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AbstractRed-light-running (RLR) is an important reason for the large number of intersection-related fatalities, injuries, and other losses. The accurate RLR prediction can effectively reduce crashes caused by RLR behavior. The RLR prediction is usually composed of two parts: the vehicle’s stop-or-go behavior and the arrival time when the vehicle reaches the stop line. Previous stop-or-go prediction models are usually based on embedded traffic sensors using machine learning algorithms. While based on the continuous trajectories collected by radar sensors, RLR prediction can be conducted more effectively. In this paper, a probabilistic stop-or-go prediction model based on the Bayesian network (BN) is proposed for RLR prediction. We extend the deterministic output into the probabilistic output, which provides decision-makers with greater autonomy. The causality of BN improves the interpretability of the prediction model. The BN model is calibrated and tested by the continuous trajectories data measured by radar sensors installed at a signalized intersection. We not only consider the movement measurements of individual vehicles (e.g., speed and acceleration), but also take into account the car-following behavior. As a comparison, different machine learning models and the model based on the inductive loop detection (ILD) are adopted. The results show that the proposed BN model has a high prediction accuracy and performs better in the feature interpretation. This paper provides a new way for probabilistic RLR prediction based on continuous trajectories, which will significantly improve traffic safety of signalized intersections. 相似文献
353.
KONG Qiao-ling MA Jie State Key Laboratory of Ocean Engineering Shanghai Jiaotong University Shanghai China 《船舶与海洋工程学报》2007,6(4)
The phase change characteristic of the power source of an underwater glider propelled by the ocean's thermal energy is the key factor in glider attitude control. A numerical model has been established based on the enthalpy method to analyze the phase change heat transfer process under convective boundary conditions. Phase change is not an isothermal process,but one that occurs at a range of temperature. The total melting time of the material is very sensitive to the surrounding temperature. When the temperature of the surroundings decreases 8 degrees,the total melting time increases 1.8 times. But variations in surrounding temperature have little effect on the initial temperature of phase change,and the slope of the temperature time history curve remains the same. However,the temperature at which phase change is completed decreases significantly. Our research shows that the phase change process is also affected by container size,boundary conditions,and the power source's cross sectional area. Materials stored in 3 cylindrical containers with a diameter of 38mm needed the shortest phase change time. Our conclusions should be helpful in effective design of underwater glider power systems. 相似文献
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以某大型码头项目设计为案例,搭建云端协同平台开展各专业的BIM协同设计,基于三维可视化的场景,对项目方案进行了设计优化。各专业模型通过云端协同方式实时链接进行总装,项目协调员根据设计成果进行碰撞检测,及时发现设计问题。同时,针对BIM在设计阶段及施工阶段的需求,对BIM设计软件中的部分功能进行了二次开发,拓展BIM应用价值,更好地推动BIM技术在项目全生命周期中的落地和工程信息的流转。结合BIM技术在本项目的研究与应用,本文总结出了一套行之有效的BIM设计应用技术路线和解决方案,为BIM技术在码头设计中的应用与推广提供实际借鉴意义。 相似文献
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本文结合某港散货港区智慧港口规划项目,介绍了该港南作业区智能化项目的核心在于构建一套适应现代散杂货港口发展趋势、突破传统散货港口作业模式的全新港口智能化系统.本次规划将物联网、大数据技术、AI人工智能、5G等新型基础设施与生产业务融合,创新生产作业流程及资源配置,显著提高港口的作业运营能力、物流协同能力、口岸支持能力、... 相似文献
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为改善城市常规公交运营效率,提出基于模拟退火-自适应布谷鸟算法的公交调度优化模型.通过结合线路实际客流数据反映的客流特征,建立考虑公交公司和乘客双方利益的公交调度优化模型;改进布谷鸟算法固定步长并加入模拟退火算法退火操作,设计模拟退火-自适应布谷鸟算法,改善寻优过程中跳出局部最优解而全局寻优的能力;以福州125路公交线... 相似文献