Advances in Perception, Control and Optimization Methods in Intelligent Transportation Systems

Dear Colleagues,

In this Special Issue titled “Advances in Perception, Control, and Optimization Methods in Intelligent Transportation Systems”, we focus on the integration of operation control and intelligent perception technologies to advance the development of intelligent transportation systems (ITS). This Special Issue highlights how advanced mathematical and computational methods are applied to optimize the performance of modern transportation systems.

A key aspect of this issue is the improvement in traffic operation efficiency and safety within the context of increasing urbanization and technological advancements. Specifically, in the realm of ITS operation control, the issue underscores the importance of real-time monitoring and adjustment of traffic participants (cars, trains, passengers, and so on) to reduce congestion and enhance safety. It showcases innovative control strategies like model predictive control and reinforcement learning, tailored for the intricacies of transportation networks.

The incorporation of intelligent perception technologies offers new dimensions in understanding and improving the operations of transportation systems. By leveraging sensors, cameras, and other data acquisition technologies, intelligent perception not only enhances real-time awareness of the traffic environment but also facilitates the development of more accurate and adaptive control strategies.

Moreover, this Special Issue delves into optimization methods that are crucial for enhancing resource allocation, scheduling, and routing decisions in ITS. It covers advanced optimization techniques such as linear and nonlinear programming, evolutionary algorithms, and swarm intelligence, aimed at addressing the complex challenges in transportation planning and management.

By integrating mathematical models with cutting-edge technologies like artificial intelligence, machine learning, and big data analytics, this Special Issue demonstrates how to enhance the efficiency and resilience of transportation systems. These interdisciplinary approaches support data-driven decision-making and adaptive control strategies, enabling transportation networks to dynamically respond to changing conditions and user demands.

In summary, this Special Issue emphasizes the critical role of advanced mathematics, control, and optimization techniques in evolving intelligent transportation systems. Through the collaborative efforts of mathematicians, engineers, and transportation experts, we aim to accelerate the development of innovative and sustainable solutions, leading to safer, more efficient, and environmentally friendly transportation networks in the future.

Dr. Haifeng Song
Dr. Min Zhou
Prof. Dr. Xiaoqing Zeng
Guest Editors

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• intelligent transportation systems (ITS)
• control theory in transportation
• traffic flow optimization
• model predictive control (MPC)
• intelligent perception technologies
• machine learning for ITS
• advanced routing algorithms
• optimization methods in transportation
• autonomous vehicle technologies
• sustainable urban transport