openACC. An open database of car-following experiments to study the properties of commercial ACC systems
arXiv:2004.06342 · doi:10.1016/j.trc.2021.103047
Abstract
Commercial Adaptive Cruise Control (ACC) systems are increasingly available as standard options in modern vehicles. At the same time, still little information is openly available on how these systems actually operate and how different is their behavior, depending on the vehicle manufacturer or model.T o reduce this gap, the present paper summarizes the main features of the openACC, an open-access database of different car-following experiments involving a total of 16 vehicles, 11 of which equipped with state-of-the-art commercial ACC systems. As more test campaigns will be carried out by the authors, OpenACC will evolve accordingly. The activity is performed within the framework of the openData policy of the European Commission Joint Research Centre with the objective to engage the whole scientific community towards a better understanding of the properties of ACC vehicles in view of anticipating their possible impacts on traffic flow and prevent possible problems connected to their widespread. A first preliminary analysis on the properties of the 11 ACC systems is conducted in order to showcase the different research topics that can be studied within this open science initiative.
References in corpus (1)
Cited by in corpus (16)
- Car-Following Models: A Multidisciplinary Review
- Physics-augmented models to simulate commercial adaptive cruise control (ACC) systems
- Characterizing driver heterogeneity within stochastic traffic simulation
- A Unified Longitudinal Trajectory Dataset for Automated Vehicle
- The Unscented Kalman Filter for Nonlinear Parameter Identification of Adaptive Cruise Control Systems
- Physics-inspired Neural Networks for Parameter Learning of Adaptive Cruise Control Systems
- An Efficient Safety-oriented Car-following Model for Connected Automated Vehicles Considering Discrete Signals
- Energy-based Assessment and Driving Behavior of ACC Systems and Humans Inside Platoons
- Driving Towards Stability and Efficiency: A Variable Time Gap Strategy for Adaptive Cruise Control
- Knowledge-data fusion dominated vehicle platoon dynamics modeling and analysis: A physics-encoded deep learning approach
- On the Robotic Uncertainty of Fully Autonomous Traffic: From Stochastic Car-Following to Mobility-Safety Trade-Offs
- Scalable analysis of stop-and-go waves: Representation, measurements and insights
- A Review on Trajectory Datasets on Advanced Driver Assistance System
- Interaction Dataset of Autonomous Vehicles with Traffic Lights and Signs
- The fragile nature of road transportation networks
- Modelling vehicle and pedestrian collective dynamics: Challenges and advances