CAREER: System-wide Traffic Condition Monitoring and State Estimation for Intelligent Transportation Systems

交通拥堵仍然是美国城市面临的最紧迫的问题之一。智能交通系统(ITS)为可持续解决城市交通问题提供了必要的系统视角。在20世纪的最后十年，数亿美元被投入到它的监视、检测和旅客信息技术上。在这第一代智能交通系统中，仍然有很大程度上尚未开发的潜力，即利用丰富的遥感数据进行自动化、时间紧迫的管理和控制。下一代智能交通系统需要多尺度的系统范围预测和状态估计，以支持主动而不是被动的交通系统管理。这一职业发展计划将为智能交通系统的全系统交通状况监测和状态估计提供综合研究和教育框架。研究活动将包括：(1)开发整个ITS系统的交通状况监测和预测框架；(2)基于季节性ARIMA的卡尔曼滤波用于单变量预测；(3)将连续统交通流理论应用于一步系统预测；以及(4)基于连续统理论的事件检测、缺失数据估计和冲击波传播预测。第一个研究活动范围广泛，将为其预测研究提供类型学重点，并为新课程开发和课程改进提供指导，以支持21世纪其从业人员和研究人员的教育和培训。具体的教育活动将包括(1)本科课程的发展和加强，以增加学生接触信息技术和基础设施的可持续性；(2)开发与其研究活动直接相关的新的交通流理论课程；(3)通过研究生领导的跨学科研究团队，让本科生参与正在进行的ITS研究活动；(4)通过针对新生和研究生的各种计划，积极从传统上代表不足的群体中招生。这些研究和教育活动将围绕一个新的校园交通运营中心和ITS实验室进行建设和整合。该实验室将提供对全系统交通状况数据和全运动监控视频的直接访问。这种随时可获得的全系统数据将大大加强研究和研究生教育工作。将特别重视通过课程项目和本科生参与其研究团队，让本科生接触到它的研究和开发。ITS实验室还将作为招生的展示窗口，包括努力吸引女性和代表性不足的少数族裔进入土木工程。

Traffic congestion continues to be one of the most pressing problems facing urban America. Intelligent transportation systems (ITS) provide the systems perspective needed for sustainable solutions to urban mobility problems. During the final decade of the 20th century, hundreds of millions of dollars were invested in ITS surveillance, detection, and traveler information technologies. In this first generation ITS there remains a largely untapped potential to exploit the wealth of remotely sensed data for automated, time critical management and control. Multi-scale system-wide forecasting and state estimation is required for next generation ITS to support proactive rather than reactive transportation system management. This career development plan will provide an integrated research and education framework for system-wide traffic condition monitoring and state estimation for intelligent transportation systems. Research activities will include: (1) development of a system-wide ITS traffic condition monitoring and forecasting framework, (2) seasonal ARIMA based Kalman filtering for univariate forecasts, (3) application of continuum traffic flow theory to one-step system forecasts, and (4) continuum theory-based incident detection, missing data estimation, and shock wave propagation prediction. The first research activity is broad in scope and will provide a typological focus for ITS forecasting research and guidance for new course development and course enhancements to support the education and training of 21st century ITS practitioners and researchers. Specific educational activities will include (1) undergraduate course development and enhancement to increase student exposure to information technologies and infrastructure sustainability, (2) development of a new traffic flow theory course directly linked with ITS research activities, (3) involvement of undergraduates in ongoing ITS research activities through interdisciplinary research teams under graduate student leadership, and (4) active recruitment of students from traditionally underrepresented groups through various programs aimed at incoming students and graduate school candidates.These research and educational activities will be built and integrated around a new campus traffic operation center and ITS lab. The lab will provide direct access to system-wide traffic condition data and full motion surveillance video. This ready access to system-wide data will greatly enhance the research and graduate education efforts. Special emphasis will be placed on exposing undergraduates to ITS research and development through course projects and undergraduate participation in ITS research teams. The ITS lab will also serve as a showcase for student recruitment, including efforts to attract women and underrepresented minorities to civil engineering.