Edge data management for software-defined vehicle
Experts from NXP and ITTIA explain how to develop advanced applications using smart edge data management for software-defined vehicles.
Autonomous Vehicles
Advanced techniques for bridging AV data gaps – Applied Explainability and virtualized sensor simulation
Experts from Tensorleap, Cognata, and Foresight discuss ways to overcome the complexities of developing automotive AI, resolving model weaknesses, and pinpointing the data you need.
Driverless durability and misuse track testing for improved efficiency, safety and data quality
Experts from AB Dynamics explain how driving robots can be used instead of human drivers to improve the efficiency and outcomes of durability and misuse track testing.
UniMap: the new era of mapmaking
Steve Harding of HERE Technologies explains the impact of recent advancements in digital maps and their effects on the global industry.
How to drive the circular economy in the automotive sector
Experts from Ricardo discuss the key drivers for circularity and provide practical advice on deploying circular economy business models and applying life cycle assessment to inform decision-making.
Enhance your automotive simulation capabilities by leveraging the power of Ansys and AWS
John Baker of Ansys explains how to overcome engineering challenges using a new cloud platform that enables automotive customers to run simulations in the cloud easily.
The right solution at the right time: scalable driving simulators, from DESKTOP to DiM500
VI-grade’s Michael Hoffmann provides an in-depth overview of a scalable family of driving simulators, from the desktop-based simulators to the DiM500.
Navigating the complexities of automotive ISP tuning and image quality for vision-based perception systems
KPIT’s Radhesh Bhat explains the challenges of tuning the automotive ISP and how having a sophisticated ISP tuning tool environment helps achieve the desired image quality.
The road to zero prototypes: strategies and critical success factors for drastically decreasing the need for physical prototypes
VI-grade’s Michael Hoffmann explains how to make the product development process more human-centric using a simulation-driven approach.
Friction brakes for future mobility applications
Continental’s Sebastian Amirioui outlines the future of friction brakes and provides insight into innovative disc and drum brakes solutions for electric and autonomous vehicles.
Scaling hardware-in-the-loop validation to reduce ADAS/AD development time and costs
Dell Technologies and dSPACE experts describe how modular HiL/SiL systems and end-to-end data management can come together to offer the most flexible, complete system for simulation and validation.
mmWave radar design for automotive applications
Dr Marta Martínez Vázquez of Renesas presents the basics of mmWave radar for automotive applications and underline the challenges and trade-offs in radar design.
Engineering data science – driving the future of mobility
FEV’s Dr Umesh N. Hivarkar explains the role engineering data science will play in shaping the future of mobility.
Failure prediction with changing EV and AV mission profiles
NXP’s Robert Jin explains how System-on-Chip (SoC) health monitoring enables failure prediction and predictive maintenance to achieve better system availability.
Radars used in autonomous vehicles are changing rapidly. Are you software ready?
KPIT’s Santhana Raj discusses critical software approaches, architectures, and solutions for the new age of radars in autonomous vehicles.
Software-defined vehicle diagnostics – keeping the ‘software on wheels’ in motion
KPIT’s Stefan Zeppetzauer and Amit Shah present a comprehensive approach to electro-mechanical diagnostics coupled with the diagnostics of software running on HPCs within the software-defined vehicle.
Frontloading HMI development in the automotive engineering process
A panel of industry experts discuss how HMI challenges are being approached and handled today within the context of the modern automotive vehicle development process.
Making artificial intelligence and machine learning safe
NXP’s Andres Barrilado explains how AI and ML will make their way into automotive safety functions as we consider how to avoid systematic failures and define new problem statements around inference to provide safety-related functions.
Exploring behaviour AI: automotive applications
Humanising Autonomy’s Raunaq Bose and Pier Paolo Porta of semiconductor design company Ambarella discuss AI applications for the automotive and urban mobility industries.
Physical layer testing challenges of high-speed in-vehicle networks
Jae-Young Chang of Keysight Technologies examines the changes sweeping automotive in-vehicle technology and the accompanying signal integrity challenges.