Parallel Transportation Systems: Toward IoT-Enabled Smart Urban Traffic Control and Management

智能交通系统 先进的交通管理系统 计算机科学 智能决策支持系统 过程(计算) 分布式计算 智能代理 运输工程 系统工程 工程类 人工智能 操作系统
作者
Fenghua Zhu,Yisheng Lv,Yuanyuan Chen,Xiao Wang,Gang Xiong,Fei–Yue Wang
出处
期刊:IEEE Transactions on Intelligent Transportation Systems [Institute of Electrical and Electronics Engineers]
卷期号:21 (10): 4063-4071 被引量:380
标识
DOI:10.1109/tits.2019.2934991
摘要

IoT-driven intelligent transportation systems (ITS) have great potential and capacity to make transportation systems efficient, safe, smart, reliable, and sustainable. The IoT provides the access and driving forces of seamlessly integrating transportation systems from the physical world to the virtual counterparts in the cyber world. In this paper, we present visions and works on integrating the artificial intelligent transportation systems and the real intelligent transportation systems to create and enhance “intelligence” of IoT-enabled ITS. With the increasing ubiquitous and deep sensing capacity of IoT-enabled ITS, we can quickly create artificial transportation systems equivalent to physical transportation systems in computers, and thus have parallel intelligent transportation systems, i.e. the real intelligent transportation systems and artificial intelligent transportation systems. The evolution process of transportation system is studied in the view of the parallel world. We can use a large number of long-term iterative simulation to predict and analyze the expected results of operations. Thus, truly effective and smart ITS can be planned, designed, built, operated and used. The foundation of the parallel intelligent transportation systems is based on the ACP theory, which is composed of artificial societies, computational experiments, and parallel execution. We also present some case studies to demonstrate the effectiveness of parallel transportation systems.

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