The six-month trial is a joint initiative between the Royal Automobile Club of Queensland (RACQ) and Redland City Council, with the support of Council of Mayors SEQ. It is operating on a 3.8 kilometre fixed loop route, co-ordinated with ferry arrivals where passengers can hop on or off at one of eight bus stops along the route.

EasyMile has announced that its autonomous vehicle on Karragarra Island in Queensland is the first-ever driverless service to connect with a public ferry terminal.

This announcement comes just months after Australia’s Redland City Council and Queensland, Australia’s peak motoring body, the Royal Automobile Club of Queensland (RACQ), announced Karragarra Island on Redlands Coast as the first location in Queensland to test a driverless bus. 

A joint initiative between RACQ and Redland City Council, with the support of Council of Mayors SEQ, the six-month trial is taking place on a 3.8 kilometer fixed loop route, and is coordinating with ferry arrivals where passengers can hop on or off at one of eight bus stops along the route.

The six-month trial is a joint initiative between the Royal Automobile Club of Queensland (RACQ) and Redland City Council, with the support of Council of Mayors SEQ. It is operating on a 3.8 kilometre fixed loop route, co-ordinated with ferry arrivals where passengers can hop on or off at one of eight bus stops along the route.

The collaboration with NIO builds on Mobileye’s AV leadership and its ability to deliver a new era of transportation for drivers and passengers in China and beyond. With NIO serving as its manufacturing partner, Mobileye’s self-driving system will be accessible to mass markets, further extending the reach of its AV innovation to automotive customers on a global scale. The agreement also marks the first large-scale automaker partner supplying vehicles to Mobileye, as the company builds a global commercial robotaxi fleet that adapts to the mobility needs of the 21st century. The service would help reduce pollution and congestion, while enhancing safety and transit quality, in urban settings around the world.

For NIO, supporting the production and integration of Mobileye’s self-driving system aligns with its mission to provide premium, smart electric vehicles that redefine the user experience for drivers. By joining with Mobileye, NIO aims to maintain its leading-edge position in the premium electric vehicle market – with cars that deliver enhanced safety and functionality, powered by advanced driver-assistance systems technologies and L4 autonomy.

How It Works: Under the planned collaboration, Mobileye will provide NIO with the design of the self-driving system building on the Mobileye AV Series, a L4 AV kit comprised of the Mobileye EyeQ system-on-chip, hardware, driving policy, safety software and mapping solution. NIO will take on the automotive-grade engineering, integration and mass-production of Mobileye’s system for both consumer automotive markets and for Mobileye’s mobility-as-a-service (MaaS) applications. In addition to integrating the self-driving system into its vehicle lines, NIO will develop a specially configured variant of electric AVs that Mobileye will use as robotaxis, deployed for ride-hailing services in global markets.

The Mobileye AV Series: The L4 AV kit is a driverless technology solution designed to be integrated in vehicles with autonomous capabilities that help effectively minimize automobile accidents.

Hardware: Mobileye’s AV Series offers necessary hardware to enable full autonomy in vehicles, including cameras, radars, lidars, cables, modem, GPS and additional mechanical components, all powered by the 5th generation EyeQ system-on-chip. It is purpose-built for low cost and low-power consumption, specifically for autonomous driving with premium deep learning and performance efficiency.

Driving policy: Mobileye’s proprietary reinforcement learning algorithms enable human-like driving skills for vehicle systems, which pair with the superhuman sight and reaction times possible through the technology’s sensing and computing platforms. Channeling Mobileye’s driving policy technology, vehicles equipped with the AV kit are able to negotiate with other human-driven vehicles on the road in complex situations.

Safety software: Mobileye’s driving policy is complemented by its Responsibility-Sensitive Safety (RSS) model, which helps ensure an autonomous vehicle will make safe decisions. RSS is an open and transparent formal model that provides safety parameters for AV decision-making, formalizing common sense human-centered concepts of what it means to drive safely. While the planning behind driving policy gets vehicles from Point A to Point B, RSS helps keep them safe along the way.

Toyota Research Institute (TRI) announced that its Platform 4 (P4) automated driving test vehicle will be available for public demonstration rides next summer in Tokyo. Offered from July to September 2020, the P4 will demonstrate Toyota’s “Chauffeur” SAE Level-4 capabilities in a specific “mobility as a service” (MaaS) driving environment.

The P4 experience will take place in Tokyo’s Odaiba district, a busy and often congested waterfront subcenter. Odaiba’s complex environment of pedestrians, vehicle traffic, diverse road infrastructure and tall glass buildings provide a challenging setting in which to demonstrate the capabilities of Toyota’s automated driving technology. The public will be invited to register for the experience, and individuals will be selected to participate. In accordance with Japanese law, a Safety Driver will be present during the experience.

TRI has been testing the P4 in the United States at its Ottawa Lake, Mich. closed-course test facility. There, TRI replicated Odaiba’s most challenging infrastructure characteristics and driving scenarios for which the P4 will have to navigate autonomously. Further testing of P4 software is being conducted on public roads in Odaiba and around TRI’s Ann Arbor, Mich. and Los Altos, Calif. research offices.

Introduced at CES 2019, the P4 test vehicle is based on the fifth-generation Lexus LS sedan. It is being used in TRI’s research and development of both “Toyota GuardianTM” active safety and “Chauffeur” automated driving applications.

The two companies will collaborate on new lidar system supply by integrating Velodyne’s latest lidar sensors with Hyundai Mobis’ cognitive software. Velodyne has the largest share of the global lidar market and exceeds the latest high lidar requirements of global automakers. In this lidar with high specifications, Hyundai Mobis will develop and integrate its own cognitive software. This software will process the outside vehicle environment data gathered by lidar sensors which means that it would recognize and analyze moving or stationary objects, along with road systems such as traffic sign information.

Hyundai Mobis and Velodyne will commercialize their first lidar system for level 3 autonomous driving in 2021 by this partnership. The two companies will mark the start by supplying the system to the Asian market and will gradually expand to automakers in North America and Europe.

With this lidar system, Hyundai Mobis will finalize its sensor technology line up for autonomous driving of level 3 and above, where the main driving force is shifted from human driver to an independent car system. It has successfully developed a short-range radar last year and will secure deep learning-based camera and high-performance radar technology by next year.

With global developments that are characterized by higher demand for transportation, increasingly congested roads and major environmental challenges, the industry needs to provide transport solutions that are safer, have a lower environmental impact and are more efficient.

Autonomous transport solutions, based on self-driving and connectivity technologies are well-suited for applications where there is a need to move large volumes of goods and material on pre-defined routes, in repetitive flows. In such situations, autonomous transport solutions can create value for customers by contributing to improved flexibility, delivery precision and productivity.

The Volvo Group has already demonstrated a number of different autonomous transport solutions.  

In the Electric Site project, material handling in a quarry was automated and electrified. The result was a safer working environment and a reduction of operator costs by 40 percent and of carbon dioxide emissions by 98 percent.

At the Brønnøy Kalk mine in Norway, autonomous Volvo FH trucks will be used in commercial operation to transport limestone along a five-kilometer stretch.

Another pioneering initiative is the self-driving, connected and electric vehicle Vera. In its first assignment Vera will form part of an integrated solution to transport goods from a logistics center to a port terminal in Gothenburg, Sweden.

Volvo Autonomous Solutions will constitute a new business area as of January 1, 2020. Its financial results will be reported as part of the Truck segment. The recruitment process for the position as Head of Volvo Autonomous Solutions has commenced.

REE announced that its ultra-modular, advanced, corner module for electric and autonomous vehicles (EVs and AVs) will be displayed alongside a global OEM partner at the 46th Tokyo Motor Show. Details of the OEM partnership will be revealed on October 23^rd, the first press day of the event. Visitors at this year’s exhibition will see product demos of REE’s corner module technology that is poised to upend automotive manufacturing.

REE brings unmatched modularity and efficiency to the electric-mobility landscape. The company has redesigned all drive vehicle components that are typically found on the chassis, including the motor, steering, suspension, drivetrain, data unit for AI preventative maintenance, brake, thermal systems, and electronics, and engineered them into a compact area of the wheel arches – known as corner modules.

REE’s corner module technology not only brings greater efficiency to the mobility of people and goods, but it will enable mobility players to provide advanced services never before possible, reshaping the future of e-mobility. REE’s modular technology is designed from its core to support the diverse range of shapes, services and requirements the new e-mobility world brings.

The super-efficient space allowed by REE’s technology not only enables newfound vehicle design and configuration freedoms, it also allows for more batteries, safety technology, and storage to be integrated seamlessly. The reduction in weight means lower running costs and reduced environmental footprint. And because the technology is modular, maintenance is simplified and fast. REE’s solution works with any electric vehicle to bring new driving value and efficiency as well as reduced vehicle development and maintenance costs to OEMs and drivers alike.

France is committed to the development of autonomous vehicles with a strong national strategy in which stakeholders in the sector, and national and local authorities are involved.
To make France a leading country for the development of the autonomous vehicle, an innovative program of experimentations supported par the government, EVRA,  is in progress.

Groupe Renault participates in this program via a consortium of the PFA, the French automotive platform, with experiments of electric and autonomous on-demand vehicles in Rouen in conjunction with the Rouen Normandy Metropolitan Area and the Normandy Region; and on the Paris-Saclay urban campus with the Paris Region (Région Île-de-France) and Île-de-France Mobilités (Public Transport Authority of Paris Region).

In this context and following the signing in June 2019 of an exclusive agreement between Groupe Renault and Nissan with Waymo on autonomous mobility services in France and Japan, the Paris Region and Groupe Renault will explore the implementation of an autonomous mobility service between Roissy-Charles de Gaulle Airport and La Défense

Netradyne uses artificial intelligence (AI) vision-based dashcam devices to monitor safety performance of fleet vehicles. Netradyne’s system may also crowdsource road and driving behavior metadata.

With this agreement, Hyundai and Netradyne will collaborate to utilize the road and driving behavior data collected by Netradyne to support HD mapping and map updates for Hyundai’s development of future L3+ ADAS and AD features.

The costs associated with outfitting traditional mobile mapping system (MMS) vehicles, which are currently employed for HD mapping, make it challenging for many OEMs to place enough MMS vehicles on the road to provide the necessary frequency of HD mapping updates. However, Netradyne’s devices are more cost-efficient and are currently equipped to numerous vehicle fleets throughout the country, potentially enabling more frequent, high quality HD map updates.

Netradyne has already captured and analyzed over 1 million unique miles of the 2.7 million total miles of paved roads in the United States. This data includes numerous passes over the same roads to provide deeper insights into how driving and road different conditions may change throughout the year.

In total, Netradyne has analyzed more than 350 million miles of road data. Each of these 350+ million miles has been analyzed with AI and collected by professional drivers.

But delivering autonomous vehicles is not something that one company can do on its own – it requires collaboration at an industry level. This morning at Arm TechCon in San Jose, I had the pleasure of announcing a significant new initiative that takes us one step closer to this goal: Arm is a founding member of the Autonomous Vehicle Computing Consortium (AVCC) a new group of industry leaders focused on accelerating the delivery of safer and affordable autonomous vehicles at scale. Members of the AVCC include General Motors, Toyota, DENSO, Continental, Bosch, NXP and Nvidia.

The AVCC: Accelerating the delivery of safe and affordable autonomous vehicles at scale

How do you make deployable autonomous vehicles a reality? By listening, learning, and taking action. There are significant challenges to deployment that include ultra-high-performance computing within the power, thermal and size constraints of a vehicle to operate a large and sophisticated autonomous software stack.

The AVCC understands the technological complexities and obstacles that need to be overcome for the deployment of autonomous vehicles and aims to work together to deliver a conceptual compute platform that addresses these challenges. The group brings together a unique combination of expertise and a shared goal, and our first objective will be to define a reference architecture and platform to meet autonomous performance goals within the practical and economical deployment constraints of a vehicle. This computing platform will be designed specifically to move today’s prototype systems to deployment at scale. We will also develop the requirements for software APIs for each building block in an autonomous system.

Putting innovation in the driving seat

Driving, and especially commuting on today’s roads can be one of the most stressful parts of the day, dealing with overcrowded, congested roads full of distracted drivers. Heading home from the office through heavy traffic recently, I was struck by the idea that in just a few years’ time the view from my windshield might be completely different than what it is today. Imagine a world where vehicles are able to perceive their dynamically changing environment, communicate seamlessly with each other, roadside infrastructure and digital services networks, while transporting their occupants – or even cargo – safely and autonomously. Drivers will become passengers, free to utilize their time productively for leisure or work, vehicles will become on-the-move content consumption platforms, and mobility will become both safer and much more sustainable.

Arm is thrilled to be joining other automotive industry leaders as we collaborate to take the industry one step closer to a future in which autonomous vehicles not only remove a lot of the stress that traveling and commuting creates today, but also play a major role in tackling much broader societal challenges. Stay tuned for new developments as this exciting initiative grows!

Development on the project is scheduled to be completed by early 2020. The project will be centered around StradVision’s deep learning-based SVNet External vision processing software.

StradVision CEO Junhwan Kim said this project is an exciting development, and further proof of StradVision’s growth in the emerging Autonomous Vehicle market.

StradVision’s SVNet External software enables vehicles to execute ADAS and self-driving functions, including:

• Automatic Emergency Braking
• Adaptive Cruise Control
• Lane Departure Warning
• Blind Spot Detection

StradVision’s deep-learning expertise is a key reason for its growth, as the company’s  algorithms lead the way in object detection (OD) and free space detection (FSD).

StradVision has also earned the coveted ASPICE CL2 certificate, and applies the ISO26262 functional safety standards, allowing StradVision to deliver peak performance to OEMs and Tier 1s.

By 2021, StradVision will have nearly 7 million vehicles on the world’s roadways using SVNet, which is already compliant with strict standards such as Euro NCAP and Guobiao (GB) in China.

StradVision is continuously expanding in China, and already deploying ADAS vehicles on Chinese roads

StradVision currently has 5 production projects in Europe and China

SVNet provides real-time feedback, detects obstacles in blind spots, and alerts drivers to potential accidents. It also prevents collisions by detecting lanes and abrupt lane changes, even in poor lighting or weather conditions.

Daimler Trucks and Torc Robotics are actively developing and testing automated trucks with SAE Level 4 intent technology on public roads. The initial routes are on highways in southwest Virginia, where Torc Robotics is headquartered. All automated runs require both an engineer overseeing the system and a highly trained safety driver certified by Daimler Trucks and Torc Robotics. All safety drivers hold a commercial driver’s license and are specially trained in vehicle dynamics and automated systems.

The deployment on public roads takes place after months of extensive testing and safety validation on a closed loop track. As part of the comprehensive safety process by Daimler Trucks and Torc Robotics, both test track and on-road validation play an integral role in establishing the essential building blocks for successfully advancing automated technology.