4.7 Article

Predicting and explaining lane-changing behaviour using machine learning: A comparative study

相关参考文献

注意:仅列出部分参考文献,下载原文获取全部文献信息。
Article Ergonomics

Transfer learning for spatio-temporal transferability of real-time crash prediction models

Cheuk Ki Man et al.

Summary: This study explores the transferability of real-time crash prediction models under an extremely imbalanced data setting using Generative Adversarial Network (GAN) and transfer learning. The findings indicate that transfer learning improves the temporal, spatial, and spatio-temporal transferability of the models, outperforming standalone models in predicting traffic crashes.

ACCIDENT ANALYSIS AND PREVENTION (2022)

Article Automation & Control Systems

An Intelligent Lane-Changing Behavior Prediction and Decision-Making Strategy for an Autonomous Vehicle

Weida Wang et al.

Summary: This article proposes a prediction method based on a fuzzy inference system and a long short-term memory neural network to accurately predict the lane-changing behavior of surrounding vehicles, as well as an intelligent decision-making strategy for path planning of autonomous vehicles to enhance driving safety.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2022)

Article Transportation

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

Changyin Dong et al.

Summary: The study demonstrates that CACC penetration rate and length of diverge influence areas significantly impact road capacity and traffic safety. Road capacity peaks after an initial decrease as CACC penetration rate increases.

TRANSPORTMETRICA A-TRANSPORT SCIENCE (2021)

Article Computer Science, Artificial Intelligence

Lane change strategy analysis and recognition for intelligent driving systems based on random forest

Qinyu Sun et al.

Summary: This study identified different lane change strategies used by vehicles through on-road experiments, including mandatory, yielding, and waiting for lane change strategies, and compared and analyzed different characteristic parameters under these strategies. A random forest classifier was employed to construct a lane change strategy identification model.

EXPERT SYSTEMS WITH APPLICATIONS (2021)

Article Engineering, Mechanical

Comparison of Machine Learning Algorithms for Predicting Lane Changing Intent

Dongho Choi et al.

Summary: This study investigates predicting driver lane change intent using on-board sensors and vehicle-to-vehicle communication, comparing the performance of several machine learning algorithms. Random forest algorithm showed the highest accuracy in predicting lane change intent.

INTERNATIONAL JOURNAL OF AUTOMOTIVE TECHNOLOGY (2021)

Article Engineering, Civil

Driver Lane-Changing Behavior Prediction Based on Deep Learning

Cheng Wei et al.

Summary: A hybrid neural network prediction model based on RNN and FC is proposed to accurately predict lane-changing behavior and improve the prospective time of prediction by about 2.1 s on average. The proposed model achieves a prediction accuracy of 93.5% in real traffic scenarios.

JOURNAL OF ADVANCED TRANSPORTATION (2021)

Article Physics, Multidisciplinary

Recognition of lane-changing behaviour with machine learning methods at freeway off-ramps

Ting Xu et al.

Summary: Frequent crashes occur at freeway off-ramps due to improper lane-changing behaviours. By utilizing machine learning technology and convolutional neural networks, an efficient lane-changing recognition model was designed with an accuracy rate exceeding 94.6%.

PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS (2021)

Article Engineering, Civil

Prediction Performance of Lane Changing Behaviors: A Study of Combining Environmental and Eye-Tracking Data in a Driving Simulator

Qi Deng et al.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2020)

Article Transportation Science & Technology

An ensemble deep learning approach for driver lane change intention inference

Yang Xing et al.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2020)

Article Engineering, Civil

Prediction of Lane-Changing Maneuvers with Automatic Labeling and Deep Learning

Vishal Mahajan et al.

TRANSPORTATION RESEARCH RECORD (2020)

Article Transportation Science & Technology

Cooperate or not? Exploring drivers' interactions and response times to a lane-changing request in a connected environment

Yasir Ali et al.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2020)

Article Ergonomics

Understanding the discretionary lane-changing behaviour in the connected environment

Yasir Ali et al.

ACCIDENT ANALYSIS AND PREVENTION (2020)

Article Ergonomics

Highway crash detection and risk estimation using deep learning

Tingting Huang et al.

ACCIDENT ANALYSIS AND PREVENTION (2020)

Article Ergonomics

Toward safer highways, application of XGBoost and SHAP for real-time accident detection and feature analysis

Amir Bahador Parsa et al.

ACCIDENT ANALYSIS AND PREVENTION (2020)

Article Transportation Science & Technology

A data-driven lane-changing model based on deep learning

Dong-Fan Xie et al.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2019)

Article Transportation Science & Technology

A game theory-based approach for modelling mandatory lane-changing behaviour in a connected environment

Yasir Ali et al.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2019)

Article Computer Science, Information Systems

A Deep Learning Method for Lane Changing Situation Assessment and Decision Making

Xiao Liu et al.

IEEE ACCESS (2019)

Article Computer Science, Artificial Intelligence

Multivariate time series prediction of lane changing behavior using deep neural network

Jun Gao et al.

APPLIED INTELLIGENCE (2018)

Article Transportation Science & Technology

Connectivity's impact on mandatory lane-changing behaviour: Evidences from a driving simulator study

Yasir Ali et al.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2018)

Article Ergonomics

Classification of motor vehicle crash injury severity: A hybrid approach for imbalanced data

Heejin Jeong et al.

ACCIDENT ANALYSIS AND PREVENTION (2018)

Article Engineering, Industrial

Multi-parameter prediction of drivers' lane-changing behaviour with neural network model

Jinshuan Peng et al.

APPLIED ERGONOMICS (2015)

Article Economics

Trajectory data reconstruction and simulation-based validation against macroscopic traffic patterns

Marcello Montanino et al.

TRANSPORTATION RESEARCH PART B-METHODOLOGICAL (2015)

Article Transportation Science & Technology

Modeling lane-changing behavior in a connected environment: A game theory approach

Alireza Talebpour et al.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2015)

Article Economics

Recent developments and research needs in modeling lane changing

Zuduo Zheng

TRANSPORTATION RESEARCH PART B-METHODOLOGICAL (2014)

Article Transportation Science & Technology

Merging behaviour: Empirical comparison between two sites and new theory development

Florian Marczak et al.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2013)

Article Automation & Control Systems

Estimation of Traffic Densities for Multilane Roadways Using a Markov Model Approach

Karandeep Singh et al.

IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS (2012)

Article Transportation Science & Technology

On selecting an optimal wavelet for detecting singularities in traffic and vehicular data

Zuduo Zheng et al.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2012)

Article Computer Science, Cybernetics

Comparing Boosting and Bagging Techniques With Noisy and Imbalanced Data

Taghi M. Khoshgoftaar et al.

IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART A-SYSTEMS AND HUMANS (2011)

Article Transportation Science & Technology

Statistical methods versus neural networks in transportation research: Differences, similarities and some insights

M. G. Karlaftis et al.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2011)

Article Transportation Science & Technology

On the assessment of vehicle trajectory data accuracy and application to the Next Generation SIMulation (NGSIM) program data

Vincenzo Punzo et al.

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES (2011)

Article Engineering, Civil

Empirical Analysis of Merging Behavior at Freeway On-Ramp

Winnie Daamen et al.

TRANSPORTATION RESEARCH RECORD (2010)

Article Engineering, Civil

Observing freeway ramp merging phenomena in congested traffic

Majid Sarvi et al.

JOURNAL OF ADVANCED TRANSPORTATION (2007)

Proceedings Paper Computer Science, Artificial Intelligence

Enhanced recursive feature elimination

Xue-Wen Chen et al.

ICMLA 2007: SIXTH INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND APPLICATIONS, PROCEEDINGS (2007)

Review Physics, Multidisciplinary

Cellular automata models of road traffic

S Maerivoet et al.

PHYSICS REPORTS-REVIEW SECTION OF PHYSICS LETTERS (2005)