Results 31 to 40 of about 14,572 (301)

Evolving a rule system controller for automatic driving in a car racing competition [PDF]

open access: yes, 2008
IEEE Symposium on Computational Intelligence and Games. Perth, Australia, 15-18 December 2008.The techniques and the technologies supporting Automatic Vehicle Guidance are important issues.
Sáez, Yago   +10 more
core   +1 more source

The Intelligent Driver Model with Stochasticity -New Insights Into Traffic Flow Oscillations [PDF]

open access: yesTransportation Research Procedia, 2017
Traffic flow oscillations, including traffic waves, are a common yet incompletely understood feature of congested traffic. Possible mechanisms include traffic flow instabilities, indifference regions or finite human perception thresholds (action points), and external acceleration noise.
Treiber, Martin, Kesting, Arne
openaire   +2 more sources

A Car-Following Model considering the Effect of Following Vehicles under the Framework of Physics-Informed Deep Learning

open access: yesJournal of Advanced Transportation, 2022
Car-following models have been studied for a long time, and many traffic engineers and researchers have devoted attention to them. With the increase in machine learning, this paper proposes a fusion model based on the physics-informed deep learning ...
Le Xu, Jianxiao Ma, Yuchen Wang
doaj   +1 more source

Design and Numerical Implementation of V2X Control Architecture for Autonomous Driving Vehicles

open access: yesMathematics, 2021
This paper is concerned with designing and numerically implementing a V2X (Vehicle-to-Vehicle and Vehicle-to-Infrastructure) control system architecture for a platoon of autonomous vehicles.
Piyush Dhawankar   +5 more
doaj   +1 more source

In loco intellegentia: Human factors for the future European train driver

open access: yes, 2006
The European Rail Traffic Management System (ERTMS) represents a step change in technology for rail operations in Europe. It comprises track-to-train communications and intelligent on-board systems providing an unprecedented degree of support to the ...
Stanton, Neville A   +8 more
core   +1 more source

Long-term trajectory prediction method based on highway vehicle-following behavior patterns

open access: yesJournal of Intelligent and Connected Vehicles
To address existing shortcomings such as short time domains and low interpretability, this study proposes a long-term trajectory prediction model for leading vehicles that considers the impact of traffic flow.
Zhichao An   +7 more
doaj   +1 more source

A New Single Point Preview-Based Human-Like Driver Model on Urban Curved Roads

open access: yesIEEE Access, 2020
To make intelligent vehicles obtain human drivers' steering characteristic, a new single point preview-based human-like driver model is proposed, which contains a preview decision module and a steering wheel angle calculation module.
Xinchen Zhou   +3 more
doaj   +1 more source

Advanced driver assistance systems from autonomous to cooperative approach

open access: yes, 2008
Advanced Driver Assistance Systems (ADAS) have been one of the most active areas of ITS studies in the last two decades. ADAS aim to support drivers by either providing warning to reduce risk exposures, or automating some of the control tasks to relieve ...
Piao, J., McDonald, M.
core   +1 more source

Safe driving in a green world : a review of driver performance benchmarks and technologies to support ‘smart’ driving [PDF]

open access: yes, 2011
Road transport is a significant source of both safety and environmental concerns. With climate change and fuel prices increasingly prominent on social and political agendas, many drivers are turning their thoughts to fuel efficient or ‘green’ (i.e ...
Mark S. Young   +5 more
core   +1 more source

Overview of lane-keeping assist system based on human–machine cooperative control

open access: yes工程科学学报, 2021
As the final stage of intelligent vehicle, traffic accidents can be effectively reduced by automatic driving. However, neither the technology nor the regulations are mature for autonomous driving.
Zeng-ke QIN, Lie GUO, Yue MA, Ming YUE
doaj   +1 more source

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