학술논문

The Surface Accelerations Reference—A Large-Scale, Interactive Catalog of Passenger Vehicle Accelerations
Document Type
Periodical
Source
IEEE Transactions on Intelligent Transportation Systems IEEE Trans. Intell. Transport. Syst. Intelligent Transportation Systems, IEEE Transactions on. 24(9):9031-9040 Sep, 2023
Subject
Transportation
Aerospace
Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Vehicles
Behavioral sciences
Standards
Roads
Accelerometers
Kinematics
Databases
Vehicle accelerations
driving style
driving comfort
big data analytics
autonomous vehicle driving style
Language
ISSN
1524-9050
1558-0016
Abstract
There is a need for a large-scale, real world, diverse, and context rich vehicle acceleration catalog that can be used to design, analyze, and compare various intelligent transportation systems. This paper fulfills three primary objectives. First, it provides such a catalog through the Surface Accelerations Reference, which is openly available as an interactive analytics tool as well as an open and downloadable dataset. The Surface Accelerations Reference statistically describes the driving profiles of about 3,500 individuals contributing 34 million miles of continuous driving data collected in the Second Strategic Highway Research Program Naturalistic Driving Study (SHRP 2 NDS). These profiles were created by summarizing billions of longitudinal and lateral acceleration epochs experienced by the participants. Second, this paper introduces a standardized methodology for creating such a catalog so that similar acceleration profiles can be produced for other human cohorts or automated driving systems. Finally, the data are used to analyze the effect of roadway speed category on the rates of lateral and longitudinal acceleration epochs at various thresholds. It is observed that, for the median driver, the rates of epochs are up to three orders of magnitude higher on low-speed roads as compared to high-speed roads. This catalog will facilitate intelligent vehicle system designers to compare and tune their systems for safer driving experiences. It will also allow agencies with similar data to create comparable catalogs facilitating safety and behavioral comparisons between populations.