Application of System Engineering and Complex Theory in Transportation

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Engineering".

Deadline for manuscript submissions: 15 June 2024 | Viewed by 1810

Special Issue Editors

School of Modern Posts, Xi'an University of Posts and Telecommunications, Xi’an 710121, China
Interests: transportation system optimization; traffic flow theory; pedestrian safety; passenger crowd dynamics and evacuation management
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Guest Editor
School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China
Interests: public transport planning and management; transportation modeling and optimization; transportation emergency management

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Guest Editor
Jiangsu Key Laboratory of Urban ITS, Jiangsu Province Collaborative Innovation Center of Modern Urban Traffic Technologies, School of Transportation, Southeast University, 2 Dongnandaxue Rd, Nanjing 211189, China
Interests: active mode traffic; active traffic safety; human factors; intelligent transportation system
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

System engineering, with its comprehensive approach to managing complex systems, plays a crucial role in addressing the inherent complexities of modern transportation systems. Complex theory, on the other hand, provides a framework for understanding the unpredictable and dynamic nature of transportation systems, enabling us to delve into the interactions among various elements within transportation system. This Special Issue focuses on exploring the latest research developments in the application of system engineering and complexity theory in the field of transportation, aiming to determine the potential of these disciplines in enhancing the efficiency, sustainability, and adaptability of transportation systems. The contents of this Special Issue will concentrate on new methods and approaches in system engineering for designing, analyzing, and implementing transportation solutions. We will also explore the role of complex theory in helping to understand and model nonlinear behaviors within transportation systems, aiming for more accurate predictions and management strategies. Additionally, this Special Issue pays special attention to potential research areas such as the integration of autonomous vehicles into existing transportation ecosystems, the application of intelligent technologies for dynamic traffic control, and the development of resilient infrastructure capable of adapting to changing demands and environmental conditions. Through these topics, we hope to provide a comprehensive overview of the current trends, challenges, and future directions in the application of system engineering and complexity theory in transportation. We eagerly invite researchers and practitioners who are pushing the boundaries in these fields to share their insights and discoveries. Your contributions will undoubtedly help shape the future of transportation systems, making them more intelligent, adaptable, and in-tune with rapidly evolving global needs.

Both original research and review works are welcome for submission. Research topics of interest include, but are not limited to, the following:

  • Smart city transportation systems;
  • Passenger behavioral analysis and travel mode choice in transportation systems;
  • Coordination and synchronization of transportation systems;
  • Relicense assessment and enhancement of transportation systems;
  • Disruption management in transportation systems;
  • Human factors and behavioral analysis in transportation systems;
  • Collaborative and cooperative systems in transportation;
  • Sustainable transportation planning and policy making;
  • Application of complex theory in emergency response and disaster management;
  • System engineering approaches to multimodal transportation networks;
  • Economic and environmental impact assessments of transportation systems;
  • Integration of renewable energy sources in transportation systems;
  • Advanced traffic prediction models using ai and machine learning;
  • Impact of autonomous vehicles on traffic dynamics and control;
  • Innovative materials and technologies for transportation infrastructure.

Dr. Shuqi Xue
Dr. Yun Wang
Dr. Xiaomeng Shi
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • system engineering
  • complex theory
  • transportation systems
  • transportation optimization
  • transportation control
  • transportation management
  • sustainable transportation
  • traffic dynamics
  • traffic behaviors
  • intelligent transportation

Published Papers (2 papers)

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Research

25 pages, 2727 KiB  
Article
Two-Stage Delivery System for Last Mile Logistics in Rural Areas: Truck–Drone Approach
by Debao Dai, Hanqi Cai, Liang Ye and Wei Shao
Systems 2024, 12(4), 121; https://doi.org/10.3390/systems12040121 - 06 Apr 2024
Viewed by 611
Abstract
In rural areas of China, the challenges of efficient and cost-effective distribution are exacerbated by underdeveloped infrastructure and low population density, with last mile logistics distribution posing a significant obstacle. To address the gap in drone application for last mile logistics in rural [...] Read more.
In rural areas of China, the challenges of efficient and cost-effective distribution are exacerbated by underdeveloped infrastructure and low population density, with last mile logistics distribution posing a significant obstacle. To address the gap in drone application for last mile logistics in rural areas, a truck–drone distribution model was developed based on the specific conditions of rural regions. The improved fuzzy C-means algorithm (FCM) and genetic simulated annealing algorithm (GASA) were employed to tackle real−world cases in rural areas. The focus of the truck–drone system is to optimize the rural logistics distribution process, reduce delivery time, and minimize costs while considering factors such as maximum mileage of trucks and drones as well as customer priority. Compared to traditional methods, this system has demonstrated notable improvements in distribution efficiency and cost reduction, offering valuable insights for practical drone applications in last mile rural logistics. Full article
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20 pages, 6287 KiB  
Article
A Dynamic Collision Risk Assessment Model for the Traffic Flow on Expressways in Urban Agglomerations in North China
by Bing Li, Xiaoduan Sun, Yulong He and Meng Zhang
Systems 2024, 12(3), 86; https://doi.org/10.3390/systems12030086 - 06 Mar 2024
Viewed by 839
Abstract
Expressways in urban agglomerations are important in connecting cities, thus attracting great attention from researchers in the expressways risk assessment. However, there is a lack of safety assessment models suitable for the characteristics of expressways in Chinese urban agglomerations, and the nature and [...] Read more.
Expressways in urban agglomerations are important in connecting cities, thus attracting great attention from researchers in the expressways risk assessment. However, there is a lack of safety assessment models suitable for the characteristics of expressways in Chinese urban agglomerations, and the nature and mode of dynamic risks on Chinese highways are still unclear. Therefore, this study adopts the Adaptive Neural Fuzzy Inference System (ANFIS) and the method of decision tree, combined with data from the Beijing section of the Beijing Harbin Expressway, to model the risk of accident-prone highways in urban agglomerations. To determine the optimal model, we evaluated the model’s bias at different time intervals. In addition, key factors affecting highway safety were analyzed, providing scientific support for the risk prevention of highways in urban agglomerations in China. Full article
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