Modeling, Estimation and Control of Traffic
- Author(s): Su, Dongyan
- Advisor(s): Horowitz, Roberto
- et al.
This dissertation studies a series of freeway and arterial traffic modeling, estimation and control methodologies.
First, it investigates the Link-Node Cell Transmission Model's (LN-CTM's) ability to model arterial traffic. The LN-CTM is a modification of the cell transmission model developed by Daganzo. The investigation utilizes traffic data collected on an arterial segment in Los Angeles, California, and a link-node cell transmission model, with some adaptations to the arterial traffic, is constructed for the studied location. The simulated flow and the simulation travel time were compared with field measurements to evaluate the modeling accuracy.
Second, an algorithm for estimating turning proportions is proposed in this dissertation. The knowledge about turning proportions at street intersections is a frequent input for traffic models, but it is often difficult to measure directly. Compared with previous estimation methods used to solve this problem, the proposed method can be used with only half the detectors employed in the conventional complete detector configuration. The proposed method formulates the estimation problem as a constrained least squares problem, and a recursive solving procedure is given. A simulation study was carried out to demonstrate the accuracy and efficiency of the proposed algorithm.
In addition to addressing arterial traffic modeling and estimation problems, this dissertation also studies a freeway traffic control strategy and a freeway and arterial coordinated control strategy. It presents a coordinated control strategy of variable speed limits (VSL) and ramp metering to address freeway congestion caused by weaving effects. In this strategy, variable speed limits are designed to maximize the bottleneck flow, and ramp metering is designed to minimize travel time in a model predictive control frame work. A microscopic simulation based on the I-80 at Emeryville, California was built to evaluate the strategy, and the results showed that the traffic performance was significantly improved .
Following the freeway control study, this dissertation discusses the coordinated control of freeways and arterials. In current practice, traffic controls on freeways and on arterials are independent. In order to coordinate these two systems for better performance, a control strategy covering the freeway ramp metering and the signal control at the adjacent intersection is developed. This control strategy uses upstream ALINEA, which is a well-known control algorithm, for ramp metering to locally maximize freeway throughput. For the intersection signal control, the proposed control strategy distributes green splits by taking into account both the available on-ramp space and the demands of all intersection movements. A microscopic simulation of traffic in an arterial intersection with flow discharge to a freeway on-ramp, which is calibrated using the data collected at San Jose, California, is created to evaluate the performance of the proposed control strategy. The results showed that the proposed strategy can reduce intersection delay by 8%, compared to the current field-implemented control strategy.
Transportation mobility can be improved not only by traffic management strategies, but also through the deployment of advanced vehicle technologies. This dissertation also investigates the impact of Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) on highway capacity. A freeway microscopic traffic simulation model is constructed to evaluate how the freeway lane flow capacity change under different penetration rates of vehicles equipped with either ACC or CACC system. This simulation model is based on a calibrated driver behavioral model and the vehicle dynamics of the ACC and CACC systems. The model also utilizes data collected from a real experiment in which drivers' selections of time gaps are recorded. The simulation shows that highway capacity can be significantly increased when the CACC vehicles reach a moderate to high market penetration, as compared to both regular manually driven vehicles and vehicles equipped with only ACC.