Evaluating the Operational Performance of Road Intersections by Mining Trajectory Data Streams

交通拥堵是指当交通需求接近道路(或道路沿线交叉口)的**通行能力时，交通网络上出现的一种情况。它的特点是速度较慢，出行时间较长，**车辆排队增加，并与巨大的社会、经济和环境成本相关。道路**交叉口是穿越公路网时遇到的最复杂的布局之一，**这些位置发生的事故比例很高。因此，改善它们的**业务表现至关重要，因为这可以大大提高整个运输网络的效率。提高交叉口效率的传统方法是基于对静态数据的分析**或专家意见。然而，今天的车辆不再是独立的交通工具。由于车辆到车辆(V2V)和车辆到基础设施(V2I)通信技术的**进步，**通过持续监测交通**信息和使车辆驾驶员能够感知情况，可以**提高道路交叉口的安全性和效率。**在这个项目中，我们的目标是利用大数据挖掘和机器学习技术，通过挖掘实时的V2I数据来持续监测**道路交叉口的运营性能。**这些方法成功的一个关键是所提供分析的质量和及时性。这项研究的预期结果有两方面：(I)提高了道路交叉口的安全性和效率，以及(Ii)以数据为导向的方法来评估**道路交叉口的运行性能。**拟议的研究合作符合加拿大的创新议程。在大数据分析和机器学习的**交集中进行研究，有可能吸引来自**世界**的最聪明的学生，同时留住国内人才。

Traffic congestion describes a situation on transport networks that occurs when demand approaches the**capacity of a road (or of the intersections along the road). It is characterized by slower speeds, longer trip times,**and increased vehicle queues and is associated to significant social, economic and environmental costs. Road**intersections represent one of the most complex configurations encountered when traversing road networks and**a high percentage of accidents occur at these locations. It is therefore of vital importance to improve their**operational performance, as that can significantly contribute towards the efficiency of the whole transport**network. Traditional approaches to improve the efficiency of intersections are based on analysis of static data**or expert opinions. However, today's vehicles are no longer stand-alone transportation means. Due to the**advancements on Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication technologies it**is possible to enhance safety and improve road intersection efficiency by continuously monitoring traffic**information and enabling situational awareness of vehicle drivers.**In this project, we aim to leverage big data mining and machine learning techniques to continuously monitor**the operational performance of road intersections through mining real-time V2I data. A key to the success of**these methods is the quality and timeliness of the analysis provided. The anticipated outcome of the research is**twofold: (i) an increased safety and efficiency of road intersections, and (ii) a data-driven approach to evaluate**road intersection operational performance.**The proposed research collaboration aligns with Canada's Innovation Agenda. Conducting research in the**intersection of big data analytics and machine learning has the potential to attract the brightest students from**around the world, while keeping domestic talent here.