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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:

Lane change detection and prediction using real-world connected vehicle data
Hongyu Guo, Mehdi Keyvan‐Ekbatani, Kun Xie
Transportation Research Part C Emerging Technologies (2022) Vol. 142, pp. 103785-103785
Closed Access | Times Cited: 33

Showing 1-25 of 33 citing articles:

Shared autonomous electric vehicle: Towards social economy of energy and mobility from power-transportation nexus perspective
Sumit K Rathor, Ameena Saad Al‐Sumaiti
Renewable and Sustainable Energy Reviews (2024) Vol. 197, pp. 114381-114381
Closed Access | Times Cited: 17
Modeling driver’s evasive behavior during safety–critical lane changes: Two-dimensional time-to-collision and deep reinforcement learning
Hongyu Guo, Kun Xie, Mehdi Keyvan‐Ekbatani
Accident Analysis & Prevention (2023) Vol. 186, pp. 107063-107063
Open Access | Times Cited: 33
Enhanced index of risk assessment of lane change on expressway weaving segments: A case study of an expressway in China
Jinbao Zhang, Jaeyoung Lee, Mohamed Abdel‐Aty, et al.
Accident Analysis & Prevention (2022) Vol. 180, pp. 106909-106909
Closed Access | Times Cited: 26
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
Hybrid perimeter control with real-time partitions in heterogeneous urban networks: An integration of deep learning and MPC
Shang Jiang, Mehdi Keyvan‐Ekbatani
Transportation Research Part C Emerging Technologies (2023) Vol. 154, pp. 104240-104240
Open Access | Times Cited: 11
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
Rethinking real-time risk prediction from multi-step time series forecasting on highway car-following scenarios
Huansong Zhang, Yongjun Shen, Qiong Bao, et al.
Accident Analysis & Prevention (2024) Vol. 207, pp. 107748-107748
Closed Access | Times Cited: 4
Empirical research on car-following and lane-changing: Recent developments, emerging vehicle technologies’ impact, and future research needs
Yasir Ali, Anshuman Sharma, Zuduo Zheng
Transportation Research Interdisciplinary Perspectives (2025) Vol. 31, pp. 101368-101368
Closed Access
Drone Data Analytics for Measuring Traffic Metrics at Intersections in High-Density Areas
Q. H. Pu, Yuan Zhu, Junqing Wang, et al.
Transportation Research Record Journal of the Transportation Research Board (2025)
Closed Access
Anomalous Identity Recognition Model Based on Vehicle Driving Characteristic Verification in Typical Scenarios
Xing Chen, Jingsheng Wang, Yan Song, et al.
Computers & Security (2025), pp. 104476-104476
Closed Access
A vehicle driving intention prediction method based on gated dual tower transformer model for autonomous driving
Xuliang Guo, Hongfei Jia, Qiuyang Huang, et al.
Expert Systems with Applications (2025), pp. 128000-128000
Closed Access
An enhanced motion planning approach by integrating driving heterogeneity and long-term trajectory prediction for automated driving systems: A highway merging case study
Ni Dong, Shuming Chen, Yina Wu, et al.
Transportation Research Part C Emerging Technologies (2024) Vol. 161, pp. 104554-104554
Closed Access | Times Cited: 2
Failed lane-changing detection and prediction using naturalistic vehicle trajectories
Yingying Xing, Yutong Wu, Hongwei Wang, et al.
Transportation Research Part C Emerging Technologies (2024) Vol. 170, pp. 104939-104939
Closed Access | Times Cited: 2
Analysing driver behaviour and crash frequency at railway level crossings using connected vehicle and GIS data
Seunghyeon Lee, Tiantian Chen, N.N. Sze, et al.
Travel Behaviour and Society (2024) Vol. 39, pp. 100957-100957
Closed Access | Times Cited: 2
A Novel Model for Driver Lane Change Prediction in Cooperative Adaptive Cruise Control Systems
Armin Nejadhossein Qasemabadi, Saeed Mozaffari, Mahdi Rezaei, et al.
(2023), pp. 1-4
Open Access | Times Cited: 4
Evaluation of Spatiotemporal Characteristics of Lane-Changing at the Freeway Weaving Area from Trajectory Data
Pengying Ouyang, Bo Yang
Sustainability (2024) Vol. 16, Iss. 4, pp. 1639-1639
Open Access | Times Cited: 1
STABILITY ANALYSIS FOR HETEROGENEOUS TRAFFIC FLOW WITH LANE-CHANGE DISTURBANCE
Hao Li, Yun Pu, Lingjuan Chen, et al.
Transport (2024) Vol. 39, Iss. 1, pp. 37-53
Open Access | Times Cited: 1
Improved time series models for the prediction of lane-change intention
Hongrui Zhang, Yonggang Wang, Shengrui Zhang, et al.
Transportation Letters (2024), pp. 1-15
Closed Access | Times Cited: 1
Multi-Level Feature Extraction and Classification for Lane Changing Behavior Prediction and POD-Based Evaluation
Zahra Rastin, Dirk Söffker
Automation (2024) Vol. 5, Iss. 3, pp. 310-323
Open Access | Times Cited: 1
CRRFNet: An adaptive traffic object detection method based on camera and radar radio frequency fusion
Wenbo Wang, Weibin Zhang
Transportation Research Part C Emerging Technologies (2024) Vol. 166, pp. 104791-104791
Closed Access | Times Cited: 1
Research on the Platoon Speed Guidance Strategy at Signalized Intersections in the Connected Vehicle Environment
Chuanxiang Ren, Li Wang, Changchang Yin, et al.
Journal of Advanced Transportation (2023) Vol. 2023, pp. 1-25
Open Access | Times Cited: 3
On the identification of risky lane changes: 2D time-to-collision and connected vehicle data
Hongyu Guo, Kun Xie, Mehdi Keyvan‐Ekbatani
(2023), pp. 1-6
Closed Access | Times Cited: 1
Exploring traffic breakdown with vehicle-level data
Youngjun Han, Jinhak Lee
Journal of Intelligent Transportation Systems (2024), pp. 1-17
Closed Access
Modeling Lane Changes Using Parallel Learning
Yu Han, Shixuan Yu, Yan Li, et al.
(2024)
Closed Access
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