STATISTICAL METHODS FOR ADVANCED ECONOMETRIC MODELS WITH APPLICATIONS TO VEHICLE HOLDING AND SPEED QUANTILES DISTRIBUTION

This dissertation proposes statistical methods to formulate, estimate and apply complex transportation models. Two main problems are part of the analyses conducted and presented in this dissertation. The first method solves an econometric problem and is concerned with the joint estimation of models that contain both discrete and continuous decision variables. The use of ordered models along with a regression is proposed and their effectiveness is evaluated with respect to unordered models. Procedure to calculate and optimize the log-likelihood functions of both discrete-continuous approaches are derived, and difficulties associated with the estimation of unordered models explained. Numerical approximation methods based on the Genz algortithm are implemented in order to solve the multidimensional integral associated with the unordered modeling structure. The problems deriving from the lack of smoothness of the probit model around the maximum of the log-likelihood function, which makes the optimization and the calculation of standard deviations very difficult, are carefully analyzed. A methodology to perform out-of-sample validation in the context of a joint model is proposed. Comprehensive numerical experiments have been conducted on both simulated and real data. In particular, the discrete-continuous models are estimated and applied to vehicle ownership and use models on data extracted from the 2009 National Household Travel Survey. The second part of this work offers a comprehensive statistical analysis of free-flow speed distribution; the method is applied to data collected on a sample of roads in Italy. A linear mixed model that includes speed quantiles in its predictors is estimated. Results show that there is no road effect in the analysis of free-flow speeds, which is particularly important for model transferability. A very general framework to predict random effects with few observations and incomplete access to model covariates is formulated and applied to predict the distribution of free-flow speed quantiles. The speed distribution of most road sections is successfully predicted; jack-knife estimates are calculated and used to explain why some sections are poorly predicted. Eventually, this work contributes to the literature in transportation modeling by proposing econometric model formulations for discrete-continuous variables, more efficient methods for the calculation of multivariate normal probabilities, and random effects models for free-flow speed estimation that takes into account the survey design. All methods are rigorously validated on both real and simulated data.

Power Factor Corrector Design applied to an 85-kHz Wireless Charger

Wireless charging technology extends the battery autonomy by allowing more flexible and practical ways of recharging it even when the electric vehicle is on move. The frequency conversion, which is required to generate a kHz-ranged magnetic field, also leads to considerable harmonics. As a result, the power factor and the corresponding efficiency decrement. This paper proposes a Power Factor Corrector which overcomes this drawback. The most relevant feature of the designed Power Factor Corrector is that it does not need any electrical signal from the secondary side to adjust its operation properly. The simulation results show the ability of the proposed scheme to increment the system efficiency for different State-Of-Charge in the Battery.

A MORE COMPLETE STREET A STREET FOR EVERYONE TO ENJOY, NORTH EAST STREET, FREDERICK, MARYLAND – A DESIGN INVESTIGATION OF DIFFERENT STREET DESIGN THEORIES

This design-research thesis suggests that the improvement of North East Street performances by using Complete Streets, Green Street, Place Making and Context Sensitive Solution principles and practices. Heavily used by a variety of users, often conflicting with one another, University of Maryland Campus Drive would benefit from a major planning and design amelioration to meet the increasing demands of serving as a city main street. The goal of this thesis project is to prioritize the benefits for pedestrians in the right-of-way and improve the pedestrian experience. This goal also responds to the recent North East Street Extension Phrase I of economic renaissances. The goal of this design-research thesis will be achieved focusing on four aspects. First, the plans and designs will suggest to building mixed use blocks, increase the diversity of street economic types and convenience of people’s living. Second, design and plans will propose bike lanes, separate driving lanes from sidewalks and bike lanes by street tree planters, and narrow driving lanes to reduce vehicular traffic volume and speed in order to reduce pedestrian and vehicle conflicts. Third, plans and designs will introduce bioswales, living walls and raingardens to treat and reuse rain water. Finally, the plans and designs will seek to preserve local culture and history by adding murals and farmers market. The outcome of the design-research thesis project is expected to serve as an example of implementing Complete Streets, Green Street, Place Making and Context Sensitive Solution principles and practices in urban landscape, where transportation, environment and social needs interact with each other.

Vehicle Routing Problems that Minimize the Completion Time: Heuristics, Worst-Case Analyses, and Computational Results

In the standard Vehicle Routing Problem (VRP), we route a fleet of vehicles to deliver the demands of all customers such that the total distance traveled by the fleet is minimized. In this dissertation, we study variants of the VRP that minimize the completion time, i.e., we minimize the distance of the longest route. We call it the min-max objective function. In applications such as disaster relief efforts and military operations, the objective is often to finish the delivery or the task as soon as possible, not to plan routes with the minimum total distance. Even in commercial package delivery nowadays, companies are investing in new technologies to speed up delivery instead of focusing merely on the min-sum objective. In this dissertation, we compare the min-max and the standard (min-sum) objective functions in a worst-case analysis to show that the optimal solution with respect to one objective function can be very poor with respect to the other. The results motivate the design of algorithms specifically for the min-max objective. We study variants of min-max VRPs including one problem from the literature (the min-max Multi-Depot VRP) and two new problems (the min-max Split Delivery Multi-Depot VRP with Minimum Service Requirement and the min-max Close-Enough VRP). We develop heuristics to solve these three problems. We compare the results produced by our heuristics to the best-known solutions in the literature and find that our algorithms are effective. In the case where benchmark instances are not available, we generate instances whose near-optimal solutions can be estimated based on geometry. We formulate the Vehicle Routing Problem with Drones and carry out a theoretical analysis to show the maximum benefit from using drones in addition to trucks to reduce delivery time. The speed-up ratio depends on the number of drones loaded onto one truck and the speed of the drone relative to the speed of the truck.

Guided Bus Rapid Transit

Electrical Bus Rapid Transit (eBRT) is a charging electrical public transport which brings a clean, high performance, and affordable cost alternative from the conventional traffic vehicles which work with combustion and hybrid technology. These buses charge the battery in every bus stop to arrive at the next station. But, this charging system needs an appropriate infrastructure called pantograph, and it requires a high precision bus location to maintain battery lifetime, energy saving and charging time. To overcome this issue Vicomtech and Datik has planned a project based on computer vision to help to the driver to locate the vehicle in the correct place. In this document, we present a mono camera bus driver guided fast algorithm because these vehicles embedded computers do not support high computation and precision operations. In addition to the frequent lane sign, there are more accurate geometric beacons painted on the road to bring metric information to the vision system. This method uses segmentation to binarize the image discriminating the background space. Besides it detects, tracks and counts different lane mark contours in addition to classify each special painted mark. Besides it does not need any calibration task to calculate longitudinal and cross distances because we know the lane mark sizes.

DESIGN OF EFFICIENT IN-NETWORK DATA PROCESSING AND DISSEMINATION FOR VANETS

By providing vehicle-to-vehicle and vehicle-to-infrastructure wireless communications, vehicular ad hoc networks (VANETs), also known as the “networks on wheels”, can greatly enhance traffic safety, traffic efficiency and driving experience for intelligent transportation system (ITS). However, the unique features of VANETs, such as high mobility and uneven distribution of vehicular nodes, impose critical challenges of high efficiency and reliability for the implementation of VANETs. This dissertation is motivated by the great application potentials of VANETs in the design of efficient in-network data processing and dissemination. Considering the significance of message aggregation, data dissemination and data collection, this dissertation research targets at enhancing the traffic safety and traffic efficiency, as well as developing novel commercial applications, based on VANETs, following four aspects: 1) accurate and efficient message aggregation to detect on-road safety relevant events, 2) reliable data dissemination to reliably notify remote vehicles, 3) efficient and reliable spatial data collection from vehicular sensors, and 4) novel promising applications to exploit the commercial potentials of VANETs. Specifically, to enable cooperative detection of safety relevant events on the roads, the structure-less message aggregation (SLMA) scheme is proposed to improve communication efficiency and message accuracy. The scheme of relative position based message dissemination (RPB-MD) is proposed to reliably and efficiently disseminate messages to all intended vehicles in the zone-of-relevance in varying traffic density. Due to numerous vehicular sensor data available based on VANETs, the scheme of compressive sampling based data collection (CS-DC) is proposed to efficiently collect the spatial relevance data in a large scale, especially in the dense traffic. In addition, with novel and efficient solutions proposed for the application specific issues of data dissemination and data collection, several appealing value-added applications for VANETs are developed to exploit the commercial potentials of VANETs, namely general purpose automatic survey (GPAS), VANET-based ambient ad dissemination (VAAD) and VANET based vehicle performance monitoring and analysis (VehicleView). Thus, by improving the efficiency and reliability in in-network data processing and dissemination, including message aggregation, data dissemination and data collection, together with the development of novel promising applications, this dissertation will help push VANETs further to the stage of massive deployment.

Effect of Pavement-Vehicle Interaction on Highway Fuel Consumption and Emission

Vehicle fuel consumption and emission are two important effectiveness measurements of sustainable transportation development. Pavement plays an essential role in goals of fuel economy improvement and greenhouse gas (GHG) emission reduction. The main objective of this dissertation study is to experimentally investigate the effect of pavement-vehicle interaction (PVI) on vehicle fuel consumption under highway driving conditions. The goal is to provide a better understanding on the role of pavement in the green transportation initiates. Four study phases are carried out. The first phase involves a preliminary field investigation to detect the fuel consumption differences between paired flexible-rigid pavement sections with repeat measurements. The second phase continues the field investigation by a more detailed and comprehensive experimental design and independently investigates the effect of pavement type on vehicle fuel consumption. The third study phase calibrates the HDM-IV fuel consumption model with data collected in the second field phase. The purpose is to understand how pavement deflection affects vehicle fuel consumption from a mechanistic approach. The last phase applies the calibrated HDM-IV model to Florida’s interstate network and estimates the total annual fuel consumption and CO2 emissions on different scenarios. The potential annual fuel savings and emission reductions are derived based on the estimation results. Statistical results from the two field studies both show fuel savings on rigid pavement compared to flexible pavement with the test conditions specified. The savings derived from the first phase are 2.50% for the passenger car at 112km/h, and 4.04% for 18-wheel tractor-trailer at 93km/h. The savings resulted from the second phase are 2.25% and 2.22% for passenger car at 93km/h and 112km/h, and 3.57% and 3.15% for the 6-wheel medium-duty truck at 89km/h and 105km/h. All savings are statistically significant at 95% Confidence Level (C.L.). From the calibrated HDM-IV model, one unit of pavement deflection (1mm) on flexible pavement can cause an excess fuel consumption by 0.234-0.311 L/100km for the passenger car and by 1.123-1.277 L/100km for the truck. The effect is more evident at lower highway speed than at higher highway speed. From the network level estimation, approximately 40 million gallons of fuel (combined gasoline and diesel) and 0.39 million tons of CO2 emission can be saved/reduced annually if all Florida’s interstate flexible pavement are converted to rigid pavement with the same roughness levels. Moreover, each 1-mile of flexible-rigid conversion can result in a reduction of 29 thousand gallons of fuel and 258 tons of CO2 emission yearly.

QoE-aware power management in vehicle-to-grid networks:a matching-theoretic approach

Frequency, time and places of charging and discharging have critical impact on the Quality of Experience (QoE) of using Electric Vehicles (EVs). EV charging and discharging scheduling schemes should consider both the QoE of using EV and the load capacity of the power grid. In this paper, we design a traveling plan-aware scheduling scheme for EV charging in driving pattern and a cooperative EV charging and discharging scheme in parking pattern to improve the QoE of using EV and enhance the reliability of the power grid. For traveling planaware scheduling, the assignment of EVs to Charging Stations (CSs) is modeled as a many-to-one matching game and the Stable Matching Algorithm (SMA) is proposed. For cooperative EV charging and discharging in parking pattern, the electricity exchange between charging EVs and discharging EVs in the same parking lot is formulated as a many-to-many matching model with ties, and we develop the Pareto Optimal Matching Algorithm (POMA). Simulation results indicates that the SMA can significantly improve the average system utility for EV charging in driving pattern, and the POMA can increase the amount of electricity offloaded from the grid which is helpful to enhance the reliability of the power grid.

Motivating the use of public transit through a mobile glanceable display

With increasing concerns about the impact of global warming on human life, policy makers around the world and researchers have sought for technological solutions that have the potential to attenuate this process. This thesis describes the design and evaluation of an information appliance that aims to increase the use of public transportation. We developed a mobile glanceable display that, being aware of the user’s transportation routines, provides awareness cues about bus arrival time, grounded upon the vision of Ambient Intelligence. We present the design process we followed, from ideation to building a prototype and conducting a field study, and conclude with a set of guidelines for the design of relevant personal information systems. More specifically we seek to test the following hypotheses: 1) That the tangible prototype that provides ambient cues will be used more frequently than a similar purpose mobile app, 2) That the tangible prototype will reduce the waiting time at the bus stop, 3) That the tangible prototype will result to reduced anxiety on passengers, 4) That the tangible prototype will result to an increase in the perceived reliability of the transit service, 5) That the tangible prototype will enhance users’ efficiency in reading the bus schedules and 6) That the tangible prototype will make individuals more likely to use public transit. In a field study, we compare the tangible prototype against the mobile app and a control condition where participants were given no external support in obtaining bus arrival information, other than their existing routines. Using qualitative and quantitative data, we test the aforementioned hypotheses and explore users’ reactions to the prototype we developed.

Motivating the use of public transit through a mobile glanceable display

With increasing concerns about the impact of global warming on human life, policy makers around the world and researchers have sought for technological solutions that have the potential to attenuate this process. This thesis describes the design and evaluation of an information appliance that aims to increase the use of public transportation. We developed a mobile glanceable display that, being aware of the user’s transportation routines, provides awareness cues about bus arrival time, grounded upon the vision of Ambient Intelligence. We present the design process we followed, from ideation to building a prototype and conducting a field study, and conclude with a set of guidelines for the design of relevant personal information systems. More specifically we seek to test the following hypotheses: 1) That the tangible prototype that provides ambient cues will be used more frequently than a similar purpose mobile app, 2) That the tangible prototype will reduce the waiting time at the bus stop, 3) That the tangible prototype will result to reduced anxiety on passengers, 4) That the tangible prototype will result to an increase in the perceived reliability of the transit service, 5) That the tangible prototype will enhance users’ efficiency in reading the bus schedules and 6) That the tangible prototype will make individuals more likely to use public transit. In a field study, we compare the tangible prototype against the mobile app and a control condition where participants were given no external support in obtaining bus arrival information, other than their existing routines. Using qualitative and quantitative data, we test the aforementioned hypotheses and explore users’ reactions to the prototype we developed.