Results 11 to 20 of about 1,522,764 (280)

Research on transformer and long short-term memory neural network car-following model considering data loss

open access: yesMathematical Biosciences and Engineering, 2023
There is limited research on the loss and reconstruction of car-following features. To delve into car-following's characteristics, we propose a car-following model based on LSTM-Transformer.
Pinpin Qin   +4 more
doaj   +1 more source

Bayesian Calibration of Car-Following Models

open access: yesIFAC Proceedings Volumes, 2009
Abstract Recent research has revealed that there exist large inter-driver differences in car-following behavior such that different car-following models may apply to different drivers. This study applies Bayesian techniques to the calibration of car-following models, where prior distributions on each model parameter are converted to posterior ...
Van Hinsbergen, C.P.IJ. (author)   +3 more
openaire   +4 more sources

An analysis of Gipps' car-following model of highway traffic [PDF]

open access: yes, 2001
A mathematical analysis of Gipps's (1981) car?following model is performed. This model is of practical importance as it powers the UK Transport Research Laboratory highway simulation package SISTM.
Wilson, R E
core   +1 more source

Transmission Capacity Analysis for Vehicular Ad Hoc Networks

open access: yesIEEE Access, 2018
Traditional studies focused on the transmission capacity of vehicular ad hoc network (VANET) contains two deficiencies: the lack of a realistic model mimicking the behaviors of vehicles and the failure to consider the impacts from enhanced distributed ...
Xinxin He, Weisen Shi, Tao Luo
doaj   +1 more source

A Study on an Anthropomorphic Car-Following Strategy Framework of the Autonomous Coach in Mixed Traffic Flow

open access: yesIEEE Access, 2020
In this study, to explore the demand characteristics of autonomous coaches in mixed traffic flow, two sections of an expressway were selected for vehicle experiments.
Chen Zhao   +3 more
doaj   +1 more source

A formulation of the relaxation phenomenon for lane changing dynamics in an arbitrary car following model

open access: yes, 2020
Lane changing dynamics are an important part of traffic microsimulation and are vital for modeling weaving sections and merge bottlenecks. However, there is often much more emphasis placed on car following and gap acceptance models, whereas lane changing
Gao, H. Oliver, Keane, Ronan
core   +1 more source

A Car-Following Driver Model Capable of Retaining Naturalistic Driving Styles

open access: yesJournal of Advanced Transportation, 2020
The modeling of car-following behavior is an attractive research topic in traffic simulation and intelligent transportation. The driver plays an important role in car following but is ignored by most car-following models.
Jie Hu, Sheng Luo
doaj   +1 more source

An Improved Car-Following Model considering Desired Safety Distance and Heterogeneity of Driver’s Sensitivity

open access: yesJournal of Advanced Transportation, 2021
We investigate the dynamic performance of traffic flow using a modified optimal velocity car-following model. In the car-following scenarios, the following vehicle must continuously adjust the following distance to the preceding vehicle in real time.
Lei Zhang   +4 more
doaj   +1 more source

Research on car-following model based on molecular dynamics

open access: yesAdvances in Mechanical Engineering, 2021
The car-following model has always been a research hot spot in the field of traffic flow theory. Modeling the car-following behavior can quantify the longitudinal interaction between cars, thereby understanding the characteristics of traffic flow, and ...
Yanfeng Jia   +4 more
doaj   +1 more source

Exact shock solution of a coupled system of delay differential equations: a car-following model [PDF]

open access: yes, 2007
In this paper, we present exact shock solutions of a coupled system of delay differential equations, which was introduced as a traffic-flow model called {\it the car-following model}.
Bando M.   +7 more
core   +2 more sources

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