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AEye Announces Groundbreaking Immersive Lidar Experience for Attendees

Be One of the First to Step Inside a Lidar Data Point Cloud to Experience How Vehicles Sense the World in Motion at AEye’s Safer Mobility for All Exhibit…

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AEye Announces Groundbreaking Immersive Lidar Experience for Attendees at CES 2023

Be One of the First to Step Inside a Lidar Data Point Cloud to Experience How Vehicles Sense the World in Motion at AEye’s Safer Mobility for All Exhibit

AEye,, a global leader in adaptive, high-performance lidar solutions, invites attendees to an immersive lidar experience at the Consumer Electronics Show (CES), taking place January 5 – 8, 2023 in Las Vegas. Visitors to AEye’s indoor and outdoor exhibit areas can experience lidar first-hand by stepping inside a virtual reality lidar data point cloud, walking through a live, lidar-monitored crosswalk, and riding through the streets of Las Vegas in AEye’s ShadowVan demonstration vehicle.

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Safer Mobility for All

AEye lidar enables safer mobility for all modes of transportation – from cars and trucks, to pedestrians and cyclists. Roadway fatalities continue to increase at an alarming rate, and are at a 16-year high, with nearly 50,000 fatalities annually due to motor vehicle and pedestrian-vehicle traffic collisions. At CES, AEye will demonstrate how reducing those numbers using technology is possible – now. The company will also release findings of its “Safer Mobility Survey,” conducted in partnership with the Partners for Automated Vehicle Education (PAVE), which gauges Americans’ views on road safety for all road users, including drivers, pedestrians, and bicyclists.

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An Immersive Lidar Experience

Through a series of interactive demonstrations, visitors to AEye’s West Hall locations will learn how adaptive lidar improves pedestrian safety, enables safe, high-speed highway ADAS and autonomous functionality, and future-proofs autonomous development.

Attendees can visit AEye in one of two locations for an immersive lidar demo experience:

Inside, at booth #3429, in the LVCC West Hall:

  • Journey through a point cloud – Don a virtual reality headset and walk through a point cloud to see first-hand how lidar accurately captures information about the 3D world.
  • Experience a lidar-monitored crosswalk – Walk through a live, lidar-monitored crosswalk to see how adaptive lidar works in real-time to identify and track pedestrians in a zone in order to improve crowd monitoring and enhance pedestrian safety.

Outside, in the LVCC West Hall lot:

  • Take a Ride in AEye’s ShadowVan – Experience Continental’s HRL131 Long Range Lidar production intent sample, built on AEye’s 4Sight Intelligent Sensing Platform, as it reconfigures performance modes on-the-fly for optimized perception in different driving environments, such as parking lots, city streets, and highways.
  • Immerse yourself in a point cloud – Put on a VR headset and fly through a live, long-range point cloud to see how it accurately captures the world in 3D.
  • Try out AEye’s SteadiCam – Adjust the pitch angle of the adaptive lidar in this interactive software demo to see how the HRL131 product adapts to road slopes, speed bumps, and potholes on-the-fly.

AEye will also participate in a panel on the “Anatomy of Autonomy” at SAE’s CES Connect2Car event. The panel, scheduled for January 5 at 10am PT, will feature AEye’s founder and CTO Luis Dussan, as well as executives from Aurora, Uber, and Ford.

AEye’s 4Sight Intelligent Sensing Platform is the industry’s only adaptive, solid-state, and software-definable lidar platform. It utilizes adaptive lidar to improve the probability of detection and accuracy of classification – complementing existing sensors and increasing the speed and accuracy of decision-making. As a software-definable platform, 4Sight facilitates the release of new industry-advancing applications across the scale of autonomy, future-proofing automotive development and paving the way for the software-defined car, while allowing for multiple ITS applications and both long- and-short-range detection using only one sensor

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