Mcity Data Collection for Automated Vehicles Study
This provides a comprehensive open-source dataset for researchers and developers in automated driving, though it is incremental as it builds on existing data collection efforts.
The paper introduces the Mcity dataset for automated vehicle development, capturing sensor data, vehicle inputs, and driver behaviors across various conditions, and includes unique choreographed interactions for vehicle-to-vehicle and vehicle-to-vulnerable road user scenarios.
The main goal of this paper is to introduce the data collection effort at Mcity targeting automated vehicle development. We captured a comprehensive set of data from a set of perception sensors (Lidars, Radars, Cameras) as well as vehicle steering/brake/throttle inputs and an RTK unit. Two in-cabin cameras record the human driver's behaviors for possible future use. The naturalistic driving on selected open roads is recorded at different time of day and weather conditions. We also perform designed choreography data collection inside the Mcity test facility focusing on vehicle to vehicle, and vehicle to vulnerable road user interactions which is quite unique among existing open-source datasets. The vehicle platform, data content, tags/labels, and selected analysis results are shown in this paper.