Exploring the Limitations of Behavior Cloning for Autonomous Driving [PDF]
, 2019 Driving requires reacting to a wide variety of complex environment conditions and agent behaviors. Explicitly modeling each possible scenario is unrealistic.
Codevilla, Felipe +3 more
core +2 more sources
Driving Behavior Modeling Based on Consistent Variable Selection in a PWARX Model
Applied Sciences, 2021 This paper proposes the hybrid system model identified by a PWARX (piecewise affine autoregressive exogenous) model for modeling human driving behavior.
Jude Chibuike Nwadiuto +2 more
doaj +1 more source
Behavioral Sciences, 2022 To prevent vehicle crashes, studies have proposed the use of flashing signals (brake lights or other light indicators) to improve the driver’s response time when the leading vehicle is braking.
Min-Chih Hsieh +3 more
doaj +1 more source
Fuel Saving Indeks Assessment on Driving Behavior Control System Prototype Model Using Neural Network [PDF]
Archives of Transport, 2022 Efficient fuel consumption in the world is essential in automotive technology development due to the increase in vehicle usage and the decrease in global oil production. Several studies have been conducted to increase fuel consumption savings, Fuel Cells
Suroto Munahar +3 more
doaj +1 more source
Estimating the Necessary Amount of Driving Data for Assessing Driving Behavior
Sensors, 2020 The aim of this paper was to provide a methodological framework for estimating the amount of driving data that should be collected for each driver in order to acquire a clear picture regarding their driving behavior.
Anna-Maria Stavrakaki +4 more
doaj +1 more source
Driving Speed Analysis Using Real-Time Traffic Light Status Information at Signalized Intersections
Engineering Proceedings, 2023 This study aims to analyze driver behavior when traffic light status information is provided to the in-vehicle systems of individual vehicles. In the case where signal information was provided when the vehicle was approaching an intersection in a red ...
Eunjin Choi +4 more
doaj +1 more source
Decision-Making Model for Dynamic Scenario Vehicles in Autonomous Driving Simulations
Applied Sciences, 2023 A scenario vehicle in autonomous driving simulations is a dynamic entity that is expected to perform trustworthy bidirectional interaction tasks with the autonomous vehicle under test.
Yanfeng Li +3 more
doaj +1 more source
Driving with Style: Inverse Reinforcement Learning in General-Purpose Planning for Automated Driving
, 2020 Behavior and motion planning play an important role in automated driving. Traditionally, behavior planners instruct local motion planners with predefined behaviors.
Großjohann, Simon +4 more
core +1 more source
Spontaneous behaviors drive multidimensional, brain-wide activity [PDF]
Science, 2018 Cortical responses to sensory stimuli are highly variable, and sensory cortex exhibits intricate spontaneous activity even without external sensory input. Cortical variability and spontaneous activity have been variously proposed to represent random noise, recall of prior experience, or encoding of ongoing behavioral and cognitive variables.
Stringer, Carsen +5 more
openaire +4 more sources
Decision-Making for Automated Vehicles Using a Hierarchical Behavior-Based Arbitration Scheme
, 2020 Behavior planning and decision-making are some of the biggest challenges for highly automated systems. A fully automated vehicle (AV) is confronted with numerous tactical and strategical choices.
Burger, Christoph +2 more
core +1 more source