Stability and Responsiveness of Real-Time Traffic Adaptive Systems

在这项研究中，实时交通自适应系统被建模为反馈控制系统，其中新的决策(交通网络信号控制中的“相位”和高速公路控制中的匝道计量率)是基于来自监控交通的传感器的“反馈”来实现的。反馈包括(I)测量系统，(Ii)估计/预测交通的系统，以及(Iii)计算适当决策/控制的决策/控制系统。在开发这些系统时，提出了(I)反馈控制系统的设计、(Ii)系统的稳定性和(Iii)系统的“响应性”的问题。研究将针对这些问题并特别集中于：(1)表征反馈中的通信/计算延迟(包括获得测量、处理它们、执行嵌入的决策算法、处理结果并将其下载到决策执行器/信号的计算周期)，(2)表征反馈中的设计参数的影响，例如决策算法的“决策地平线”、“控制更新间隔”和“时空分辨率”，(3)研究系统的稳定性，在某种意义上它是趋于“平衡”还是在极限内“循环”，以及(4)调查反馈系统对临时短期情况(事件、交通高峰等)的响应情况。以及缓慢变化的长期变化(例如，总体交通量的逐渐变化)。除了基础研究的贡献和博士生的参与，预计(1)关于交通适应系统稳定性和响应性的结果将被引入课程，以及(2)对交通适应系统的分析将对USDOT和计划在其管辖范围内实施最先进系统的交通机构非常有用。

In this research, Real-time Traffic Adaptive Systems are modeled as Feedback Control Systems, where new decisions (the "phasing" in traffic network signal control and the ramp-metering rates in freeway control) are implemented based on "feedback" from sensors that monitor traffic. The feedback includes (i) a measurement system, (ii) a system that estimates/predicts traffic, and (iii) a decision/control system that computes appropriate decision/controls. In developing these systems, issues are raised on (i) the design of the feedback control system, (ii) the stability of the system, and (iii) the "responsiveness" of the system. The research will address these issues and particularly focus on: (1) Characterizing the communication/computational delays in the feedback (including the computational cycle of getting measurements, processing them, executing the embedded decision-making algorithms, processing the result, and downloading it to decision actuators /signals), (2) Characterizing the effect of design parameters in the feedback, such as "decision horizon", "control update interval", and "space-time resolution" of the decision-making algorithms, (3) Studying the stability of the system, in the sense does it go to an "equilibrium" or does it "cycle" in the limit, and (4) Investigating how well the feedback system responds to temporary short-term conditions (incidents, traffic surges, etc.) and slow varying long-term changes (e.g., gradual changes in the overall traffic volumes). In addition to basic research contributions and involvement of PhD students in the effort, it is anticipated that (1) the results on stability and responsiveness of traffic adaptive systems will be introduced into curricula, and (2) the analysis of the traffic adaptive systems would be very useful to USDOT and traffic agencies that are planning to implement state of-the-art systems within their jurisdictions.