Developments Targeting Hybrid Test Systems for HIL Testing
This paper compares the requirements for a generic and modular test architecture as well as trends and solutions to achieve architectures for hybrid test systems used in the aerospace industry with the requirements for the automotive industry.
Jump-Start Your Next Innovation – Join the RTMaps Forum
Are you exploring new ideas in advanced technologies? Are you looking for support to accelerate the development process for your innovations? Get answers to your questions from other RTMaps users by joining the new RTMaps Forum.
Blog: Smart Data Logging – Part I: Reducing Redundancy
Data logging in the automotive industry has been transitioning to a new form due to challenges arising from new E/E architectures, including ADAS/AD functions. In this blog post, we will give you some tips and recommendations on how you can optimize data logging and make it more efficient by using the right tools and methods.
Camera ECU Testing with Simulated Driving Scenarios
In autonomous vehicles, the electronic control unit (ECU) that interprets the camera’s environment images plays a key role. dSPACE offers a system for testing these camera ECUs, consisting of a dSPACE camera box, a dSPACE SCALEXIO simulator, and dSPACE software.
New dSPACE MicroAutoBox III variant with comprehensive range of bus and network interfaces
In the development of self-driving and electrically- powered cars, the connectivity requirements for in-vehicle prototyping systems are constantly growing. This is why dSPACE offers its MicroAutoBox III in-vehicle prototyping system with a high number of channels and an extended range of bus and network interfaces.
Blog: Ensuring Safety in the Era of Autonomous Driving: An Outlook on Data Replay HIL Stations and HIL Scalability
Establishing safe autonomous vehicles is an ongoing challenge requiring a cooperative effort by the automotive industry and legislative bodies. Data replay testing brings about new challenges at the HIL level as well as for the scalability of HIL clusters and efficient cloud backbone connectivity. In our newest blog post, our colleague Bassam Abdelghani explores these challenges and possible solutions.
Transferring the Complexity of the Real World to Simulation
dSPACE and understand.ai offer a new service that generates simulation scenarios from recorded measurement data used to validate functions for autonomous driving and driver assistance. With this offer, dSPACE supports its customers in the automotive industry in developing autonomous vehicles quickly and efficiently using realistic simulation.
