A novel lane change decision-making model of autonomous vehicle based on support vector machine

Y Liu, X Wang, L Li, S Cheng, Z Chen - IEEE access, 2019 - ieeexplore.ieee.org
Autonomous driving is a crucial issue of the automobile industry, and research on lane
change is its significant part. Previous works on the autonomous vehicle lane change mainly …

Examining lane change gap acceptance, duration and impact using naturalistic driving data

M Yang, X Wang, M Quddus - Transportation research part C: emerging …, 2019 - Elsevier
Abstract Analysis of lane change is important for microsimulation and safety improvement,
and can also provide reference for advanced driver assistance systems (ADAS) and …

Understanding the discretionary lane-changing behaviour in the connected environment

Y Ali, Z Zheng, MM Haque, M Yildirimoglu… - Accident Analysis & …, 2020 - Elsevier
Discretionary lane-changing (DLC) is one of the complex driving manoeuvres that requires
surrounding traffic information for efficient and safe manoeuvring. The connected …

A novel lane-changing decision model for autonomous vehicles based on deep autoencoder network and XGBoost

X Gu, Y Han, J Yu - IEEE Access, 2020 - ieeexplore.ieee.org
Lane-changing (LC) is a critical task for autonomous driving, especially in complex dynamic
environments. Numerous automatic LC algorithms have been proposed. This topic …

Analysing and modelling of discretionary lane change duration considering driver heterogeneity

G Li, Z Yang, Y Pan, J Ma - Transportmetrica B: Transport …, 2023 - Taylor & Francis
This paper aims to investigate the characteristics of discretionary lane change (LC) duration
on freeways based on an enriched dataset that contains the LC vehicle trajectories of 2905 …

A unified modeling framework for lane change intention recognition and vehicle status prediction

R Yuan, M Abdel-Aty, X Gu, O Zheng… - Physica A: Statistical …, 2023 - Elsevier
Accurately detecting and predicting Lane Change (LC) processes of human-driven vehicles
can help autonomous vehicles better understand their surrounding environment, recognize …

Application of machine learning algorithms in lane-changing model for intelligent vehicles exiting to off-ramp

C Dong, H Wang, Y Li, X Shi, D Ni… - … A: transport science, 2021 - Taylor & Francis
The primary objective of this study is to evaluate how intelligent vehicles equipped with
cooperative adaptive cruise control (CACC) improve freeway efficiency and safety at an off …

Time-varying mixed logit model for vehicle merging behavior in work zone merging areas

J Weng, G Du, D Li, Y Yu - Accident Analysis & Prevention, 2018 - Elsevier
This study aims to develop a time-varying mixed logit model for the vehicle merging
behavior in work zone merging areas during the merging implementation period from the …

Using graph-theoretic machine learning to predict human driver behavior

R Chandra, A Bera, D Manocha - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Studies have shown that autonomous vehicles (AVs) behave conservatively in a traffic
environment composed of human drivers and do not adapt to local conditions and socio …

Virtual-to-real knowledge transfer for driving behavior recognition: Framework and a case study

C Lu, F Hu, D Cao, J Gong, Y Xing… - IEEE Transactions on …, 2019 - ieeexplore.ieee.org
Considering the difficulty and high cost of collecting sufficient data in the real world, driving
simulators are used in many studies as an alternative data source, which can provide a …