Study of narrow waterways congestion based on automatic identification system (AIS) data: A case study of Houston Ship Channel
出版年份 2021 全文链接
标题
Study of narrow waterways congestion based on automatic identification system (AIS) data: A case study of Houston Ship Channel
作者
关键词
Maritime transport system, Waterway congestion, Quantifying congestion, AIS data, Houston Ship Channel
出版物
Journal of Ocean Engineering and Science
Volume -, Issue -, Pages -
出版商
Elsevier BV
发表日期
2021-10-31
DOI
10.1016/j.joes.2021.10.010
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Ship behavior prediction via trajectory extraction-based clustering for maritime situation awareness
- (2021) Brian Murray et al. Journal of Ocean Engineering and Science
- Characterizing multicity urban traffic conditions using crowdsourced data
- (2019) Divya Jayakumar Nair et al. PLoS One
- Using big GPS trajectory data analytics for vehicle miles traveled estimation
- (2019) Junchuan Fan et al. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES
- The Maturity of Automatic Identification Systems (AIS) and Its Implications for Innovation
- (2019) EunSu Lee et al. Journal of Marine Science and Engineering
- Using Empirical Data to Quantify Port Resilience: Hurricane Matthew and the Southeastern Seaboard
- (2018) Katherine F. Touzinsky et al. JOURNAL OF WATERWAY PORT COASTAL AND OCEAN ENGINEERING
- How can Automatic Identification System (AIS) data be used for maritime spatial planning?
- (2018) M. Le Tixerant et al. OCEAN & COASTAL MANAGEMENT
- Simulation modeling of Houston Ship Channel vessel traffic for optimal closure scheduling
- (2018) Behnam Rahimikelarijani et al. SIMULATION MODELLING PRACTICE AND THEORY
- The waterway ship scheduling problem
- (2018) Eduardo Lalla-Ruiz et al. TRANSPORTATION RESEARCH PART D-TRANSPORT AND ENVIRONMENT
- Using Empirical Data to Quantify Port Resilience: Hurricane Matthew and the Southeastern Seaboard
- (2018) Katherine F. Touzinsky et al. JOURNAL OF WATERWAY PORT COASTAL AND OCEAN ENGINEERING
- Research on road traffic congestion index based on comprehensive parameters: Taking Dalian city as an example
- (2018) Wan-Xiang Wang et al. Advances in Mechanical Engineering
- Developing and Implementing a Port Fluidity Performance Measurement Methodology using Automatic Identification System Data
- (2018) C. James Kruse et al. TRANSPORTATION RESEARCH RECORD
- Walkability index across trip purposes
- (2018) Meeghat Habibian et al. Sustainable Cities and Society
- Influence of external conditions and vessel encounters on vessel behavior in ports and waterways using Automatic Identification System data
- (2017) Yaqing Shu et al. OCEAN ENGINEERING
- Big AIS data based spatial-temporal analyses of ship traffic in Singapore port waters
- (2017) Liye Zhang et al. TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW
- Measuring Performance on Two-Lane Highways
- (2017) Ahmed Al-Kaisy et al. TRANSPORTATION RESEARCH RECORD
- Comparison study on AIS data of ship traffic behavior
- (2015) Fangliang Xiao et al. OCEAN ENGINEERING
- Visual Traffic Jam Analysis Based on Trajectory Data
- (2013) Zuchao Wang et al. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS
- Inference of Single Vessel Behaviour with Incomplete Satellite-based AIS Data
- (2013) Changqing Liu et al. JOURNAL OF NAVIGATION
- Vessel Speed, Course, and Path Analysis in the Botlek Area of the Port of Rotterdam, Netherlands
- (2013) Yaqing Shu et al. TRANSPORTATION RESEARCH RECORD
- Use of Data from Automatic Identification Systems to Generate Inland Waterway Trip Information
- (2013) James P. Dobbins et al. TRANSPORTATION RESEARCH RECORD
- Study on collision avoidance in busy waterways by using AIS data
- (2010) Jun Min Mou et al. OCEAN ENGINEERING
- Indicators of Performance on Two-Lane Rural Highways
- (2009) Ahmed Al-Kaisy et al. TRANSPORTATION RESEARCH RECORD
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreCreate your own webinar
Interested in hosting your own webinar? Check the schedule and propose your idea to the Peeref Content Team.
Create Now