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Human-like autonomous car-following model with deep reinforcement learning
This study proposes a framework for human-like autonomous car-following planning based
on deep reinforcement learning (deep RL). Historical driving data are fed into a simulation …
on deep reinforcement learning (deep RL). Historical driving data are fed into a simulation …
An adaptive longitudinal driving assistance system based on driver characteristics
A prototype of a longitudinal driving-assistance system, which is adaptive to driver behavior,
is developed. Its functions include adaptive cruise control and forward collision …
is developed. Its functions include adaptive cruise control and forward collision …
Towards data-driven car-following models
Car following models have been studied with many diverse approaches for decades.
Nowadays, technological advances have significantly improved our traffic data collection …
Nowadays, technological advances have significantly improved our traffic data collection …
Self-learning optimal cruise control based on individual car-following style
This study aims to develop an optimal cruise controller that can automatically adapt to
individual car-following style. First, the adaptive cruise control (ACC) problem is formulated …
individual car-following style. First, the adaptive cruise control (ACC) problem is formulated …
Development and testing of a fully adaptive cruise control system
Adaptive Cruise Control systems have been developed and introduced into the consumer
market for over a decade. Among these systems, fully-adaptive ones are required to adapt …
market for over a decade. Among these systems, fully-adaptive ones are required to adapt …
[HTML][HTML] Modeling car-following behaviors and driving styles with generative adversarial imitation learning
Y Zhou, R Fu, C Wang, R Zhang - Sensors, 2020 - mdpi.com
Building a human-like car-following model that can accurately simulate drivers' car-following
behaviors is helpful to the development of driving assistance systems and autonomous …
behaviors is helpful to the development of driving assistance systems and autonomous …
Artificial neural network models for car following: Experimental analysis and calibration issues
This article deals with the application of artificial neural networks to model car following
drivers' behavior. The study is based on experimental data collected by several global …
drivers' behavior. The study is based on experimental data collected by several global …
Human-like mechanism deep learning model for longitudinal motion control of autonomous vehicles
Artificial intelligence (AI) plays a critical role in the prediction, planning, and control of
autonomous vehicle. The original motion control methods are increasing in accuracy, but …
autonomous vehicle. The original motion control methods are increasing in accuracy, but …
Real‐time predictive eco‐driving assistance considering road geometry and long‐range radar measurements
Eco‐driving assistance systems incorporating predictive or feedforward information are a
promising technique to increase energy‐efficiency and reduce CO 2 emissions from road …
promising technique to increase energy‐efficiency and reduce CO 2 emissions from road …
Modelling the human lane-change execution behaviour through multilayer perceptrons and convolutional neural networks
Driving is a highly complex task that involves the execution of multiple cognitive tasks
belonging to different levels of abstraction. Traffic emerges from the interaction of a big …
belonging to different levels of abstraction. Traffic emerges from the interaction of a big …