نبذة مختصرة : Urban road traffic network optimization based on the Internet of Things (IoT) is one of the important methods to reduce vehicle exhaust and ease traffic congestion. A two-level planning model on road traffic network optimization in IoT and the IS-APCPSO algorithm is deployed, which can effectively solve the above problems. The experimental results show that the total vehicle emissions of the proposed scheme are lower than those of traditional schemes. Moreover, the real-time perception, interactive coupling, and coordinated control of “people-vehicle-road-environment” can be achieved through the use of the IoT. We discuss the sensitivity of the model to establish a scene selection that takes into account different regional and road traffic conditions, avoiding the subjective randomness in model parameter selection. A novel multi-objective method based on IoT proposed in this paper helps to alleviate “urban diseases,” such as traffic congestion, vehicle emissions, and energy waste, and to emphasize the overall benefits of energy-saving and emission reduction in urban road networks. By setting up traffic lights reasonably and guiding the driver behavior, the integrated control and management of traffic flow and exhaust emission under multiple driving cycles are realized.
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