Results 41 to 50 of about 2,712,717 (312)

Piecewise linear car-following modeling [PDF]

Transportation Research Part C: Emerging Technologies, 2012
19 pages, 3 ...
openaire   +3 more sources

Longitudinal Dynamic versus Kinematic Models for Car-Following Control Using Deep Reinforcement Learning

, 2019
The majority of current studies on autonomous vehicle control via deep reinforcement learning (DRL) utilize point-mass kinematic models, neglecting vehicle dynamics which includes acceleration delay and acceleration command dynamics.
Azad, Nasser L., Lin, Yuan, McPhee, John
core   +1 more source

Calibrating Car-Following Models Using SUMO-in-the-Loop and Vehicle Trajectories From Roadside Radar

SUMO Conference Proceedings
This paper presents an innovative calibration method for car-following (CF) models in the Simulation of Urban MObility (SUMO) using real-world trajectory data from a 1.5 km signalized urban corridor, captured by roadside radars.
Maxwell Schrader, Arya Karnik, Alexander Hainen, Joshua Bittle   +3 more
doaj   +1 more source

Fusion Modeling Method of Car-Following Characteristics

IEEE Access, 2019
Car-following model is indispensable to evaluate the characteristics of car-following behaviors. Through an analysis and comparison of data-driven and theoretically driven car-following models, it shows that the data-driven model has poor ...
Yufang Li, Xiaoding Lu, Chen Ren, Hongwei Zhao   +3 more
doaj   +1 more source

Learning Car-Following Behaviors for a Connected Automated Vehicle System: An Improved Sequence-to-Sequence Deep Learning Model

IEEE Access, 2023
Data-driven car-following modeling is of great significance to traffic behavior analysis and the development of connected automated vehicle (CAV) technology. The existing researches focus on reproducing the car-following process by capturing the behavior
Wenqi Lu, Ziwei Yi, Bingjie Liang, Yikang Rui, Bin Ran   +4 more
doaj   +1 more source

Line-of-Sight Obstruction Analysis for Vehicle-to-Vehicle Network Simulations in a Two-Lane Highway Scenario [PDF]

, 2013
In vehicular ad-hoc networks (VANETs) the impact of vehicles as obstacles has largely been neglected in the past. Recent studies have reported that the vehicles that obstruct the line-of-sight (LOS) path may introduce 10-20 dB additional loss, and as a ...
Abbas, Taimoor, Tufvesson, Fredrik
core   +3 more sources

A review on following behavioral models: Regular to connected autonomous vehicle heterogeneity

IATSS Research
Following behavior, an integral part of driving, is vital in describing the longitudinal interaction among vehicles. The traffic composition of the stream influences the following behavior.
Nazmul Haque, Md Asif Raihan, Md Mizanur Rahman, Md Hadiuzzaman   +3 more
doaj   +1 more source

Modeling Driver Behavior in Road Traffic Simulation

Sensors, 2022
Driver behavior models are an important part of road traffic simulation modeling. They encompass characteristics such as mood, fatigue, and response to distracting conditions.
Teodora Mecheva, Radoslav Furnadzhiev, Nikolay Kakanakov   +2 more
doaj   +1 more source

Generalized Force Model of Traffic Dynamics

, 1999
Floating car data of car-following behavior in cities were compared to existing microsimulation models, after their parameters had been calibrated to the experimental data.
B. S. Kerner, B. S. Kerner, B. S. Kerner, B. S. Kerner, Benno Tilch, C. Wagner, D. A. Kurtze, D. C. Gazis, D. H. Hoefs, D. Helbing, D. Helbing, D. Helbing, D. Helbing, D. Helbing, D. Helbing, D. Helbing, D. Helbing, Dirk Helbing, H. J. Herrmann, I. Prigogine, J. T. Jenkins, M. Bando, M. Bando, M. Herrmann, M. Rickert, M. Schreckenberg, N. Metropolis, P. Wagner, S. F. Foerster, S. Krauss, T. Bleile, T. Nagatani, T. Nagatani, T. Pöschel, W. G. Hoover   +34 more
core   +1 more source

In-vehicle channel sounding in the 5.8-GHz band [PDF]

, 2015
The article reports vehicular channel measurements in the frequency band of 5.8 GHz for IEEE 802.11p standard. Experiments for both intra-vehicle and out-of-vehicle environments were carried out.
Chandra, Aniruddha, Kukolev, Pavel, Mecklenbräuker, Christoph, Mikulášek, Tomáš, Prokeš, Aleš, Zemen, Thomas   +5 more
core   +2 more sources