Browsing by Author "Yu, Tungsheng"

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    On-line Traffic Signalization using Robust Feedback Control
    Yu, Tungsheng (Virginia Tech, 1997-12-18)
    The traffic signal affects the life of virtually everyone every day. The effectiveness of signal systems can reduce the incidence of delays, stops, fuel consumption, emission of pollutants, and accidents. The problems related to rapid growth in traffic congestion call for more effective traffic signalization using robust feedback control methodology. Online traffic-responsive signalization is based on real-time traffic conditions and selects cycle, split, phase, and offset for the intersection according to detector data. A robust traffic feedback control begins with assembling traffic demands, traffic facility supply, and feedback control law for the existing traffic operating environment. This information serves the input to the traffic control process which in turn provides an output in terms of the desired performance under varying conditions. Traffic signalization belongs to a class of hybrid systems since the differential equations model the continuous behavior of the traffic flow dynamics and finite-state machines model the discrete state changes of the controller. A complicating aspect, due to the state-space constraint that queue lengths are necessarily nonnegative, is that the continuous-time system dynamics is actually the projection of a smooth system of ordinary differential equations. This also leads to discontinuities in the boundary dynamics of a sort common in queueing problems. The project is concerned with the design of a feedback controller to minimize accumulated queue lengths in the presence of unknown inflow disturbances at an isolated intersection and a traffic network with some signalized intersections. A dynamical system has finite L₂-gain if it is dissipative in some sense. Therefore, the Hinfinity-control problem turns to designing a controller such that the resulting closed loop system is dissipative, and correspondingly there exists a storage function. The major contributions of this thesis include 1) to propose state space models for both isolated multi-phase intersections and a class of queueing networks; 2) to formulate Hinfinity problems for the control systems with persistent disturbances; 3) to present the projection dynamics aspects of the problem to account for the constraints on the state variables; 4) formally to study this problem as a hybrid system; 5) to derive traffic-actuated feedback control laws for the multi-phase intersections. Though we have mathematically presented a robust feedback solution for the traffic signalization, there still remains some distance before the physical implementation. A robust adaptive control is an interesting research area for the future traffic signalization.
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    Traffic flow modeling in highway networks
    Yu, Tungsheng (Virginia Tech, 1992)
    The emergence of the Advanced Traffic Management System poses new challenges in traffic flow modeling of urban areas. The motivation of this project is to produce working freeway traffic simulations within a reasonable time-scale. This project. describes a hybrid traffic modeling approach, which is a combination of microscopic and macroscopic traffic modeling techniques. The traffic stream is composed of individual vehicles, while the interactions in the traffic stream are modeled macroscopically using the average speed-density relationship. All existing freeway simulation models use the time-driven approach which advances the simulation clock after each fixed time-slice. However, this approach has a limitation of capturing the dynamic nature of traffic flow. The project proposes a new assumption of vehicular movement. This assumption leads to an easy implementation of a traffic simulation model using the event-driven approach which advances the simulation clock from one event to the next. The event-driven traffic model provides a new tool for the development of dynamic freeway simulation/assignment models. A number of experimental results are provided from an empirical comparison of the event-driven approach versus the time-driven approach. These results indicate that the event-driven simulation model is competitive with the time-driven simulation model in both accuracy and efficiency. Finally, specific potential directions for future research are pinpointed.