Topology-Constrained Network Design

International audienc

Travel Time in Macroscopic Traffic Models for Origin-Destination Estimation

Transportation macroscopic modeling is a tool for analyzing and prioritizing future transportation improvements. Transportation modeling techniques continue to evolve with improvements to computer processing speeds and traffic data collection. These improvements allow transportation models to be calibrated to real life traffic conditions. The transportation models rely on an origin-destination (OD) matrix, which describes the quantity and distribution of trips in a transportation network. The trips defined by the OD matrix are assigned to the network through the process of traffic assignment. Traffic assignment relies on the travel time (cost) of roadways to replicate route choice of trips between OD trip pairs. Travel time is calculated both along the roadway and from delay at the intersections. Actuated traffic signals, one form of signalized intersections, have not been explicitly modeled in macroscopic transportation models. One of the objectives of this thesis is to implement actuated signals in the macroscopic modeling framework, in order to improve traffic assignment by more accurately representing delay at intersections. An actuated traffic signal module was implemented into QRS II, a transportation macroscopic model, using a framework from the 2010 Highway Capacity Manual. Results from actuated intersections analyzed with QRS II indicate the green time for each phase was reasonably distributed and sensitive to lane group volume and input parameters. Private vendor travel time data from companies such as Navteq and INRIX, have extensive travel time coverage on freeways and arterials. Their extensive travel time coverage has the potential to be useful in estimating OD matrices. The second objective of this thesis is to use travel time in the OD estimation framework. The presented OD estimation method uses travel time to determine directional split factors for bi-directional traffic counts. These directional split factors update target volumes during the OD estimation procedure. The OD estimation technique using travel time from floating car runs was tested using a mid-sized network in Milwaukee, WI. The analysis indicates applicability of using travel time in OD estimation

Topology Considerations in Hybrid Electric Vehicle Powertrain Architecture Design.

Optimal system architecture (topology or configuration) design has been a challenging design problem because of its combinatorial nature. Parametric optimization studies make design decisions assuming a given architecture but there has been no general methodology that addresses design decisions on the system architecture itself. Hybrid Electric Vehicle (HEV) powertrains allow various architecture alternatives created by connecting the engine, motor/generators and the output shaft in different ways through planetary gear systems. Addition of clutches to HEV powertrains allows changing the connection arrangement (configuration) among the powertrain components during the vehicle operation. Architectures with this capability are referred to as multi-mode architectures while architectures with fixed configurations are referred to as single-mode architectures. HEV architecture optimization requires designing the powertrain’s configuration and its sizing simultaneously. Additionally, evaluation of an HEV architecture design depends on a power management (control) strategy that distributes the power demand to the engine and motor/generators. Including this control problem increases the complexity of the HEV architecture design problem. This dissertation focuses on a general methodology to make design decisions on HEV powertrain architecture and component sizes. The representation of the architecture design problem is critical to solving this problem. A new general representation capable of describing all architecture alternatives is introduced. Using the representation, all feasible configurations are generated where these feasible configurations are used to create single- and multi-mode HEV architectures. Single-mode and multi-mode architecture design problems considering fuel economy, vehicle performance and architecture complexity are formulated separately and solution strategies are developed. The high complexity of the resulting optimization problem does not allow us to claim true optimality rigorously; therefore, the terms ``promising" or ``near-optimal" are more accurate in characterizing our results. The results show that different architectures must be designed for different applications. The case studies designing architectures for some available vehicles from the market find the architectures already implemented in these vehicles under some design constraints. Alternative architectures that improve these designs under different design constraints are also demonstrated. Architectures for a new application that is not available in the market are also designed.PHDMechanical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111412/1/bayrak_1.pd

Solving Assignment and Routing Problems in Mixed Traffic Systems

This doctoral thesis presents not only a new traffic assignment model for mixed traffic systems but also new heuristics for multi-paths routing problems, a case study in Hanoi Vietnam, and a new software, named TranOpt Plus, supporting three major features: map editing, dynamic routing, and traffic assignment modeling. We investigate three routing problems: k shortest loop-less paths (KSLP), dissimilar shortest loop-less paths (DSLP), and multi-objective shortest paths (MOSP). By developing loop filters and a similarity filter, we create two new heuristics based on Eppstein's algorithm: one using loop filters for the KSLP problem (HELF), the other using loop-and-similarity filters for the DSLP problem (HELSF). The computational results on real street maps indicate that the new heuristics dominate the other algorithms considered in terms of either running time or the average length of the found paths. In traffic assignment modeling, we propose a new User Equilibrium (UE) model, named GUEM, for mixed traffic systems where 2- and 4-wheel vehicles travel together without any separate lanes for each kind of vehicle. At the optimal solution to the model, a user equilibrium for each kind of vehicle is obtained. The model is applied to the traffic system in Hanoi, Vietnam, where the traffic system is mixed traffic dominated by motorcycles. The predicted assignment by the GUEM model using real collected data in Hanoi is in high agreement with the real traffic situation in Hanoi. Finally, we present the TranOpt Plus software, containing the implementation of all the routing algorithms mentioned in the thesis, as well as the GUEM model and a number of popular traffic assignment models for both standard traffic systems and mixed traffic systems. With its intuitive graphical user interface (GUI) and its strong visualization tools, TranOpt Plus also enables users without any mathematical or computer science background to use conveniently. Nevertheless, TranOpt Plus can be easily extended by further map-related problems, e.g., transportation network design, facility location, and the traveling salesman problem. Keywords: mixed traffic assignment modeling, routing algorithms, shortest paths, dissimilar paths, Hanoi, TranOpt Plus, map visualizatio

Normal mode computations and applications

Proteins are fundamental functional units in cells. Proteins form stable and yet somewhat flexible 3D structures and often function by interacting with other molecules. Their functional behaviors are determined by their 3-D structures as well as their flexibilities. In this thesis, I focus my study on protein dynamics and its role in protein function. One of the most powerful computational methods for studying protein dynamics is normal mode analysis (NMA). Especially its low frequency modes having the intrinsic dynamics of proteins are of interest for most of protein dynamics studies. Although NMA provides analytical solutions to a protein\u27s collective motions, it is inconvenient to use because of its requirement of energy minimization, and it is prohibitive due to the large memory consumption and the long computation time especially when the system is too large. Additionally, it is unclear what meanings the frequencies of normal modes have, and if those meanings can be validated by comparison with the experimental results. The majority of this thesis resolves the above issues. I have addressed following sequence of questions and developed several simplified NMAs as answers: (1) what is the role of inter residue forces; (2) how to remove the energy minimization requirement in NMA yet to keep most of accuracy; (3) how to efficiently build the coarse-grained model from the all-atomic model with keeping atomic accuracy. Additionally, using newly developed models and traditional NMA, I have examined the meaning of normal modes in all frequency range, and have found the connection with experimental results. The last part of this thesis addresses, as an application of normal modes, how the normal modes can depict the sequence of breathing motion of myoglobin to find the transition pathway that dynamically opens ligand migration channels. The results have an excellent agreement with molecular dynamics simulation results and experimentally determined reaction rate constants

A novel synthetic route towards anti-inflammatory mediator: Resolvin E1

The health benefits of fish oil supplementations have been proven to be effective by several studies which are discussed in this thesis. It was found that these compounds had potent anti-inflammatory properties and since then has prompted much research into the use of these compounds as potential treatments for chronic inflammation based diseases, where the overuse of current anti-inflammatory drugs cause many problems with undesired side-effects. The aim of this research is to study the bioactivity of resolvin E1 and various analogues, and to determine a novel route towards resolvin E1 natural product so that bioactivity tests may be conducted in comparison of synthetically produced resolvin E1 and naturally extracted resolvin E1. The initial aim of this research was to develop a range of analogues of a fragment of Resolvin E1. This was so that a series of compounds could be produced with various R groups to identify any structure-activity relationships for this part of the natural product. There is one stereocentre in this fragment of resolvin E1 and it was decided that a racemic version of these compounds would be tested for bioactivity, and if any of the compounds had significant anti-inflammatory properties then the R and S versions could be separated, allowing for the testing of both enantiomers to determine which gave the most potent anti-inflammatory response. This led to the creation of several novel fragments and their biological testing. The secondary aim of the project was to complete the total synthesis of the resolvin E1 natural product. We devised a novel route towards resolvin E1 which used MIDA boronate protecting group to introduce a fixed trans double bond which was useful in a compound with multiple alkene systems. Resolvin E1 also contains three stereocentres, the synthesis from the fragment work was recycled to begin the synthesis, and made use of 1,2:5,6-di-O-isopropylidene-D-mannitol and Noyori s catalyst to setup the stereocentres. The use of new MIDA-boronate moieties were also explored in order to develop a new, efficient synthesis toward resolvin E1

Race, Crime, and Institutional Design

Minorities are gravely overrepresented in every stage of the criminal process--from pedestrian and automobile stops, to searches and seizures, to arrests and convictions, to incarceration and capital punishment. While racial data can provide a snapshot of the current state of affairs, such information rarely satisfies questions of causation, and usually only sets the scene for normative theory