M
Mashrur Chowdhury
Researcher at Clemson University
Publications - 219
Citations - 3740
Mashrur Chowdhury is an academic researcher from Clemson University. The author has contributed to research in topics: Intelligent transportation system & Traffic simulation. The author has an hindex of 26, co-authored 212 publications receiving 2960 citations. Previous affiliations of Mashrur Chowdhury include The Chinese University of Hong Kong & University of Dayton.
Papers
More filters
Journal ArticleDOI
A Review of Communication, Driver Characteristics, and Controls Aspects of Cooperative Adaptive Cruise Control (CACC)
Kakan Dey,Li Yan,Xujie Wang,Yue Wang,Haiying Shen,Mashrur Chowdhury,Lei Yu,Chenxi Qiu,Vivekgautham Soundararaj +8 more
TL;DR: The issues that existing CACC control modules face when considering close to ideal driving conditions are discussed, including how to keep drivers engaged in driving tasks during CACC operations.
Journal ArticleDOI
Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication in a heterogeneous wireless network – Performance evaluation
TL;DR: Field studies conducted in this research demonstrated that the use of Het-Net broadened the range and coverage of V2V and V2I communications and the application layer handoff technique to maintain seamless connectivity for CVT applications was successfully demonstrated and can be adopted in future Het -Net supported connected vehicle applications.
Journal ArticleDOI
Review of Microscopic Lane-Changing Models and Future Research Opportunities
TL;DR: A detailed review and systematic comparison of existing microscopic lane- changing models that are related to roadway traffic simulation is conducted to provide a better understanding of respective properties, including strengths and weaknesses of the lane-changing models, and to identify potential for model improvement using existing and emerging data collection technologies.
Book
Fundamentals of Intelligent Transportation Systems Planning
Mashrur Chowdhury,Adel W. Sadek +1 more
TL;DR: This book presents the essential information necessary for the successful planning of intelligent transportation systems (ITS) and serves as a practical reference for transportation operations/planning practitioners.
Journal ArticleDOI
Real-Time Highway Traffic Condition Assessment Framework Using Vehicle–Infrastructure Integration (VII) With Artificial Intelligence (AI)
TL;DR: The proposed VII-AI framework provides a reliable alternative to traditional traffic sensors in assessing traffic conditions and provides additional information, including an estimate of the incident location and the likely number of lanes blocked, which will be helpful for implementing an appropriate response strategy.