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At the 17th #AUTOSAR Open Conference (AOC) in Shanghai, #iSOFT (iSOFT Infrastructure Software Co., Ltd.) contributed its self-developed intelligent driving operating system as the global code baseline for AUTOSAR's Common Adaptive Platform Implementation (#CAPI) - a notable milestone in the evolution of the global smart vehicle industry. With 25...

201,147 просмотров • 1 месяц назад •via X (Twitter)

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Reckless Driver Arrested After Eluding Police Across Redmond; Drone Program Helps Track Vehicle Officers attempted to stop a vehicle in the early morning hours of April 23 after noticing it had no license plates. The driver accelerated well above the posted speed limit and failed to stop, ignoring emergency lights and sirens. The vehicle continued through Redmond, running red lights, making dangerous turns, and driving at high speeds. At one point, the driver returned toward an officer, flashing high beams in an apparent attempt to provoke a pursuit, and drove into oncoming traffic. Due to the reckless behavior and risk to the public, officers did not engage in a pursuit. Multiple drones were deployed remotely from docking locations throughout the city by a single Drone as First Responder (DFR) pilot, allowing officers to maintain continuous visual contact with the vehicle as it drove recklessly across Redmond. With assistance from aerial support, officers tracked the vehicle as it continued driving dangerously through the area, including SR-520 and downtown Redmond. Spike strips were successfully deployed, and the vehicle was later located at an apartment complex. Officers conducted a high-risk stop, and the driver was taken into custody without incident. The individual was arrested for eluding a police vehicle and further investigated for DUI. The driver was under the legal drinking age, and an open alcoholic beverage was found inside the vehicle. The individual was also driving with a suspended license. This type of reckless driving puts everyone at risk. Thank you to assisting units for their coordinated response.

RedmondWaPD

11,793 просмотров • 3 месяцев назад

Autonomous driving through very dense dynamic traffic, with extremely tight-complex-stochastic traffic-dynamics on sub-urban roads, connecting to an open ground, with absolutely zero traffic-rules. This is the most heavily cluttered environment where we have tested our #autonomousdriving technology, presenting many of the adversarial negotiation scenarios as well, throughout the autonomous navigation task. This demo was done at the Mata Baglamukhi Madir campus in the city of Nalkheda, in MP, India, and was done in the presence of heavy police forces deployed that day on the ground, as can be seen in our demo. Our autonomous vehicle starts from the temple with a generic open environment, with zero traffic rules, with very narrow corridors created out of barricades for vehicles movement by the security forces. In the corridor no two vehicles can pass through at the same time, and our vehicle was tasked with driving through this corridor, while negotiating its way from any traffic, two-wheelers, or pedestrians it faces, with dense presence of bikes and cars on either side, presenting a very challenging environment for #autonomousvehicles. The vehicle exits the open area, and then assumes generic dual lane navigation, avoiding both static and dynamic obstacles, before encountering a police check-post, where the vehicle is supposed to wait if the barricade is closed, and proceed if open. Upon exiting the checkpost, the vehicle negotiates a traffic-intersection with stochastic and adversarial driving behaviour of other vehicles on the road. Our vehicle continuously faced heavily cluttered traffic scene, where entities on the road can execute a random driving pattern, making the decision making task very challenging. We did the demo over a period of two days, successfully executing multiple (30+) trials in this setting. This demo was again a culmination of our prior works and demos: Kankali Kali Mata demo, on-roads, bidirectional negotiation capability on single lane roads, and open environment Level-5 negotiation capability as showcased in our Toll-Plaza demo. We again scaled up classical decision making and motion planning algorithmic framework, to adapt to such a level of density of obstacles on the road. This framework is further being scaled up with #reinforcementlearning and unsupervised #deeplearning at Swaayatt Robots. We will again do a demo in the month of June here, showcasing autonomously acquired skills to pave the way for Level-5 autonomous driving, and to solve the Level-4 autonomy problem by the end of 2024. #MachineLearning

Sanjeev Sharma

332,952 просмотров • 2 лет назад

BREAKING - EARLY EXCLUSIVE: XPENG Partners with Google Maps to Fuel Global Expansion The global autonomous driving landscape is becoming even more competitive! XPENG has announced a milestone global partnership with Google Maps, bringing a complete refresh of its in-car navigation and advanced driver assistance systems (ADAS). This major upgrade will come standard in the newly debuted XPENG L03. At the official launch event for the L03 in Munich, Germany, XPENG Chairman and CEO He Xiaopeng announced that the Next-Gen AI SUV Coupe will launch simultaneously in 64 countries and regions. XPENG is building its native in-car navigation system using Google Maps’ Auto SDK for vehicles outside China, which I’m sure MANY of you will be excited about. First in APAC to Adopt Google Maps Auto SDK XPENG is the first automaker from the APAC region to ship a vehicle with Google Maps Auto SDK integration. Instead of using your smartphone for basic screen mirroring, drivers get a native, custom in-car map application designed entirely by XPENG and powered directly by Google Maps. This integration brings: Real-time precision: Live traffic-aware guidance and highly accurate place search. Smart EV routing: Direct in-car EV energy estimation and trip planning. Native control: Full compatibility with voice control and multi-screen display transfer. Laying the Foundation for Global Autonomous Driving This partnership goes beyond finding directions. XPENG is officially utilizing Google Maps' in-vehicle Map Data Services to support its flagship full-scenario ADAS, Next Generation Pilot (NGP), as well as its foundational assist system, XPILOT ASSIST. To scale XPENG's advanced driving systems internationally, future applications of NGP (VLA 2.0) must rely on highly accurate map data and navigation maneuvers. Google Map Data Services will serve as the cornerstone for this phased global rollout, excluding markets in the Commonwealth of Independent States (CIS). Think of it as a fusion of XPENG’s technology with Google Maps Technology to get a more robust, intelligent, powerful, and safe autonomous driving experience. Overseas users of the XPENG L03 will be the very first to experience this upgraded, Google-powered native navigation system. My Thoughts I personally love and use Google Maps, so I’m glad to see this partnership, and I find it really neat how XPENG and Google Maps technology will work together. What are your thoughts and questions on XPENG integrating Google Maps natively to power its global self-driving tech? Let me know in the replies, and I will try to find the answers to your questions.

M. Brandon Lee | THIS IS TECH TODAY

65,878 просмотров • 28 дней назад