Netscribes’ Post

While I might not have a Ph.D. in cars, every day at Molex is a learning adventure that I wholeheartedly embrace. I may not be a car expert, but I'm passionate about what I do, absorbing knowledge and contributing to the exciting innovations in the automotive world. 🚗 🌐 Enter Zonal Architecture! It's like giving each part of the car its own smart hub, making things simpler, lighter, and more reliable. 📚 Check out Molex's whitepaper for more insights into the benefits and capabilities of Zonal Architecture. Exciting times are ahead in the world of automotive innovation! #PassionateLearner #MolexTeam

Zonal architecture is doing more than simply making room for new features — it's revolutionizing vehicle efficiency, maintenance and manufacturing.🚘 Buckle up and explore our latest blog, “Zonal Architecture vs. Domain Architecture” to learn how this vehicle design transformation is streamlining the overly complex systems of the past. The future of more intelligent, autonomous vehicles depends on zonal architecture.⚡ Read more about the impact of zonal👇 https://bit.ly/3HIvG8h #molex #zonalarchitecture

Future Mobility I read a great article by Christopher Mash of Ethernovia He was discussing the path to success for increased autonomy and eventually fully autonomous vehicles. He believe it lies in the in-vehicle network. I agree, one of the main aspects of achieving a fully autonomous vehicle will be the right vehicle architecture and network to support it. When I read the article, I was 30 minutes away from presenting the direction of vehicle architecture to my boss. He knows I have been working on it for a awhile and that I am passionate about the role we can play as material suppliers. I find myself getting caught up in terms like software defined vehicle (SDV) domain control unit (DCU) and system-on-chip (SoC). I would not say that he glazes over but he is more interested in the “why” of it all. Chris Mash was precise in his description, “massive amounts of data.”. You might not think about it but there is a significant amount of data being collected and processed. Currently, that data is controlled via an in-vehicle network. For this to work successfully as vehicles obtain more control over driving function and safety outcome, the network that is currently used will not work. The data must be controlled centrally. Edge computing at each sensor does not serve this end. “Instead, building and implementing a centralized architecture will streamline the aggregation of collected data into zonally located ECUs. “ “The typical passenger vehicle on the road today is running on a 100 Mbs or 1 Gbps backbone, but solutions are coming to market soon running at 2.5Gbs, 5Gbs up to 10 Gbps-cutting latency 10x, meaning a lot more data can be moved much quicker, giving autonomous ECUs the time they need to make the necessary decisions on a multitude of sensor data that keep passengers and pedestrians alike safe. Once these networks enabling high-speed data processing and ultra-low latency can be implemented into new-vehicle production, the road to full autonomy will become much clearer, much safer and much more reliable.” #futuremobility #data #vehiclearchitecture #autonomousvehicles #edgecomputing #centralizedcomputing

A piece of our joint effort has been published and now available for reading We talked about how considering the human-like behaviour of Connected Autnomous Vehicles (CAVs) can help us overcome the unavailability of data from CAVs during the calibration process, the 3 most anticipated driving behaviours of CAVs and how the coexistence of CAVs and human driving is possible from the beginning of the development process, ultimately leading us to sustainable transport. Thanking Constantinos Antoniou, Moeid Qurashi and Panagiotis Papantoniou for sharing their knowledge and contributing to the paper. My special thanks and gratitude go to Nima Dadash-Zadeh and Michalis Makridis for their lead in simulation and visualization. Available for cite: Dinar, Y.; Qurashi, M.; Papantoniou, P.; Antoniou, C. How Do Humanlike Behaviors of Connected Autonomous Vehicles Affect Traffic Conditions in Mixed Traffic? Sustainability 2024, 16, 2402. https://lnkd.in/gJ4pqHPq #transportationengineering

In this article, the authors specifically focus on how #millimeter-#wave (#mmWave) communications are being approached in vehicular standardization activities, #connected #and #autonomous #vehicles (#CAVs) use cases and deployment challenges in realizing the future fully connected settings. Finally, they also present a detailed performance assessment on mmWave-enabled #vehicle-#to-#vehicle (#V2V) cooperative perception as an example case study to show the impact of different configurations. ---- Muhammad Baqer Mollah, Honggang Wang, Mohammad Ataul Karim, (Julia) Hua Fang More details can be found at this link: https://lnkd.in/ep7PeAYm

New Invention Apollo White and the 7 Pillars In China, there's a company named Baidu that released an open source software named Apollo. The idea is, if you use the exact sensor configuration they give you, you can download their software components, and have access to fully autonomous vehicle. Because it's all open source, so is their architecture. Here it is: #selfdrivingcars #automation #newinnovation

In the latest issue of Automobil Elektronik (Hüthig Medien GmbH), our Senya Pertsel explores the crucial role of centralized processing in advancing autonomous driving technology, from the challenges faced by designers to the strides already made in the industry. His article “Meeting in the Middle – Centralized Processing for Vehicle Autonomy” discusses achieving low-level sensor fusion and accelerating the journey to L3 and L4 autonomy levels. Read the full article for free, which is available exclusively in German 🇩🇪: https://bit.ly/3T1ytjo Special thanks to Nicole Ahner for publishing our article! #Automotive #Automobil #Innovation #AutonomousVehicles #ADAS #LIDAR #AMBA #AIenvisioned #Ambarella

Another milestone for MS-IR LLC client Foresight Automotive (#nasdaq: FRSX), receiving patent approval in Japan for its “multi-spectral vehicular system for providing pre-collision alerts.”   The patented technology forms the core of Foresight's QuadSight® automotive vision system, offering unparalleled obstacle detection capabilities for semi-autonomous and autonomous vehicles. By combining visible-light and thermal imaging, QuadSight delivers robust object detection in all weather and lighting conditions, including darkness, rain, haze, fog, and glare.   This achievement underscores Foresight's commitment to pushing the boundaries of automotive innovation, particularly in Japan, a global leader in automotive technology.   For more information, click the link in the first comment.   Haim Siboni Eli Yoresh Yeela Wineberg-Shohat Oren Bar-on #autonomousdriving #ADAS #stereovision #3Dperception #innovation #Foresight #AutomotiveInnovation #PatentApproval

Researchers define a criticality metric that quantifies the level of reaction needed to avert a potential collision in junction areas, and validate its accuracy against near-miss data for merging scenarios. This criticality metric is promising for improvements in safety of SAE level 4 and 5 autonomous vehicles. "Criticality Metrics Study for Safety Evaluation of Merge Driving Scenarios, Using Near-Miss Video Data" by Takashi Imaseki, Fukashi Sugasawa, Eriko Kawakami, & Hiroshi Mouri (Tokyo University of Agriculture and Technology, Japan) Read the full #openaccess article of the SAE International Journal of Transportation Safety below, or from SAE Mobilus®: https://sae.to/3WgNIFO #safety #research #automotiveindustry