Roadside Lidar Helping to Build Smart and Safe Transportation Infrastructure Velodyne Lidar

Format:

Book

Conference/Event

Author/Creator:

Barad, Jon, author.

Conference Name:

Business of Automated Mobility (BAM) Forum (2021-06-23 : Live Online, Pennsylvania, United States)

Language:

English

Physical Description:

1 online resource cm

Place of Publication:

Warrendale, PA SAE International 2021

Summary:

As part of its research in transportation infrastructure, the University of Nevada, Reno's Nevada Center for Applied Research, in conjunction with the Regional Transportation Commission of Washoe County and the Nevada DOT, used Velodyne's lidar sensors to collect data aimed at making transportation more efficient, sustainable and safe. This paper summarizes the research results and data obtained by UNR's Nevada Center for Applied Research. The program integrated Velodyne Ultra Puck lidar sensors with traffic signals to detect, count and track pedestrians, cyclists and traffic. It leveraged the data captured with the sensors to help improve traffic analytics, congestion management and pedestrian safety. The initial lidar sensor was placed at a Reno intersection in 2017. A review of studies and data indicates this may have been the first-ever application of lidar on a traffic signal. Additional lidar sensors were placed at crossing signs and intersections in Reno, the nearby Tahoe Reno Industrial Center and in the city of Henderson, Nevada. Since lidar used today does not allow for facial recognition, the incorporation of these sensors helped preserve trust and anonymity among the public. The project is being conducted in real-world test environments, known as Living Laboratories. It was developed through Intelligent Mobility, a comprehensive and multidisciplinary initiative led by UNR researchers and supported by the Nevada Governor's Office of Economic Development. These "lidar-enhanced" roads in Northern and Southern Nevada are also able to communicate data to connected vehicles to support eco-drive and collision avoidance applications. They are also capable of addressing roadway congestion monitoring and near-crash analysis

Notes:

Vendor supplied data

Publisher Number:

2021-01-1013

Access Restriction:

Restricted for use by site license