标题： 城市交通优化集成策略：预测、自适应信号控制和通过消息传递的分布式通信 显示英文标题

标题： Integrated Strategy for Urban Traffic Optimization: Prediction, Adaptive Signal Control, and Distributed Communication via Messaging

摘要： 本文介绍了一种集成方法来优化城市交通，该方法通过结合车辆流量的预测建模、自适应交通信号控制以及通过分布式消息传递的模块化集成架构。利用来自各种传感器的实时数据，系统能够预测交通波动，并动态调整信号相位持续时间以减少延迟和改善交通流。这种前馈式调整得到了模拟退火算法和强化学习算法的支持，还提高了能源效率，减少了污染物排放，并有效应对意外事件（恶劣天气、事故或临时聚集）。在现实城市环境中进行的初步仿真显示平均等待时间显著减少。未来的发展包括整合来自联网车辆的数据、集成新的交通方式，并不断改进预测模型以应对城市交通日益增长的挑战。 显示英文摘要

摘要： This work introduces an integrated approach to optimizing urban traffic by combining predictive modeling of vehicle flow, adaptive traffic signal control, and a modular integration architecture through distributed messaging. Using real-time data from various sensors, the system anticipates traffic fluctuations and dynamically adjusts signal phase durations to minimize delays and improve traffic flow. This proactive adjustment, supported by algorithms inspired by simulated annealing and reinforcement learning, also enhances energy efficiency, reduces pollutant emissions, and responds effectively to unexpected events (adverse weather, accidents, or temporary gatherings). Preliminary simulations conducted in a realistic urban environment demonstrate a significant reduction in average waiting times. Future developments include incorporating data from connected vehicles, integrating new modes of transport, and continuously refining predictive models to address the growing challenges of urban mobility.