and infrastructure management systems.
  • Predictive Risk Prevention: By analyzing data patterns, ERC can predict potentially dangerous environments and identify “noisy bands” that might impair sensor accuracy for ADAS and autonomous driving, enabling proactive risk mitigation.
  • Enhanced Fleet Management: The platform facilitates the efficient transmission of rich road condition data, allowing fleet operators to gain real-time insights, optimize routes to avoid low-grip areas, and improve vehicle efficiency.
  • Seamless Integration for Smart Infrastructure and V2X Communication: ERC provides a robust framework for sharing data between connected vehicles and smart infrastructure, building responsive transportation ecosystems that adapt to changing road conditions.
  • This also contributes to infrastructure maintenance, allowing authorities to address potential hazards before accidents occur.

The Easyrain Cloud transforms individual vehicle safety into a collective, data-driven approach to road safety, paving the way for smarter and more resilient mobility.

The Road Ahead: Conquering Robotaxi Low-Grip Conditions Challenges

The journey towards fully autonomous vehicles, particularly robotaxis, operating reliably in all conditions is complex. While significant strides have been made in controlled environments, the unpredictable nature of adverse weather remains a formidable challenge. Current systems, heavily reliant on visual and radar perception, struggle to interpret and react effectively to low-grip conditions, leading to safety concerns and limiting widespread deployment.

Easyrain’s comprehensive ecosystem, with its DAI virtual sensors providing a predictive “haptic sense” and the AIS actively mitigating aquaplaning, offers a compelling solution. By enabling vehicles to truly “feel” the road and proactively respond to hazardous conditions, Easyrain’s technology bridges a critical gap in autonomous driving capabilities. This integration of predictive software and active physical intervention, combined with cloud-based data sharing, promises to enhance safety, reliability, and ultimately, accelerate the widespread adoption of robotaxis, making the vision of all-weather autonomous mobility, even in **robotaxi low grip weather**, a tangible reality.

The Slippery Challenge of Autonomous Driving

tempesta di tuono sulla citta di notte

Autonomous vehicles are an incredible feat of engineering, promising to revolutionize how we travel. They rely on an intricate array of sensors—cameras, radar, and LiDAR—to see and understand the world around them. While effective under clear skies and on dry roads, these systems struggle when the environment is anything but perfect. This is a critical challenge, and it’s one that limits the real-world deployment of self-driving cars. In fact, when the weather turns, autonomous technology faces its toughest test.

Heavy rain, snow, and ice can severely compromise the performance of these vision-based systems. As a result, the vehicle’s ability to perceive its surroundings degrades significantly. This isn’t just a minor inconvenience; it’s a critical safety issue. A study from Politecnico di Milano, for example, highlights the limitations of current autonomous systems on wet or icy roads, underscoring the need for new solutions.

Strada piovosa al crepuscolo

Beyond Perception: The Real Grip on Safety

While seeing the road is essential, the even greater challenge lies in maintaining vehicle control in low-grip conditions. After all, traditional Advanced Driver Assistance Systems (ADAS) and current autonomous setups can become unreliable or even dangerous in these scenarios. Take aquaplaning, for example. This phenomenon is notoriously difficult to predict using only visual or radar data. The vehicle loses contact with the road surface, and with it, the ability to brake or steer.

This is where Easyrain comes in. The company is a leader in developing and licensing a suite of technologies to tackle these specific low-grip challenges head-on. The future of autonomous driving isn’t just about knowing what’s around the car; it’s about truly knowing what’s underneath its tires. Easyrain’s mission is to provide an haptic sense to vehicles, allowing them to feel the road and act preemptively, even when visibility is poor. This capability is essential for the widespread adoption of autonomous driving in all weather conditions.

Easyrain’s core technology, the Digital Advanced Information (DAI) platform, leverages a range of virtual sensors to provide vehicles with critical, real-time data on road conditions. These include:

  • Aquaplaning: A virtual sensor that detects the risk of aquaplaning by analyzing the relationship between tire and road surface.
  • Ground: Provides real-time information on the vehicle’s grip level.
  • Snow & Ice: Identifies the presence of snow and ice on the road.
  • iTPMS: An intelligent tire pressure monitoring system.
  • Tire Wear: Monitors the state of tire wear.
  • Wheel Misalignment: Detects any misalignment of the wheels.

These virtual sensors, combined with the physical Aquaplaning Intelligent Solution (AIS) and the Easyrain Cloud, create a comprehensive ecosystem for enhancing vehicle safety. The company even partnered with NVIDIA to further develop its DAI platform, a collaboration aimed at advancing safety in autonomous vehicles.

robotaxi in ambiente futuristico

The Road Ahead: Predictive and Adaptive Solutions

Enabling widespread autonomous adoption in adverse weather demands innovative solutions that move beyond the limitations of current sensor technology. Leading the way are next-generation systems that integrate multiple data sources with intelligent algorithms and multimodal neural networks.

These solutions use predictive and dynamic calibration software to detect and compensate for changing grip conditions. They can adapt the vehicle’s behavior in real-time, optimizing safety and performance even on the most challenging surfaces. This proactive approach to vehicle control is not just an upgrade; it is a fundamental requirement for the future of full vehicle automation. Ultimately, the ultimate challenge for autonomous vehicles today is not just to see the world, but to truly feel the road, ensuring reliability and safety when it matters most. Explore how Easyrain’s technology is addressing this critical issue.

 

 

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Autonomous driving and safety solutions for low-grip conditions
Progettazione e realizzazione di un sistema di guida autonoma in scala ridotta per il controllo di veicoli in condizioni di bassa aderenza
Easyrain Partners with NVIDIA to Boost Autonomous Driving Safety
Low-Grip Solutions: The Critical Challenge for Autonomous Driving

The Role of Virtual Sensors in the Future of Automotive Safety

easyrain automotive insight virtual sensors automotive safety01

As the automotive industry accelerates towards a future dominated by autonomous vehicles, safety remains paramount. A critical new frontier is emerging: **virtual sensors for automotive safety**. These innovative software-based solutions are poised to revolutionize the sector. They offer unprecedented accuracy, reliability, and adaptability, especially in challenging driving conditions. This article delves into the transformative role of virtual sensors. We explore their distinct advantages and their profound impact on enhancing vehicle safety systems.

Advantages of Virtual Sensors for Automotive Safety Over Traditional Hardware

Traditional automotive sensors are indispensable. However, they face inherent limitations. Physical components can be susceptible to environmental factors. Dirt, fog, rain, or snow can compromise their data. Furthermore, their accuracy can be affected by physical wear, calibration shifts, or electromagnetic interference. This is where virtual sensors offer a compelling alternative and powerful complement. They directly contribute to **virtual sensors for automotive safety** advancements.

Enhanced Data Interpretation and Reliability with Virtual Sensors

Virtual sensors are software algorithms. They derive information about the vehicle’s state or its environment. This data comes from existing on-board sensors (like wheel speed, steering angle, accelerometer, GPS, etc.). Their advantages are multifaceted. By fusing data from multiple sources, virtual sensors often infer parameters with greater precision. They use sophisticated algorithms, especially in ambiguous situations. They can “see” what physical sensors might miss. Environmental interference might cause misinterpretations. Research in this field, such as studies found on ResearchGate, consistently highlights these improvements.

Cost-Effectiveness and Robustness of Virtual Sensor Solutions

As software solutions, virtual sensors eliminate the need for additional physical hardware. This significantly reduces manufacturing costs, weight, and complexity during vehicle assembly. Their integration is primarily a software task. This allows for faster deployment and Over-The-Air (OTA) updates. Virtual sensors also provide an invaluable layer of redundancy. If a physical sensor fails or provides unreliable data, a virtual sensor can often continue to estimate critical parameters. This maintains safety functionality. This enhances the overall robustness of ADAS and autonomous driving systems. It’s a topic often discussed by organizations like SAE International.

Operating in “Unseen” Conditions: A Virtual Sensor Advantage

Virtual sensors can estimate parameters difficult or impossible for physical sensors to directly measure. Examples include road friction coefficients, tire grip limits, or subtle changes in road surface conditions like a thin film of water. This capability is vital for navigating low-grip scenarios safely. Unlike reactive physical sensors, virtual sensors can also be designed with predictive models. They anticipate potential hazards or changes in vehicle dynamics before they physically manifest.

Automotive virtual sensor technology

How Virtual Sensors Revolutionize Automotive Safety Systems

The ability of virtual sensors to process and interpret complex data streams fundamentally transforms how automotive safety systems operate. Their impact on accuracy and reliability is profound.

Precise Road Condition and Hazard Assessment for Enhanced Safety

Virtual sensors analyze minute variations in wheel speed, slip, and vehicle dynamics. They accurately detect changes in road surface conditions. This includes transitions from dry to wet asphalt, or the presence of ice or snow. This real-time, precise understanding of grip levels allows ADAS to adapt braking, acceleration, and steering inputs dynamically. This prevents loss of control. By continuously monitoring vehicle parameters and environmental cues, virtual sensors can identify precursors to dangerous situations. For instance, they can detect the early stages of hydroplaning. This happens before the driver (or even other physical sensors) perceives a problem. This triggers preventive actions.

Improving Vehicle Control and Autonomous Decision-Making with Virtual Sensors

With a more accurate real-time estimate of available grip, Electronic Stability Control (ESC) and Anti-lock Braking Systems (ABS) operate with greater precision. They optimize braking force and traction delivery to maximize safety and control. This reduces stopping distances in adverse conditions. For autonomous vehicles, highly accurate and reliable sensor data is non-negotiable. Virtual sensors provide critical “ground truth” information about the vehicle-road interaction. This enables autonomous driving systems to make safer, more informed decisions. This is crucial at higher speeds or in challenging environments. This is where the true potential of **virtual sensors for automotive safety** is realized.

Advanced virtual sensor display in car

Easyrain: Pioneering the Future of Automotive Safety with Virtual Sensors

At Easyrain, we are at the forefront of developing and integrating cutting-edge virtual sensor technologies. Our goal is to redefine **automotive safety with virtual sensors**. Our solutions are specifically engineered to address the most critical challenges in autonomous driving, particularly in low-grip and adverse weather conditions. Learn more about who we are at Easyrain.

Our Core Ecosystem: DAI Virtual Sensor Platform and AIS

Our ecosystem is built on two foundational pillars. Both heavily rely on the power of virtual sensors:

  • DAI (Digital Advanced Information) – The Virtual Sensor Platform: DAI is our revolutionary software platform of virtual sensors. It offers innovative safety and efficiency features. It provides the crucial “haptic sense” that complements traditional visual perception. This makes autonomous driving Level 3 and above on low grip truly viable. DAI’s sophisticated algorithms perform both road sensing (detecting Aquaplaning, Snow & Ice, and Irregular Ground conditions) and vehicle sensing (monitoring iTPMS, Wheel Misalignment, and Tire Wear). This hardware-free approach minimizes OEM integration effort. It also significantly enhances ADAS accuracy and optimization in dangerous driving conditions.
  • AIS (Aquaplaning Intelligent Solution) – The Active Prevention System: AIS is the world’s first and only active safety system. It’s specifically designed to eliminate aquaplaning risks. Powered by crucial data from our virtual sensors, AIS actively enhances grip. It sprays fluid jets ahead of the front tires. This prevents the loss of control that typically occurs on wet surfaces. This system is key to truly enhance ADAS systems for limited grip scenarios. It ensures the vehicle maintains control when it matters most.

Enhanced Fleet Management with ERC Cloud and Virtual Sensor Data

Furthermore, our ERC (Easyrain Cloud) leverages DAI (virtual sensor) data. It enables advanced predictive infrastructure maintenance and optimized fleet management. This allows for the sharing of critical hazard coordinates. It improves overall road safety innovations. It also solves a significant problem that still contributes to a large number of accidents on low-grip surfaces.

Unparalleled Safety Capabilities with Easyrain’s Virtual Sensors

The integration of Easyrain’s solutions allows carmakers to offer vehicles with unparalleled safety capabilities. Our patented technologies are designed for short integration times. They feature Over-The-Air (OTA) updates, ensuring continuous improvement. We believe our virtual sensor systems are pivotal. They make autonomous driving solutions truly viable and safe for widespread adoption. Ultimately, this contributes to a future with fewer accidents and fatalities on the roads. It sets new standards for **automotive safety with virtual sensors** globally. Achieving optimal **virtual sensors for automotive safety** remains our core mission.

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