Linrui Ma, Chun Hei Lo, Xinyu Wang, Peng Lu, Xihao Yuan, Hanting Chen, Kai Han, Xinghao Chen, Chengjun Zhan, Hanlin xu, Yichun Yin, Lifeng Shang, Feng Wen, Boxing Chen, Yufei Cui. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.

A number of existing studies have attempted to predict freeway incident duration or incident clearance time. Because lane blockage is the main cause of congestion during freeway incidents, it is more beneficial to predict the lane clearance time instead of the incident clearance time for incidents that involve lane blockages. However, previous studies have not developed prediction models for the lane clearance time. This paper utilizes the M5P tree algorithm for lane clearance time prediction, which has advantages, compared with traditional prediction algorithms. These advantages include the M5P tree algorithm's ability to deal with categorical and continuous variables and variables with missing values. The developed model shows that there are a number of variables that affect the lane clearance time, including the number of lanes blocked, time of day, types and number of vehicles involved, the response by the Severe Incident Response Vehicle (SIRV), and traffic management center response and verification times. Comparison results show that the developed model can generally achieve better prediction results than the traditional regression and decision tree models.

As the development of the Internet continues, congestion control has become a big issue to the computer network society. Most congestion control schemes fall into two categories, end-to-end and hop-by-hop schemes. We propose a novel hop-by-hop algorithm that originates from a classical traffic control algorithm. The experimental results show that our proposed algorithm can achieve short delays and quick responses to the congestion situations and cause no packet loss. It can also minimize the bandwidth requirement and achieve a very high buffer usage level for nodes along the transmission path.

Abstract As an environmental phenomenon, hurricanes cause significant property damage and loss of life in coastal areas almost every year. Research concerning hurricanes and their aftermath is gaining more and more attention nowadays. This paper presents our work in designing and building a Web‐based distributed software system that can be used for the statistical analysis and projection of hurricane occurrences. Firstly, our system is a large‐scale system and can handle the huge amount of hurricane data and intensive computations in hurricane data analysis and projection. Secondly, it is a distributed system, which allows multiple users at different locations to access the system simultaneously and to share and exchange the data and data model. Thirdly, our system is a database‐centered system where the Oracle database is employed to store and manage the large amount of hurricane data, the hurricane model and the projection results. Finally, a three‐tier architecture has been adopted to make our system robust and resistant to the potential change in the lifetime of the system. This paper focuses on the three‐tier system architecture, describing the design and implementation of the components at each layer. Copyright © 2004 John Wiley & Sons, Ltd.