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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:

Non-linear effects of the built environment on automobile-involved pedestrian crash frequency: A machine learning approach
Chuan Ding, Peng Chen, Junfeng Jiao
Accident Analysis & Prevention (2018) Vol. 112, pp. 116-126
Open Access | Times Cited: 117

Showing 1-25 of 117 citing articles:

To walk or not to walk? Examining non-linear effects of streetscape greenery on walking propensity of older adults
Linchuan Yang, Yibin Ao, Jintao Ke, et al.
Journal of Transport Geography (2021) Vol. 94, pp. 103099-103099
Open Access | Times Cited: 317
A geographically and temporally weighted regression model to explore the spatiotemporal influence of built environment on transit ridership
Xiaolei Ma, Jiyu Zhang, Chuan Ding, et al.
Computers Environment and Urban Systems (2018) Vol. 70, pp. 113-124
Closed Access | Times Cited: 264
Quantifying and comparing the effects of key risk factors on various types of roadway segment crashes with LightGBM and SHAP
Xiao Wen, Yuanchang Xie, Lingtao Wu, et al.
Accident Analysis & Prevention (2021) Vol. 159, pp. 106261-106261
Closed Access | Times Cited: 208
The application of XGBoost and SHAP to examining the factors in freight truck-related crashes: An exploratory analysis
Chao Yang, Mingyang Chen, Quan Yuan
Accident Analysis & Prevention (2021) Vol. 158, pp. 106153-106153
Closed Access | Times Cited: 204
Predicting effects of built environment on fatal pedestrian accidents at location-specific level: Application of XGBoost and SHAP
Iljoon Chang, Hoontae Park, Eungi Hong, et al.
Accident Analysis & Prevention (2022) Vol. 166, pp. 106545-106545
Closed Access | Times Cited: 73
Advances, challenges, and future research needs in machine learning-based crash prediction models: A systematic review
Yasir Ali, Fizza Hussain, Md. Mazharul Haque
Accident Analysis & Prevention (2023) Vol. 194, pp. 107378-107378
Open Access | Times Cited: 50
Effectiveness of road safety interventions: An evidence and gap map
Rahul Goel, Geetam Tiwari, Mathew Varghese, et al.
Campbell Systematic Reviews (2024) Vol. 20, Iss. 1
Open Access | Times Cited: 15
Promoting carsharing attractiveness and efficiency: An exploratory analysis
Songhua Hu, Peng Chen, Hangfei Lin, et al.
Transportation Research Part D Transport and Environment (2018) Vol. 65, pp. 229-243
Closed Access | Times Cited: 89
Exploring the mechanism of crashes with automated vehicles using statistical modeling approaches
Song Wang, Zhixia Li
PLoS ONE (2019) Vol. 14, Iss. 3, pp. e0214550-e0214550
Open Access | Times Cited: 85
Machine learning in occupational accident analysis: A review using science mapping approach with citation network analysis
Sobhan Sarkar, J. Maiti
Safety Science (2020) Vol. 131, pp. 104900-104900
Closed Access | Times Cited: 76
Nonlinear and threshold effects of the built environment on e-scooter sharing ridership
Hongtai Yang, Rong Zheng, Xuan Li, et al.
Journal of Transport Geography (2022) Vol. 104, pp. 103453-103453
Closed Access | Times Cited: 54
On the interpretability of machine learning methods in crash frequency modeling and crash modification factor development
Xiao Wen, Yuanchang Xie, Liming Jiang, et al.
Accident Analysis & Prevention (2022) Vol. 168, pp. 106617-106617
Closed Access | Times Cited: 45
A Powerful Paradigm for Cardiovascular Risk Stratification Using Multiclass, Multi-Label, and Ensemble-Based Machine Learning Paradigms: A Narrative Review
Jasjit S. Suri, Mrinalini Bhagawati, Sudip Paul, et al.
Diagnostics (2022) Vol. 12, Iss. 3, pp. 722-722
Open Access | Times Cited: 42
Nonlinear effects of built environment features on metro ridership: An integrated exploration with machine learning considering spatial heterogeneity
Mengyang Liu, Yuxuan Liu, Yu Ye
Sustainable Cities and Society (2023) Vol. 95, pp. 104613-104613
Closed Access | Times Cited: 27
Machine learning techniques for evaluating the nonlinear link between built-environment characteristics and travel behaviors: A systematic review
Mahdi Aghaabbasi, Saksith Chalermpong
Travel Behaviour and Society (2023) Vol. 33, pp. 100640-100640
Closed Access | Times Cited: 23
Can we trust our eyes? Interpreting the misperception of road safety from street view images and deep learning
Xujing Yu, Jun Ma, Yihong Tang, et al.
Accident Analysis & Prevention (2024) Vol. 197, pp. 107455-107455
Closed Access | Times Cited: 13
Fatigue at the wheel: A non-visual approach to truck driver fatigue detection by multi-feature fusion
Chen He, Pengpeng Xu, Xin Pei, et al.
Accident Analysis & Prevention (2024) Vol. 199, pp. 107511-107511
Closed Access | Times Cited: 13
Evaluating machine learning performance in predicting injury severity in agribusiness industries
Fatemeh Davoudi Kakhki, Steven A. Freeman, Gretchen A. Mosher
Safety Science (2019) Vol. 117, pp. 257-262
Open Access | Times Cited: 71
A joint probability model for pedestrian crashes at macroscopic level: Roles of environment, traffic, and population characteristics
Junbiao Su, N.N. Sze, Lu Bai
Accident Analysis & Prevention (2020) Vol. 150, pp. 105898-105898
Open Access | Times Cited: 52
Applying machine learning and google street view to explore effects of drivers’ visual environment on traffic safety
Qing Cai, Mohamed Abdel‐Aty, Ou Zheng, et al.
Transportation Research Part C Emerging Technologies (2021) Vol. 135, pp. 103541-103541
Closed Access | Times Cited: 52
Predicting shared-car use and examining nonlinear effects using gradient boosting regression trees
Tao Wang, Songhua Hu, Yuan Jiang
International Journal of Sustainable Transportation (2020) Vol. 15, Iss. 12, pp. 893-907
Closed Access | Times Cited: 50
Predicting bicycling and walking traffic using street view imagery and destination data
Steve Hankey, Wenwen Zhang, Huyen Le, et al.
Transportation Research Part D Transport and Environment (2020) Vol. 90, pp. 102651-102651
Closed Access | Times Cited: 50
An Advanced Machine Learning Approach to Predicting Pedestrian Fatality Caused by Road Crashes: A Step toward Sustainable Pedestrian Safety
Wenlong Tao, Mahdi Aghaabbasi, Mujahid Ali, et al.
Sustainability (2022) Vol. 14, Iss. 4, pp. 2436-2436
Open Access | Times Cited: 28
Critical review on data-driven approaches for learning from accidents: Comparative analysis and future research
Yi Niu, Yunxiao Fan, Xing Ju
Safety Science (2023) Vol. 171, pp. 106381-106381
Closed Access | Times Cited: 18
Towards safer streets: A framework for unveiling pedestrians’ perceived road safety using street view imagery
Omar Faruqe Hamim, Satish V. Ukkusuri
Accident Analysis & Prevention (2023) Vol. 195, pp. 107400-107400
Closed Access | Times Cited: 17
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