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The V2X roadside sensing system from LSLiDAR is based on the fusion of LiDAR and camera data to accurately locate and identify vehicles, non-motor vehicles, and pedestrians on the road through leading neural network algorithms. Then the real-time information is transmitted to the traffic management department to realize the early warning of road conditions and dangers. This will improve the safety and redundancy of autonomous driving, and bring a safe, efficient, reliable safety guarantee and environmentally friendly road traffic system for autonomous driving.
Advanced neural networks and deep learning algorithms accurately identify the targets such as vehicles, non-motor vehicles and pedestrians.All information related to distance, speed, direction and traffic flow can be acquired.
Compared with other sensors such as infrared, ultrasonic and radar, LiDAR has more accurate and faster detection capability.
Advanced neural networks and deep learning algorithms are used to identify target classifications such as vehicles, non-motor vehicles and pedestrians. All information related to distance, speed, direction and traffic flow can be accessed.
Identify events such as "reverse", "traffic jam", "slow driving", "abnormal lane change", "driving in the emergency lane", "intrusion", "measurement over limit", "Pull over", "speeding", "V2P", etc.
Customize various V2X roadside sensing solutions to enrich LiDAR options according to the scenario.
Customize various V2X roadside sensing solutions to enrich LiDAR options according to the scenario.
Different projects have been deployed in Beijing, Shanghai, Guangzhou, Shenzhen, Zhengzhou, Chongqing, Xi ‘an, Tianjin, Wuhan, Suzhou, Xuchang, Changzhou and other cities, covering traffic lights, accident blind areas, road intersections, Bridges and tunnels, schools and other areas.
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Thank you very much for your approval of LSLiDAR, we will do our best to serve you ! We will respond to your intended needs within 24 hours, thank you for your support.
*Please fill in the correct email address to avoid failure to receive messages/files.