Abhishek Jadav

By 2030, it is expected that nearly 70% of new vehicles will feature functions like lane departure warning and lane change assist. These Autonomous Driving Level 2 (ADL2) functions are already available in many mid-range and luxury vehicle segments. The level of automation is also likely to increase significantly in the low-price segment over the next few years. At the same time, it can be anticipated that Mobility-as-a-Service (MaaS) solutions based on ADL4 and ADL5 will then be introduced on a large scale in metropolises worldwide. 📰 Learn more in this article (in German): https://ow.ly/Un9Q30sBU5Z #FunctionalSafety #Automotive #AutonomousDriving HANSER automotive

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#Integration and #Testing the complex system in Software Defined Vehicles (#SDV) context is the biggest challenge to be solved by OEMs and Software suppliers!

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🛠️ We’re excited to announce that Paige Atkinson has published a new blog, Control Engineering – An Essential Guide to a Fast-Growing Specialty 🛠️. This blog dives into the critical importance of control engineering and guides potential candidates on how to transition into this exciting field of engineering.  The subjects we cover include skill set requirements, salary data, and job opportunities. Read it today: https://lnkd.in/ghHXsCxb #ControlEngineering #TechTrends #EngineeringJobs

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Elektrek reports: "Tesla releases update to remove steering wheel nag, shuts down sunglasses loophole," with improved camera-based #driver #monitoring. We need to call this update for what it is. Tesla's improvements to its #DMS amount to no more than polishing a turd. Elektrek continues: "This enhancement is available on vehicles equipped with a #cabincamera and only when the cabin camera has clear and continuous visibility of the driver’s eyes (e.g. the camera is not occluded, there is sufficient cabin illumination, and the driver is looking forward at the road ahead and not wearing sunglasses, a hat with a low brim, or other objects covering the eyes). A DMS needs to work at all times and under all lighting conditions to effectively perform the supervisory role for #FSD and #Autopilot. To not work in low light, or simply if the driver is wearing sunglasses, means it works unless it doesn't. That amounts to a hardware defect which cannot be resolved with changes to the software. This is the game Tesla is currently playing with #NHTSA. Coming regulatory changes mean Tesla is out of time for its woeful DMS. Tesla DMS came last in a recent #IIHS #automation #safeguards ranking (Ford Motor Company's DMS was ranked first) but coming harmonization of regulatory requirements across the U.S., Europe, and China through the 5-star #NCAP test will force Tesla's hand regarding properly functioning DMS in the near term. At a minimum, Tesla needs to implement DMS with 940nm optical path, add “Owl & Lizard” movement detection, work properly with sunglasses, and provide measures of #distraction and #drowsiness. Euro NCAP - For Safer Cars, Vans & Trucks is set to announce its 2026 DMS test protocols later this year and could add metrics for #cognitivedistraction and #impaired driving. Ironically it is Tesla FSD/Autopilot crashes that provide regulators with the data of what functions a DMS performing a supervisory role for partial automation most need to fulfil. NHTSA issued an #ANPRM for impaired driving in November. It is likely to follow that up with clear rulemaking for minimum DMS performance requirements in the next 12 months. The industry should not expect those requirement to be lame. FMVSS 127 for AEB was a major #safety advance. #Automakers should prepare now for the same step-change for DMS in the U.S. too. The latest edition of Semicast's report "#ADAS & #Automotive Vision-based Driver Monitoring Systems" is published. Significant segmentation of the DMS/OMS market is provided. This is summarized as follows:   - by movement detection into "Owl-only" and "Owl & Lizard" detection - by feature set - by processor type - by CMOS image sensor location - by CMOS image sensor resolution - by driver and occupant monitoring - by front-seat and whole-cabin monitoring   Message me for a copy of the sales brochure for the study. My inbox is open. https://lnkd.in/eWNvfQSm

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🌟 Humans, Robots and Autonomous Vehicles - at Auto UI 2024! 🌟 Exciting opportunity for my extended HRI and Autonomous Vehicle Interaction research community! Join me for the "Symbiotic - Workshop on Transferability between Human-Robot Interaction (HRI) and Autonomous Vehicle-Other Road Users Interactions Research" at the upcoming Auto UI 2024 conference, hosted at Stanford University. 🔍 Workshop Focus: Explore the intersections of interactions with Robots and Autonomous Vehicles (AVs), foster discussions and collaborations on the transferability of methodologies and insights between these fields. 🤖 Who Should Attend? Researchers and professionals in HRI and AV interaction domains—roboticists, AI specialists, UX designers, ethicists, policymakers, and forward-thinking industry innovators. 📝 Call for Contributions: We're looking for insights that could span across HRI and AV interaction realms: * Position papers and empirical studies on HRI and AV interaction. * Innovative models and frameworks  * Theoretical explorations and ethical paradigms.  Submissions can range from short work-in-progress to comprehensive research papers. 🎤 Features of the Workshop: Engaging panel discussions with experts. Opportunities to present your research. Collaborate on a multi-author paper summarizing the workshop's insights. 📅 Mark Your Calendars! Paper Submission Deadline: August 25 Organized by: Paul Schmitt (Torc Robotics) Swapna Joshi, PhD (Northeastern University) Bruce N. Walker (Georgia Tech) Azra Habibovic (Scania) For more details and to register, visit Automotive UI '24. Special thanks to MassRobotics for supporting this work!   Looking forward to seeing many of you there! #AutoUI2024 #HumanRobotInteraction #AutonomousVehicles #MassRobotics #InteractionResearch #ResearchCollaboration #Innovation #Technology https://lnkd.in/ee9EX8bK https://lnkd.in/ebcEQj3m

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Green Tiger Mobility, an innovative #startup, is revolutionizing India's two-wheeler market with hybrid technology. By retrofitting existing vehicles, they’re making strides in #EV adoption. As a beneficiary of the MathWorks Accelerator and Startup Programs, and with the help of MathWorks Consulting Services and tools like MATLAB, Simulink, and Stateflow, they've optimized their battery management system, achieving up to 70 km (43.5 miles) on a 1.8 kWh battery pack! 🌱🔋 Read the full story: https://spr.ly/6045itLmB

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Missed expectations on board. Rivian falls short of reaching the revenue highway as the automaker misses Q3 expectations and lowers earnings guidance. Its situation is a microcosm of the bigger problems facing the auto industry where companies are all struggling. It's losing less money, so that's a start. Producing vehicles isn't for the weak at heart, and the same can be said for Rivian. The company lost $39,130 for every vehicle that they delivered in Q3 2024, which isn't great until you understand losses used to be more than $125,000 per vehicle. Being small is tough especially in the EV business. Traditional automakers like General Motors, Ford and Stellantis have had their own share of issues related to supply chain disruptions, growing inventory and high interest rates. The arrival of 2025 models certainly isn't helping clear out the lot at the moment for many. Stellantis just recently announced 1,100 layoffs because of declining sales for its Jeep brand, while Volkswagen is closing plants in Germany for the first time ever. Small and nimble requires four-wheel drive. Smaller automakers like Rivian face greater challenges in the EV market due to their limited product lines. Even Tesla has had its problems. In contrast, established giants like GM and Ford have significant investments in EVs and are launching numerous models to appeal to a wider range of consumers. Where Rivian can standout or at least enhance its runway is through partnerships. Just last quarter, Volkswagen invested $1 billion in Rivian to develop technology to be used in future EVs. That type of investment provides the cash cushion the struggling automaker needs to weather a quarter with subpar sales https://cnb.cx/3UKz4GS #rivian #electricvehicles #automotiveindustry #supplychain

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Reposting for reach to fellow researchers. New data drop. More mileage. Added some granularity in the mileage data to provide more information on the distribution of driving within geographic regions (helps with ODD correction; check out this preprint: https://lnkd.in/e4KUuTJX).

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Could not believe it when I read the news about GM yesterday, which I have summarized below. General Motors (GM) is stepping back from its robotaxi plans, citing high costs and tough competition in the autonomous vehicle space. This shift comes after a rocky year for Cruise, GM’s self-driving unit. Cruise hit a major roadblock in 2023 when one of its vehicles injured a pedestrian, triggering a pause in operations, regulatory reviews, and a legal settlement. Despite resuming testing in California and striking a deal with Uber to deploy its robotaxis, GM has decided the financial and operational challenges are too steep right now. Instead, the company will combine Cruise’s team with GM’s other technical groups to focus on driver assistance tech, like its Super Cruise and Ultra Cruise systems, which are already being used in consumer vehicles. While this may seem like a step back, it’s also an opportunity for GM to double down on the technologies that are closer to market and can make driving safer for millions of people today. By focusing on practical solutions, GM could set itself up for long-term success in autonomous tech. All this being said, it is being reported that the decision has left many Cruise employees feeling blindsided and uncertain about their future. Clear communication and support from leadership will be crucial to maintaining morale and ensuring a smooth transition. What do you think—are incremental advancements like driver assistance systems the smarter play for now, or should companies keep pushing full steam ahead on robotaxis? #GM #Cruise #GeneralMotors #robotaxi #autonomousvehicles #ADAS

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Waymo driving on the wrong side of the road due to what appears to be a bad driving decision -- for the second video in a week. Wonder what their excuse will be this time! Last time it was a strained story that they were trying to be safe by moving into an oncoming traffic lane (with oncoming traffic) for well over a block a few days ago (pointer to that earlier video here; involves a swarm of unicycles: https://lnkd.in/eHFicWNg ) This video is a lot more straightforward. The problem with heavy-tail situations is it highlights a lack of "common sense" that is an inherent limitation to machine learning-based technology. Not a great look for a company trying to convince us that human drivers are terrible. Video source is apparently from TikTok. Or a deepfake -- or one from a year ago that just surfaced -- let's see what Waymo says. Happy to update with more info on date/source/provenance if we find out. Update: I got a note saying this was in Phoenix from an informed source, but not iron-clad confirmation. The previous video with crazy unicycle circumstances, no crash, and a laughable explanation is one thing. A second video makes Waymo's one-off edge case defense a lot less credible. Source: https://lnkd.in/eQJQxsap

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News about ADS - Jun 17, 2024: 😢 1) Waymo driverless vehicle contacts with a tele pole in an alley near 7th Avenue and Roosevelt Street 8 mph when pulling over in AZ on May 21, 2024 -> SW recall on Jun 12, 2024 https://lnkd.in/g9xQScah https://lnkd.in/gC_MYrE2 https://lnkd.in/g8zAxcQZ Root cause: "SW map" seems not a real root cause-> possible perception issue 2) Real robot driving a car - robot driver Misachi 😁 https://lnkd.in/ggpB_u3G 3) "NVIDIA Research Wins CVPR Autonomous Grand Challenge for End-to-End Driving" 👍 https://lnkd.in/ginE6CWF 4) Tier IV & Suzuki partner up for ADS 👍 https://lnkd.in/gTzvTrEJ 5) A sad story - but what happens to the driver who used the phone - too unresponsible 😔 - Tesla with FSD engaged from AP News https://lnkd.in/gCS9eXuZ

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Learn about the role of AI in vehicle design simulation and how it is tackling some of the major challenges that OEMs are facing in producing their vehicles as efficiently and cost-effectively as possible. https://bit.ly/3P1jseS

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🔧 In-Depth Exploration of the J1939 Protocol: Advanced Insights 🔧 For professionals entrenched in the complexities of vehicle network communications, the SAE J1939 protocol represents a sophisticated framework for high-performance, heavy-duty vehicle networks. Leveraging its foundation on the CAN bus, J1939 is critical for integrating and managing the plethora of electronic control units (ECUs) found in modern commercial and industrial vehicles. Technical Overview of J1939:- 1. CAN Bus Integration: J1939 builds upon the CAN protocol’s reliable, multi-master, and fault-tolerant communication framework. It extends CAN’s capabilities to support the high demands of heavy-duty applications with a focus on data integrity and network reliability. 2. Protocol Stack: The J1939 protocol stack consists of: - Physical Layer (CAN): Defines electrical and physical characteristics. - Data Link Layer (CAN): Manages message framing, error detection, and arbitration. - Network Layer (J1939): Manages message routing, priority, and error handling. - Application Layer (J1939): Defines parameter groups, message formats, and data standards specific to automotive applications. 3.ParameterGroup Numbers (PGNs): PGNs are integral to J1939, categorizing messages into predefined groups that streamline data exchange. Each PGN specifies the type of data being transmitted and its associated parameters, ensuring organized and efficient communication across the network. 4. Data Communication: - Message Frames: J1939 uses extended CAN frames to support larger payloads, accommodating complex data structures. - Transmission Protocols: Includes Broadcast and Request/Response modes, allowing for flexible data dissemination and retrieval. - Prioritization: Uses a priority scheme to manage message urgency and network bandwidth effectively, minimizing latency and ensuring critical data gets through. 5. Diagnostics and Maintenance: - Diagnostic Data: J1939 provides detailed diagnostic information, including fault codes and sensor data, essential for predictive maintenance and real-time troubleshooting. - Software Updates: Facilitates the updating of ECU firmware. 6. Extended Capabilities: - Application Profiles: Customizable for various applications, from engine control to transmission management and beyond. - Interoperability: Standardized communication ensures compatibility across different manufacturers and vehicle models, fostering a more integrated industry ecosystem. Why J1939 Matters: The protocol's robust architecture and extensive diagnostic capabilities make it indispensable for modern vehicle systems, driving innovations in performance monitoring, fault diagnostics, and fleet management. As vehicle systems become increasingly complex, J1939 remains a cornerstone of reliable and efficient communication in heavy-duty applications. #J1939 #AutomotiveEngineering #VehicleNetworking #CANBus #AdvancedDiagnostics #FleetManagement #AutomotiveTechnology

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