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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

An ensemble deep learning approach for driver lane change intention inference
Yang Xing, Chen Lv, Huaji Wang, et al.
Transportation Research Part C Emerging Technologies (2020) Vol. 115, pp. 102615-102615
Open Access | Times Cited: 169

Showing 26-50 of 169 citing articles:

Continual driver behaviour learning for connected vehicles and intelligent transportation systems: Framework, survey and challenges
Zirui Li, Cheng Gong, Yunlong Lin, et al.
Green Energy and Intelligent Transportation (2023) Vol. 2, Iss. 4, pp. 100103-100103
Open Access | Times Cited: 20
Driver lane change intention prediction based on topological graph constructed by driver behaviors and traffic context for human-machine co-driving system
Tao Huang, Rui Fu, Qinyu Sun, et al.
Transportation Research Part C Emerging Technologies (2024) Vol. 160, pp. 104497-104497
Closed Access | Times Cited: 7
Spatial-temporal ConvLSTM for vehicle driving intention prediction
He Huang, Zheni Zeng, Danya Yao, et al.
Tsinghua Science & Technology (2021) Vol. 27, Iss. 3, pp. 599-609
Open Access | Times Cited: 39
Driver Intention Recognition: State-of-the-Art Review
Koen Vellenga, H. Joe Steinhauer, Alexander Karlsson, et al.
IEEE Open Journal of Intelligent Transportation Systems (2022) Vol. 3, pp. 602-616
Open Access | Times Cited: 26
Lane-change intention prediction using eye-tracking technology: A systematic review
Yunxian Pan, Qinyu Zhang, Yifan Zhang, et al.
Applied Ergonomics (2022) Vol. 103, pp. 103775-103775
Closed Access | Times Cited: 23
A unified modeling framework for lane change intention recognition and vehicle status prediction
Renteng Yuan, Mohamed Abdel‐Aty, Xin Gu, et al.
Physica A Statistical Mechanics and its Applications (2023) Vol. 632, pp. 129332-129332
Closed Access | Times Cited: 16
A Deep Learning Framework to Explore Influences of Data Noises on Lane-Changing Intention Prediction
Ye Li, Fei Liu, Lu Xing, et al.
IEEE Transactions on Intelligent Transportation Systems (2024) Vol. 25, Iss. 7, pp. 6514-6526
Closed Access | Times Cited: 6
Modeling coupled driving behavior during lane change: A multi-agent Transformer reinforcement learning approach
Hongyu Guo, Mehdi Keyvan‐Ekbatani, Kun Xie
Transportation Research Part C Emerging Technologies (2024) Vol. 165, pp. 104703-104703
Open Access | Times Cited: 6
Importance Weighted Gaussian Process Regression for Transferable Driver Behaviour Learning in the Lane Change Scenario
Zirui Li, Jianwei Gong, Chao Lu, et al.
IEEE Transactions on Vehicular Technology (2020) Vol. 69, Iss. 11, pp. 12497-12509
Closed Access | Times Cited: 35
Multi-scale driver behavior modeling based on deep spatial-temporal representation for intelligent vehicles
Yang Xing, Chen Lv, Dongpu Cao, et al.
Transportation Research Part C Emerging Technologies (2021) Vol. 130, pp. 103288-103288
Closed Access | Times Cited: 32
Exploring Behavioral Patterns of Lane Change Maneuvers for Human-Like Autonomous Driving
Yaoyu Chen, Guofa Li, Shen Li, et al.
IEEE Transactions on Intelligent Transportation Systems (2021) Vol. 23, Iss. 9, pp. 14322-14335
Closed Access | Times Cited: 32
Intelligent transportation systems (ITS): A systematic review using a Natural Language Processing (NLP) approach
Zulkarnain Zulkarnain, Tsarina Dwi Putri
Heliyon (2021) Vol. 7, Iss. 12, pp. e08615-e08615
Open Access | Times Cited: 32
Intent prediction of vessels in intersection waterway based on learning vessel motion patterns with early observations
Jie Ma, Chengfeng Jia, Yaqing Shu, et al.
Ocean Engineering (2021) Vol. 232, pp. 109154-109154
Closed Access | Times Cited: 30
Hybrid-Learning-Based Driver Steering Intention Prediction Using Neuromuscular Dynamics
Yang Xing, Chen Lv, Yahui Liu, et al.
IEEE Transactions on Industrial Electronics (2021) Vol. 69, Iss. 2, pp. 1750-1761
Closed Access | Times Cited: 29
The Application of Electroencephalogram in Driving Safety: Current Status and Future Prospects
Yong Peng, Qian Xu, Shuxiang Lin, et al.
Frontiers in Psychology (2022) Vol. 13
Open Access | Times Cited: 21
Use of Social Interaction and Intention to Improve Motion Prediction Within Automated Vehicle Framework: A Review
Djamel Eddine Benrachou, Sébastien Glaser, Mohammed Elhenawy, et al.
IEEE Transactions on Intelligent Transportation Systems (2022) Vol. 23, Iss. 12, pp. 22807-22837
Closed Access | Times Cited: 21
Prediction-Uncertainty-Aware Threat Detection for ADAS: A Case Study on Lane-Keeping Assistance
John Dahl, Gabriel Rodrigues de Campos, Jonas Fredriksson
IEEE Transactions on Intelligent Vehicles (2023) Vol. 8, Iss. 4, pp. 2914-2925
Closed Access | Times Cited: 12
Intelligent Transportation System Based on Smart Soft-Sensors to Analyze Road Traffic and Assist Driver Behavior Applicable to Smart Cities
Anass Barodi, Abdelkarim Zemmouri, Abderrahim Bajit, et al.
Microprocessors and Microsystems (2023) Vol. 100, pp. 104830-104830
Closed Access | Times Cited: 12
Predicting highway lane-changing maneuvers: A benchmark analysis of machine and ensemble learning algorithms
Basma Khelfa, Ibrahima Ba, Antoine Tordeux
Physica A Statistical Mechanics and its Applications (2023) Vol. 612, pp. 128471-128471
Open Access | Times Cited: 11
Lane-Changing Intention Recognition Based on Multivehicle Interaction Dynamic Graph Modeling in a Connected Environment
Yunchao Zhang, Yanyan Chen, Yongxing Li, et al.
Journal of Transportation Engineering Part A Systems (2024) Vol. 150, Iss. 6
Closed Access | Times Cited: 4
A two-stage framework for parking search behavior prediction through adversarial inverse reinforcement learning and transformer
Ji Tianyi, Cong Zhao, Yuxiong Ji, et al.
Expert Systems with Applications (2024) Vol. 255, pp. 124548-124548
Closed Access | Times Cited: 4
Lane change decision prediction: an efficient BO-XGB modelling approach with SHAP analysis
Haobo Sun, Qixiu Cheng, Pu Wang, et al.
Transportmetrica A Transport Science (2024), pp. 1-38
Closed Access | Times Cited: 4
Predicting lane change maneuver and associated collision risks based on multi-task learning
Liu Yang, Jike Zhang, Nengchao Lyu, et al.
Accident Analysis & Prevention (2024) Vol. 209, pp. 107830-107830
Closed Access | Times Cited: 4
Early Recognition of Driving Intention for Lane Change Based on Recurrent Hidden Semi-Markov Model
Qingxiao Liu, Shaohang Xu, Chao Lu, et al.
IEEE Transactions on Vehicular Technology (2020) Vol. 69, Iss. 10, pp. 10545-10557
Closed Access | Times Cited: 29
A Bayesian inference based adaptive lane change prediction model
Jinghua Wang, Zhao Zhang, Guangquan Lu
Transportation Research Part C Emerging Technologies (2021) Vol. 132, pp. 103363-103363
Closed Access | Times Cited: 26

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