Autonomous driving technology is on the cusp of revolutionizing transportation, but several challenges must be addressed to realize its full potential.
Ensuring consumer safety is paramount, requiring extensive testing and robust safety protocols.
Feature Development Limitations
Current feature development methodology often overlooks the crucial corner case scenarios, focusing primarily on standard conditions, which limits the full capabilities of Level 3 autonomy and onwards.
Localization Issues
Localization presents another significant hurdle, heavily reliant on infrastructure and map data that are not updated frequently enough to reflect real-time changes.
Lack of Integrated Validation Approach
Validation of autonomous driving systems is fragmented, with individual sensors, features, and software tested separately, leading to potential safety risks and performance gaps in autonomous vehicles.
Limited AI Solutions Beyond Perception
The shortage of advanced AI and regulatory challenges hinder progress toward higher levels of autonomous driving.
Moreover, the regulatory environment poses its own set of hurdles, as laws and guidelines need to keep pace with technological innovations.
Addressing these intertwined issues is crucial to achieve higher autonomy level at scale.
Overcoming the challenges
Overcoming the challenges in the autonomous driving landscape demands a holistic approach that integrates advanced technology, adherence to regulatory standards, and a commitment to enhancing the end user experience.
Our goal
Our goal is to create and implement solutions that tackle these critical issues, empowering automakers to produce vehicles that are not only highly autonomous but also safe, reliable, and trusted by consumers.
KPIT, as a leading partner in automotive industry, is constantly striving to address the challenges in autonomous driving today.
Our robust simulation environments ensure feature development covers all driving scenarios, including corner cases. Our comprehensive validation frameworks combine various testing methodologies for continuous and thorough validation.
Additionally, our AI-driven decision-making solutions extend beyond perception, enhancing the intelligence and reliability of autonomous systems.
Through these innovations, we empower automakers to develop safe, reliable, and highly autonomous vehicles.
Einblicke
Künstliche Intelligenz (KI) treibt die szenariogesteuerte Validierung für das automatisierte Fahren an.
Ein Autokalibrierungssystem für Sensoren in autonomen Fahrzeugen
Architektur eines integrierten Park-in- und Park-out-Systems
Our offerings
System Engineering and Functional Safety
Software and platform integration
Integrated domain validation
ADAS Feature development
AI based perception and planning
Cloud and DevOps
Auswirkungen auf die Arbeit
Safety process for autonomous vehicle platform
KPIT owned the end-to-end safety process starting from concept to the safety validation.
System definition for various sub systems of level 4 AD vehicle
Define system definition & system requirement for L4 trucks
Feature Development & data driven validation for L2 & L3 Vehicle
Safety Process for Autonomous Vehicle Platform
Industry leading simulation, V&V, Feature Development
Validation partner to japanese OEM
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