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Special Issue: Emerging Solutions in Intelligent Vehicles, Transportation, and Logistics

Guest Editors

Prof. Wei Zhang
Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, China
Email: wei.sz.zhang@connect.polyu.hk


Prof. Jingwen Qi
Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, China
Email: jingwen.qi.94@gmail.com


Prof. Shuaian (Hans) Wang
Department of Logistics and Maritime Studies, The Hong Kong Polytechnic University, China
Email: hans.wang@polyu.edu.hk

Manuscript Topics


In recent years, technological progress has triggered a notable transformation in the realms of intelligent vehicles, transportation, and logistics. This surge of innovation has been energized by a multitude of cutting-edge technologies, including artificial intelligence (AI) for enhanced decision-making, autonomous systems driving the era of self-driving vehicles, data analytics offering both predictive and prescriptive insights, advanced sensor technologies facilitating real-time data collection, and cloud computing enabling seamless connectivity, among others. These technologies have shattered the limitations of conventional methods, propelling us toward uncharted horizons in the field of transportation and logistics.


Concurrently, we've borne witness to the extraordinary development of novel vehicles, exemplified by the rapid ascent of electric vehicles (EVs) as sustainable alternatives to traditional automobiles. In parallel, the emergence of autonomous vehicles (AVs) and electric vertical takeoff and landing (eVTOL) aircraft has ignited our imagination with the promise of reshaping personal and commercial transportation.


Simultaneously, disruptive forces such as ride-sharing services and micro-mobility solutions have introduced fresh paradigms for urban travel, seamlessly integrating on-demand mobility into our daily lives. Additionally, the landscape of transportation and logistics is further enriched by the concept of ground-air cooperation. This innovative approach envisions the harmonious collaboration between ground-based transportation and aerial systems to optimize the flow of goods and passengers. It holds the potential to revolutionize the way we think about cargo movement, offering efficient, swift, and environmentally conscious solutions for the logistics industry. Complementing these advancements, state-of-the-art algorithms have assumed a pivotal role, optimizing and enhancing the efficiency of our transportation and logistics systems.


These interwoven innovations are charting a future where intelligent vehicles, versatile travel modes, and cutting-edge algorithms converge to redefine transportation and logistics. This special issue is dedicated to capturing this ever-evolving landscape, presenting novel insights and solutions that bridge existing gaps and propel us toward transformed transportation and logistics systems. The scope of this special issue encompasses a wide range of topics, including but not limited to:


Intelligent vehicles, such as EVs, AVs, eVTOL
• Urban mobilities, such as ridesharing, on-demand transportation services
• Intelligent logistics, such as ground-air cooperation, last-mile delivery innovations
• Mathematical model and algorithms for transportation and logistics
• Optimization in transportation and logistics
• Data analytics in transportation and logistics
• Artificial Intelligence in transportation and logistics
• Decision-making in transportation and logistics


Instructions for authors
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Please submit your manuscript to online submission system
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Paper Submission

All manuscripts will be peer-reviewed before their acceptance for publication. The deadline for manuscript submission is 31 December 2024

Published Papers(8)

Research article
Optimization problems in liquefied natural gas transport and storage for multimodal transport companies
Hongyu Zhang Yiwei Wu Lu Zhen Yong Jin Shuaian Wang
2024, Volume 32, Issue 8: 4828-4844. doi: 10.3934/era.2024221
Abstract HTML PDF Cited (2) Viewed (2001)
Research article
Incorporating mobile phone data-based travel mobility analysis of metro ridership in aboveground and underground layers
Jiping Xing Xiaohong Jiang Yu Yuan Wei Liu
2024, Volume 32, Issue 7: 4472-4494. doi: 10.3934/era.2024202
Abstract HTML PDF Cited (2) Viewed (1335)
Research article
Traffic flow prediction with a multi-dimensional feature input: A new method based on attention mechanisms
Shaohu Zhang Jianxiao Ma Boshuo Geng Hanbin Wang
2024, Volume 32, Issue 2: 979-1002. doi: 10.3934/era.2024048
Abstract HTML PDF Cited (1) Viewed (2120)
Research article
Design of a novel multimodal optimization algorithm and its application in logistics optimization
Weishang Gao Qin Gao Lijie Sun Yue Chen
2024, Volume 32, Issue 3: 1946-1972. doi: 10.3934/era.2024089
Abstract HTML PDF Cited (1) Viewed (1687)
Research article
Nonlinear modeling and interior point algorithm for the material flow optimization in petroleum refinery
Fenglian Dong Dongdong Ge Lei Yang Zhiwei Wei Sichen Guo Hekai Xu
2024, Volume 32, Issue 2: 915-927. doi: 10.3934/era.2024044
Abstract HTML PDF Viewed (1552)
Research article
Hybrid short-term traffic flow prediction based on the effect of non-linear sequence noise
Gang Cheng Yadong Liu
2024, Volume 32, Issue 2: 707-732. doi: 10.3934/era.2024034
Abstract HTML PDF Cited (1) Viewed (1712)
Research article
Enhancing passenger comfort and operator efficiency through multi-objective bus timetable optimization
Gang Cheng Yijie He
2024, Volume 32, Issue 1: 565-583. doi: 10.3934/era.2024028
Abstract HTML PDF Viewed (2357)
Research article
Dynamic coordinated strategy for parking guidance in a mixed driving parking lot involving human-driven and autonomous vehicles
Zhiyuan Wang Chu Zhang Shaopei Xue Yinjie Luo Jun Chen Wei Wang Xingchen Yan
2024, Volume 32, Issue 1: 523-550. doi: 10.3934/era.2024026
Abstract HTML PDF Viewed (2282)