Tag: Robotaxi

  • Seen & Heard: Autonomous vehicles and Apple AirTags

    Seen & Heard: Autonomous vehicles and Apple AirTags

    “Seen & Heard” is a monthly feature of GPS World magazine, traveling the world to capture interesting and unusual news stories involving the GNSS/PNT industry.


    Image: iStock/Getty Images Plus/Getty Images
    Image: iStock/Getty Images Plus/Getty Images

    San Francisco Not Keen on Avs

    San Francisco officials aren’t happy with autonomous vehicles (AV) on their streets. They say the AVs are at fault for traffic violations and congestion, delays in emergency response and public transport — even trips onto public sidewalks. California officials granted the first AV deployment permits this year, allowing companies to release self-driving cars onto city streets and to provide passenger service as robotaxis. State governments have the legal power to grant permits to AV companies to conduct testing and ride-hail services, leaving city officials powerless to control self-driving car incidents that affect public safety.


    (Image: Apple)
    Image: Apple

    AirTag under Fire 

    Two women have filed a class-action lawsuit against Apple, claiming its AirTag trackers are being used for malicious and criminal purposes. Both women say they were tracked by ex-partners using Apple AirTags hidden in their belongings. They are seeking damages for negligence and privacy violations, and are hoping to prevent Apple from continuing to manufacture the product with “design flaws.”


    (Image: TU Delft/Frank Auperlé)
    Image: TU Delft/Frank Auperlé

    Navigating Urban Canyons with SuperGPS 

    Researchers at Delft University of Technology, Vrije Universiteit Amsterdam and VSL have developed an alternative positioning system that is more robust and accurate than GPS, especially in urban settings. The aim of the project — SuperGPS — was to develop an alternative positioning system that makes use of mobile telecommunications networks instead of satellites and that has better accuracy than GPS. A prototype of the infrastructure achieved an accuracy of 10 centimeters. The new technology is important for the implementation of a range of location-based applications, including automated vehicles, quantum communication and next-generation mobile communication systems.


    (Image: Allison Usavage/Cornell University)
    Image: Allison Usavage/Cornell University

    Robots Head to Vineyards

    Cornell researchers have designed PhytoPatholoBots (PPB) that will be deployed in vineyards across the country next spring in the first of a four-year project at Cornell, which is led by the University of Minnesota. The autonomous robots will collect data on the health of each grapevine, helping growers to evaluate their vineyards. The robots are part of the Specialty Crops Research Initiative, bringing innovation to the wine and grape industries.

  • DeepRoute.ai completes L4 driverless test in busy Shenzhen, China

    DeepRoute.ai completes L4 driverless test in busy Shenzhen, China

    The company tested Driver 2.0, a Level 4 production-ready autonomous driving solution

    New video highlights navigating heavy traffic safely and efficiently

    Photo: DeepRoute.ai
    Photo: DeepRoute.ai

    DeepRoute.ai, an international autonomous driving technology company, has announced the results of its latest fully driverless test of its Driver 2.0 Level 4 production-ready autonomous driving solution.

    DeepRoute.ai released a video exhibiting a driverless vehicle retrofitted with the solution on Central Business District roads in Shenzhen, demonstrating its advanced capacity in complex and challenging traffic environments. It was the first legal driverless test in China — Shenzhen unveiled China’s first regulation on intelligent connected vehicles on July 6.

    The fully driverless vehicle drove just under 14 miles in one hour, navigating through significant traffic and narrow lanes safely and efficiently. The vehicle:

    • intelligently maneuvered around double-parked cars and counterflow e-scooters and pedestrians
    • negotiated with oncoming vehicles to calculate the right timing and trajectory to pass busy intersections
    • conducted multiple lane changes and unprotected left turns.

    “The recent legislation permitting driverless robotaxis in Shenzhen is the first of its kind, a major milestone in advancing autonomous driving technology to wider and faster adoption,” said Maxwell Zhou, CEO of DeepRoute.ai. “As we advance our mission for commercial deployment of autonomous driving vehicles, we will collaborate with automakers to refine our L4 solution to make it as safe and efficient as possible.”

    DeepRoute.ai has made significant improvements to achieve driverless capability, with both software and hardware meeting auto-grade standards. The safety mechanism was also upgraded to guarantee driverless safety on the road. In the case of long tail scenarios, the system will alert the remote monitoring center to intervene or take other safety measures.

    The Driver 2.0 System

    Driver 2.0 includes five solid-state lidar units, eight cameras and other sensors, and a computing platform integrated with its proprietary inference engine. The perception algorithm with sensor fusion can achieve precise object detection up to nearly 220 yards. The planning and control algorithm based on game theory can choose optimal routes and make decisions based on real-time situations when negotiating with oncoming vehicles and other road agents.

    With its deep learning approach, the inference engine optimizes compute resources, allowing the algorithm to run on its low-cost and power-efficient computing platform effectively and stably. As a result, Driver 2.0 can be priced at $3,000 for automakers in mass production and the algorithm can work with 2 to 5 solid-state lidars for automakers’ customization needs.

    The latest legal and regulatory framework is aligned with autonomous-driving industry developments and is considered the prelude to mass production and commercialization of autonomous-driving vehicles. DeepRoute.ai is working with automakers to mass produce consumer vehicles integrated with Driver 2.0, expected to be available for consumer purchase in 2025. It is also being integrated into robotaxi operations.

    Photo: DeepRoute.ai
    Photo: DeepRoute.ai
  • DeepRoute.ai unveils autonomous ‘Robotaxi’ fleet

    DeepRoute.ai unveils autonomous ‘Robotaxi’ fleet

    DeepRoute.ai, an international autonomous driving technology company, is offering a Robotaxi fleet equipped with its Level 4 autonomous driving solution, Driver 2.0.

    Level 4 autonomous vehicles do not require human interaction in most circumstances, but a driver still has the option to manually override.

    Photo:
    Image: GPS World

    According to DeepRoute.ai, its advancement in autonomous technology previews the future of Level 4 consumer vehicles.

    Composed of 30 SAIC Motor Marvel R SUVs, the Robotaxi fleet will deploy in Shenzhen, China, in the coming months.

    Mass Production. Driver 2.0 was engineered for mass production and adoption by automakers. DeepRoute.ai projects mass production of Level 4 autonomous vehicles equipped with Driver 2.0 will begin in 2024 and be available for consumer purchase afterward.

    DeepRoute.ai is collaborating with global automakers to achieve series production of Level 4 autonomous driving vehicles and expects to further reduce the current $10,000 cost of the solution by approximately 70%.

    Driver 2.0 sensor configurations can be customized to meet automakers’ needs, equipped with two to five solid-state lidar scanners and eight cameras. Its proprietary low-energy consumption computing platform and inference engine combined with Nvidia Drive Orin systems-on-chip will allow the company to meet automotive-grade standards for series production more quickly, the company said.

    DeepRoute.ai’s camera-based redundancy perception system guarantees autonomous capabilities should other sensors malfunction, in addition to 5G remote control and network safety redundancy fused into the safety-critical systems.

    Level 4 self-driving can first be achieved in areas supported by rich data. Level 4 consumer vehicles on the road operating in a hybrid model will continuously gather additional data, laying the foundation for the scalability of Level 4 autonomous driving in other cities, the company said.

    DeepRoute.ai plans to accelerate Level 4 commercialization through technology iterations in data collection and analysis, algorithm improvement, simulation and road testing.

    Photo: DeepRoute.ai
    Photo: DeepRoute.ai

    With a 360-degree view and 200-meter perception range, the fleet offers high-performance Level 4 autonomous driving in an urban environment. The sensors are designed to be less noticeable and part of the auto’s chassis design.

    The entirety of DeepRoute.ai’s Robotaxi fleet across Wuhan, Shenzhen, Hangzhou and Fremont, California, now encompasses a variety of models: GAC Aion, SAIC Motor Marvel R, Lincoln MKZ, Geely, Dongfeng Motors E70 and Ford Mondeo.