Skip to main content

Lidar technology wins big in China’s autonomous vehicle challenge

China’s fifth annual Future Challenge earlier this month pitted eleven unmanned intelligent vehicles against each other on a course designed to test their capabilities in suburban and urban road tests, over a 23-kilometre course. All of the first eight cars to finish were equipped with Velodyne’s 3D Lidar vision technology which provides active sensing for crash avoidance, driving automation and mobile road survey and mapping. Velodyne HDL-64E and HDL-32E sensors deliver 360-degree views of the car’s env
November 26, 2013 Read time: 2 mins
China’s fifth annual Future Challenge earlier this month pitted eleven unmanned intelligent vehicles against each other on a course designed to test their capabilities in suburban and urban road tests, over a 23-kilometre course.

All of the first eight cars to finish were equipped with Velodyne’s 3D Lidar vision technology which provides active sensing for crash avoidance, driving automation and mobile road survey and mapping. Velodyne HDL-64E and HDL-32E sensors deliver 360-degree views of the car’s environment, with real-time updates twenty times per second.

Cars on the course needed to demonstrate the ability to recognise light, eliminate human and vehicle interference, successfully detour around construction zones, turn around and come to a stop. All were also required to establish the ability to make a U-turn, accelerate and decelerate. Performance was graded on safety, smartness, smoothness and speed.

"This is simply a remarkable accomplishment," said Wolfgang Juchmann, PhD, 2259 Velodyne Lidar director of sales and marketing. "The Future Challenge course was nothing less than demanding throughout, with terrain and tests that demonstrated Lidar’s versatility and reliability in real time. And the fact that eight of eleven vehicles were so equipped stands as a huge vote of confidence in our technology."

For more information on companies in this article

Related Content

  • M&S looks all around to reduce collisions
    June 20, 2014
    UK retailer Marks & Spencer (M&S) is trialling the latest 360-degree camera system from Brigade and technology partner, ASL Vision, to further improve safety on its lorry fleet. As systems offering a surround view in a single image become more widespread on rigid trucks, M&S wants to find out if the benefits can be extended to articulated vehicles. An initial trial was set up using the Backeye 360 Elite system from Brigade Electronics with powerful software from ASL Vision at its core. The trial is now to b
  • AVs in the Netherlands? Don't forget the bikes
    June 11, 2019
    The Netherlands’ famous love of bicycles could be a problem when it comes to the deployment of autonomous vehicles there. And there might be other obstacles, finds Ben Spencer Of all the countries on the planet, the Netherlands is most ready to start deploying autonomous vehicles (AVs), according to a survey by KPMG earlier this year. On the face of it, this is good news: coming first out of 25 countries listed in the Autonomous Vehicles Readiness Index (AVRI) for the second consecutive year puts the Du
  • Need for performance standards for road user charging systems
    February 2, 2012
    GNSS-based road use metering systems need performance metrics, as well as ways to test and reliably compare them. Bern Grush and Joaquín Cosmen write about the function of the GNSS Metering Association for Road-use charging (GMAR), recently set up to address this issue
  • Daimler’s double take sees machine vision move in-vehicle
    December 13, 2013
    Jason Barnes looks at Daimler’s Intelligent Drive programme to consider how machine vision has advanced the state of the art of vision-based in-vehicle systems. Traditionally, radar was the in-vehicle Driver Assistance System (DAS) technology of choice, particularly for applications such as adaptive cruise control and pre-crash warning generation. Although vision-based technology has made greater inroads more recently, it is not a case of ‘one sensor wins’. Radar and vision are complementary and redundancy