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Anuj Sharma
Researcher at Iowa State University
Publications - 184
Citations - 2702
Anuj Sharma is an academic researcher from Iowa State University. The author has contributed to research in topics: Computer science & Traffic flow. The author has an hindex of 23, co-authored 166 publications receiving 1902 citations. Previous affiliations of Anuj Sharma include Purdue University & Texas A&M University System.
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Journal ArticleDOI
Input–Output and Hybrid Techniques for Real-Time Prediction of Delay and Maximum Queue Length at Signalized Intersections
TL;DR: Two techniques are presented for real-time measurement of vehicledelay and queue length at a signalized intersection, and these automated delay and queue estimates are compared with manually ground-truthed measurement.
Journal ArticleDOI
Event-Based Data Collection for Generating Actuated Controller Performance Measures
TL;DR: In this article, an integrated general purpose data collection module that timestamps detector and phase state changes within a National Electrical Manufacturers Association actuated traffic signal controller was developed to provide quantitative graphs to assess arterial progression, phase capacity utilization, movement delay, and served volumes on a cycle-by-cycle basis.
Journal ArticleDOI
Traffic Congestion Detection from Camera Images using Deep Convolution Neural Networks
Pranamesh Chakraborty,Yaw Adu-Gyamfi,Subhadipto Poddar,Vesal Ahsani,Anuj Sharma,Soumik Sarkar +5 more
TL;DR: Although poor camera conditions at night affected the accuracy of the models, the areas under the curve from the deep models were found to be greater than 0.9 for all conditions, which shows that the models can perform well in challenging conditions as well.
Proceedings ArticleDOI
The 2018 NVIDIA AI City Challenge
Milind Naphade,Ming-Ching Chang,Anuj Sharma,David C. Anastasiu,Vamsi Krishna Jagarlamudi,Pranamesh Chakraborty,Tingting Huang,Shuo Wang,Ming-Yu Liu,Rama Chellappa,Jenq-Neng Hwang,Siwei Lyu +11 more
TL;DR: The second edition of the NVIDIA AI City Challenge provided a forum to more than 70 academic and industrial research teams to compete and solve real-world problems using traffic camera video data.
Journal ArticleDOI
Estimating dilemma zone hazard function at high speed isolated intersection
TL;DR: A dilemma zone hazard function estimating procedure to obtain the probability of traffic conflict occurring and demonstrates the potential of sensor providing richer data than an inductive loop detector can be used to further enhance the safety at signal operations.