Results 11 to 20 of about 17,260 (260)

Integrating Surrounding Vehicle Information for Vehicle Trajectory Representation and Abnormal Lane-Change Behavior Detection

open access: yesSensors, 2023
The detection of abnormal lane-changing behavior in road vehicles has applications in traffic management and law enforcement. The primary approach to achieving this detection involves utilizing sensor data to characterize vehicle trajectories, extract ...
Da Xu   +3 more
doaj   +1 more source

Analysis of the Relationship between the Density and Lane-Changing Behavior of Circular Multilane Urban Expressway in Mixed Traffic

open access: yesJournal of Advanced Transportation, 2022
The behavior of changing lanes has a great impact on road traffic with heavy traffic. Traffic flow density is one of the important parameters that characterize the characteristics of traffic flow, and it will also be affected by the behavior of changing ...
Han Xie, Juanxiu Zhu, Huawei Duan
doaj   +1 more source

Research on the SSIDM Modeling Mechanism for Equivalent Driver’s Behavior

open access: yesWorld Electric Vehicle Journal, 2023
To solve the problem of smooth switching between the car-following model and lane-changing model, the Intelligent Driver Model (IDM) for a single lane was used to study the driver’s behavior switching mechanism of normally following, generating ...
Rui Fang
doaj   +1 more source

Lane-Changing Behavior Prediction Based on Game Theory and Deep Learning

open access: yesJournal of Advanced Transportation, 2021
Lane changing is an important scenario in traffic environments, and accurate prediction of lane-changing behavior is essential to ensure traffic and driver safety.
Shuo Jia   +4 more
doaj   +1 more source

An Optimized Car-Following Behavior in Response to a Lane-Changing Vehicle: A Bézier Curve-Based Approach

open access: yesIEEE Open Journal of Intelligent Transportation Systems, 2023
Sudden lane-changing maneuvers can disrupt the traffic flow. In this paper, we introduce an approach to optimize car-following behavior in response to a lane-changing vehicle in a connected driving environment.
Gihyeob An   +2 more
doaj   +1 more source

Vehicles Lane-changing Behavior Detection

open access: yesCoRR, 2018
The lane-level localization accuracy is very important for autonomous vehicles. The Global Navigation Satellite System (GNSS), e.g. GPS, is a generic localization method for vehicles, but is vulnerable to the multi-path interference in the urban environment.
Iljoo Baek, Mengwen He
openaire   +2 more sources

The Atlas of Lane Changes: Investigating Location-Dependent Lane Change Behaviors Using Measurement Data from a Customer Fleet [PDF]

open access: yes2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021
the article has been accepted for publication during the 24th IEEE Intelligent Transportation Systems Conference (ITSC), 8 pages, 11 ...
Florian Wirthmüller   +3 more
openaire   +2 more sources

How Do Vehicles Make Decisions during Implementation Period of Discretionary Lane Change? A Data-Driven Research

open access: yesJournal of Advanced Transportation, 2023
To investigate and compare the lane changing behavior of passenger cars and heavy vehicles during the implementation period (defined as the interval from the start time to the end time of a lane change maneuver), this study applies the gradient boosting ...
Qiangru Shen   +4 more
doaj   +1 more source

Lane-Changing Recognition of Urban Expressway Exit Using Natural Driving Data

open access: yesApplied Sciences, 2022
The traffic environment at the exit of the urban expressway is complex, and vehicle lane-changing behavior occurs frequently, making it prone to traffic conflict and congestion.
Lei Zhao   +3 more
doaj   +1 more source

Driver Lane-Changing Behavior Prediction Based on Deep Learning

open access: yesJournal of Advanced Transportation, 2021
A correct lane-changing plays a crucial role in traffic safety. Predicting the lane-changing behavior of a driver can improve the driving safety significantly. In this paper, a hybrid neural network prediction model based on recurrent neural network (RNN)
Cheng Wei, Fei Hui, Asad J. Khattak
doaj   +1 more source

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