Special Session on Data-Driven Smart Logistics and Urban Parking Management

Special Session Chairs

•Prof. Pengyu Yan, University of Electronics and Science Technology of China, Chengdu, China

•A. Prof. Xiaohui Li, Chang'an University, Xi' an, China

•A. Prof. Weidong Lei, Xi'an University of Science and Technology Xi' an, China

•Dr. Mingyan Bai, University of Electronics and Science Technology of China, Chengdu, China

Introduction

In the era of artificial intelligence, the integration of data-driven technologies is revolutionizing logistics and urban traffic management, transforming traditional challenges into opportunities for innovation. As cities grow and evolve, the complexity of managing logistics and traffic systems increases, demanding smarter, more efficient solutions. The deployment of Unmanned Aerial Vehicles (UAVs) and advanced machine learning algorithms offers groundbreaking possibilities to enhance efficiency, responsiveness, and user satisfaction in smart logistics and parking management. This special session invites researchers and industry experts to explore the forefront of data-driven smart logistics and parking management. We seek submissions that delve into theoretical frameworks, algorithmic innovations, and practical implementations, with a strong emphasis on pioneering approaches and real-world applications.

Keywords

Smart Logistics; UAV Scheduling; Smart Parking; Reinforcement Learning; Online Learning Algorithms; Data-Driven Optimization; Urban Mobility; Human-AI Collaboration

Topics of Interest

Topics include but are not limited to:

•UAV Scheduling for Smart Logistics

•Reinforcement Learning Applications in Smart Logistics

•Data Analytics for Green Logistics Optimization

•Adaptive Optimization in Urban Mobility

•Smart Parking Management Systems

•Online Learning Algorithms for Parking User Preferences

•Distributed Systems for Collaborative Parking Management

•Human-AI Interaction in Logistics and Parking Management

•Multi-Agent Systems for Dynamic Resource Allocation

•AI-Driven Decision Support Systems for Urban Planning