CES 2019 Roundup: Autonomous Vehicle Tech
Matthew Greenwood posted on January 10, 2019 |

AEye’s AE200 iDAR

The iDAR is touted by AEye as a “new form of intelligent data collection that enables dynamic perception.” The iDAR simulates how the human visual cortex focuses on and evaluates the environment around the vehicle, driving conditions, and road hazards.

AEye AE200 iDAR

AEye AE200 iDAR

While current LIDAR sensors rely on an array of independent sensors that produce large quantities of data—which that needs long processing times and extensive computing power to analyze and translate into actionable information that a car can use. These LIDAR platforms also lack the intelligence to prioritize the data they gather.

AEye’s iDAR combines solid-state LIDAR with a low-light HD camera. It integrates them with AI that prioritizes the information received, focusing on imminent dangers and obstacles. This decreases the amount of data used—and speeds up reaction time. The company claims that iDAR increases the speed of a car’s self-driving perception system by up to 10 times, while reducing power consumption 5 to 10 times.

AutoX Automated Delivery Vehicles

AutoX is using self-driving car technology to deliver groceries to consumers’ home—describing it as “the grocery run of the future.”

AutoX vehicles are temperature-controlled and feature a mobile shop right in the car for users to try new products. High-resolution sensing technology and AI-boosted navigation enables self-driving cars to deliver groceries safely and on time.

AutoX launched a pilot program last year in San Jose, California, which is also testing a smart scheduling and fleet management system. The company believes that last mile delivery is “likely going to be one of the first large-scale self-driving car applications.” 

Screenshots of the AutoX app.
Screenshots of the AutoX app.

Connected Signals

This technology platform integrates traffic light information with vehicle navigation systems to enable both drivers and self-driving cars get around more efficiently and safer. It combines real-time municipalities traffic light information with map, GPS and speed limit information—and then runs that data through proprietary analytics and algorithms to predict traffic light behavior.

Many autonomous vehicles rely on having their cameras aimed at traffic lights to interpret them. Integrating Connected Signals’ real-time traffic light data into their navigation systems could improve speed, routing and driving efficiency, could eliminate the dangers of the car being unable to see obstructed traffic lights, and would add another layer of information for the vehicle to use when driving.

AutonomousONE Motherboard

Autonomous vehicle developers and testers often find that the tools to gather, test and interpret data can be difficult to find. Intrepid Control Systems offers a solution: a motherboard that allows users to replace bulky, cobbled-together equipment with a single streamlined interface device that integrates data from multiple sources into a single open platform.

The AutonomousONE motherboard links components such as the CPU and GPS, and has the capacity to connect multiple sensors including cameras, radar and LIDAR. It synchronizes all data through an integrated data logger. The motherboard also features a removable storage solution with up to 64 terabyte capacity.


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