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How We Define and Understand Autonomous Driving

Freetech commercializes Level 4 autonomous driving solutions for closed/semi-closed scenarios and low-speed driving.

For passenger transport services, these solutions mainly focus on simple urban roads, fixed urban public transport routes, as well as short-distance shuttle system at locations such as resorts, tourist attractions, airports, industrial parks, and university campuses.
For freight logistics, these solutions primarily concentrate on logistics and transportation involving trucks or special vehicles in parks, ports, and airports.

Optimize hardware configuration and improve algorithm software performance in order to make cars more intelligent, while keeping system costs under control
Leveraging on 5G connectivity and networking, and the collaboration between individual smart vehicles and the network, improve the safety of autonomous driving.
Application of automotive grade products, with system redundancy designs for vehicles, in order to continuously improve system reliability and explore safety strategies for autonomous driving functions.

Support data integration for multiple types of sensors, including vision, LiDAR, millimeter wave, ultrasonic sensors, etc., with multiple sensors.
Achieve target detection based on multi-LiDAR point cloud integration and multi-millimeter wave radar point cloud data integration.
Improve sensing and target integration accuracy by relying on automated dynamic designation and precise time synchronization based on hardware signals.
Filter out false targets and reduce integrated computing resources by combining high-precision maps and vehicle positioning; expand target tracking attributes to improve target motion prediction accuracy.
Integrate roadside unit target information using networking equipment in order to increase target integration confidence and possess sensing ability beyond line-of-sight.

Support sensor integrated positioning based on vision, LiDAR, IMU, GNSS/RTK, and odometer.

Integrate positioning using LiDAR-based SLAM and GNSS to increase positioning accuracy and reliability when GNSS signal loses lock.
Integrate map lane lines and visual lane lines to enhance the reliability of structured road positioning.

Support various functions, including setting driving routes, lane cruising, smooth driving on slopes, adaptive car-following, autonomous obstacle avoidance, passing through road intersections, as well as stopping and picking up passengers at sites.
Local path planning technology that meets dynamics-related constraints and with vertical and horizontal collaboration optimization.

Vehicle trajectory tracking control technology based on sliding mode variable structure and LQR method.

Full sensor coverage of the vehicle's sides without blind spots, which improves driving safety.

Excellent side-front and side-rear detection ability, which improves the reliability of the vehicle when passing intersections and changing lanes.
Cross detection of key areas by heterogeneous sensors, which improves the accuracy of target detection.

Well configured sensing system, which reduces system costs under pre-set driving scenarios.