TRAFFIC IMPACT ANALYSIS OF SEVERAL DYNAMIC LANE MANAGEMENT STRATEGIES FOR CONGESTION MITIGATION BASED ON DTA MODEL

Persistent daily congestion has been increasing in recent years, particularly along major corridors during selected periods in the mornings and evenings. On certain segments, these roadways are often at or near capacity. However, a conventional Predefined control strategy did not fit the demands that changed over time, making it necessary to implement the various dynamical lane management strategies discussed in this thesis. Those strategies include hard shoulder running, reversible HOV lanes, dynamic tolls and variable speed limit. A mesoscopic agent-based DTA model is used to simulate different strategies and scenarios. From the analyses, all strategies aim to mitigate congestion in terms of the average speed and average density. The largest improvement can be found in hard shoulder running and reversible HOV lanes while the other two provide more stable traffic. In terms of average speed and travel time, hard shoulder running is the most congested strategy for I-270 to help relieve the traffic pressure.

Real-time analytics on large dynamic graphs

In today's fast-paced and interconnected digital world, the data generated by an increasing number of applications is being modeled as dynamic graphs. The graph structure encodes relationships among data items, while the structural changes to the graphs as well as the continuous stream of information produced by the entities in these graphs make them dynamic in nature. Examples include social networks where users post status updates, images, videos, etc.; phone call networks where nodes may send text messages or place phone calls; road traffic networks where the traffic behavior of the road segments changes constantly, and so on. There is a tremendous value in storing, managing, and analyzing such dynamic graphs and deriving meaningful insights in real-time. However, a majority of the work in graph analytics assumes a static setting, and there is a lack of systematic study of the various dynamic scenarios, the complexity they impose on the analysis tasks, and the challenges in building efficient systems that can support such tasks at a large scale. In this dissertation, I design a unified streaming graph data management framework, and develop prototype systems to support increasingly complex tasks on dynamic graphs. In the first part, I focus on the management and querying of distributed graph data. I develop a hybrid replication policy that monitors the read-write frequencies of the nodes to decide dynamically what data to replicate, and whether to do eager or lazy replication in order to minimize network communication and support low-latency querying. In the second part, I study parallel execution of continuous neighborhood-driven aggregates, where each node aggregates the information generated in its neighborhoods. I build my system around the notion of an aggregation overlay graph, a pre-compiled data structure that enables sharing of partial aggregates across different queries, and also allows partial pre-computation of the aggregates to minimize the query latencies and increase throughput. Finally, I extend the framework to support continuous detection and analysis of activity-based subgraphs, where subgraphs could be specified using both graph structure as well as activity conditions on the nodes. The query specification tasks in my system are expressed using a set of active structural primitives, which allows the query evaluator to use a set of novel optimization techniques, thereby achieving high throughput. Overall, in this dissertation, I define and investigate a set of novel tasks on dynamic graphs, design scalable optimization techniques, build prototype systems, and show the effectiveness of the proposed techniques through extensive evaluation using large-scale real and synthetic datasets.

NUMERICAL SIMULATION STUDY OF VIBRATION MITIGATION EFFECTIVENESS OF TUNED MASS DAMPERS FOR TRAFFIC SIGNAL MAST ARM STRUCTURES

Fatigue damage in the connections of single mast arm signal support structures is one of the primary safety concerns because collapse could result from fatigue induced cracking. This type of cantilever signal support structures typically has very light damping and excessively large wind-induced vibration have been observed. Major changes related to fatigue design were made in the 2001 AASHTO LRFD Specification for Structural Supports for Highway Signs, Luminaries, and Traffic Signals and supplemental damping devices have been shown to be promising in reducing the vibration response and thus fatigue load demand on mast arm signal support structures. The primary objective of this study is to investigate the effectiveness and optimal use of one type of damping devices termed tuned mass damper (TMD) in vibration response mitigation. Three prototype single mast arm signal support structures with 50-ft, 60-ft, and 70-ft respectively are selected for this numerical simulation study. In order to validate the finite element models for subsequent simulation study, analytical modeling of static deflection response of mast arm of the signal support structures was performed and found to be close to the numerical simulation results from beam element based finite element model. A 3-DOF dynamic model was then built using analytically derived stiffness matrix for modal analysis and time history analysis. The free vibration response and forced (harmonic) vibration response of the mast arm structures from the finite element model are observed to be in good agreement with the finite element analysis results. Furthermore, experimental test result from recent free vibration test of a full-scale 50-ft mast arm specimen in the lab is used to verify the prototype structure’s fundamental frequency and viscous damping ratio. After validating the finite element models, a series of parametric study were conducted to examine the trend and determine optimal use of tuned mass damper on the prototype single mast arm signal support structures by varying the following parameters: mass, frequency, viscous damping ratio, and location of TMD. The numerical simulation study results reveal that two parameters that influence most the vibration mitigation effectiveness of TMD on the single mast arm signal pole structures are the TMD frequency and its viscous damping ratio.