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ItemModeling the impact of road grade on vehicle operation, vehicle energy consumption, and emissions(Georgia Institute of Technology, 2018-08-08) Liu, HaobingMotor vehicle emissions and their impacts on local air pollutant concentrations are a primary concern in cities. Properly quantifying energy and emissions is the key step in identifying the major sources of air pollution, evaluating whether transportation activities are consistent with air quality goals, and providing decision makers with reference for implementation of new policies for sustainable development. Mathematical models are commonly used to predict vehicle energy consumption and emissions. Vehicle-specific power (VSP) is widely used in such models to evaluate engine load, and it is represented as a function of vehicle mass, vehicle dynamic parameters (rolling/drag coefficient), driving behavior (speed and acceleration) and road conditions (gravitational acceleration and road gradient). In the U.S. Environmental Protection Agency’s (USEPA’s) MOVES (MOtor Vehicle Emission Simulator) model, speed and VSP levels are tied to vehicle energy consumption and emission rates. Detailed and accurate speed-acceleration joint distributions (SAJDs, also known as Watson plots) can be used to reflect onroad activity required for calculating the distribution of activities in MOVES VSP and speed bins, and thus for estimating vehicle energy consumption and emissions. Road grade is also a critical variable that affects engine operations, as uphill grades require that the engine perform additional work against gravity in the direction of vehicle motion (while downhill grades obtain an energy benefit). Real-world vehicle speed and acceleration can be easily collected using low-cost global positioning system (GPS) data loggers, on-board diagnostics (OBD) system data loggers, and smartphones apps. But, The effect of road grade is usually ignored in emission modeling. On the other hand, very little attention has been paid to the interaction between real-world road grade and onroad activity patterns and the resulting impact on energy use and emissions. However, road grade is expected to impact vehicle operations due to drivers’ response to uphill and downhill driving, or due to vehicle mechanical performance. It is currently unclear that how speed and accelerations vary across different road grade levels, and how the interaction of driver behavior and road grade affect engine power, energy consumption, and emissions modeling. This study is directed at answering two issues: 1): how road grade impacts vehicle speed and acceleration distributions, and how such distributions vary across vehicle types, roadway types, traffic conditions, etc., and 2): how significant the impact of integrating grade interactions is with respect to energy, emissions, and air quality modeling.
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ItemMethodology for collecting vehicle occupancy data on multi-lane interstate highways: a ga 400 case study(Georgia Institute of Technology, 2011-07-08) D'Ambrosio, Katherine T.A before and after comparison of vehicle occupancy distributions for the Atlanta, GA I-85 HOV to High Occupancy Toll (HOT) lane conversion scheduled for summer 2011, will assess the changes in vehicle and passenger throughput associated with lane conversion. The field deployment plans and data collection methodologies developed for the HOT evaluation were the result of a comprehensive literature review, an examination of previous data collection methods, an evaluation of the physical characteristics of the I-85 corridor, and the testing of a variety of equipment/manpower strategies. The case study in this thesis evaluates the established vehicle occupancy methodology for consistency across multiple observers during parallel data collection efforts. The differences noted in exact matches and consistency across the use of the "uncertain" values developed for field implementation is specifically assessed. Results from this study are the first step in assessing the validity of the data collection methods used on the HOT corridor and will yield recommendations for improving the methodology for future occupancy studies. A separate assessment of the accuracy of the methodology is also being conducted by the research team and will be published under a separate cover.
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ItemMeasurement of Freeway Traffic Flow Quality Using GPS-Equipped Vehicles(Georgia Institute of Technology, 2006-07-07) Ko, JoonhoThe evaluation of freeway service quality is crucial work, and thus, transportation professionals have developed numerous measures including traffic volume, speed, and density. However, recent research efforts have indicated that such traditional measures may not fully reflect the quality of roadway service from the perspective of individual drivers, necessitating the development of alternative approaches that complement or replace the current service quality measures. As an alternative approach, the speed variation of a vehicle has been suggested as a promising indicator of traffic flow quality perceived by individual drivers. In particular, acceleration noise, defined by the standard deviation of the acceleration of a vehicle, has been often studied as a measure of the degree of speed variation. However, previous studies have been limited to the experimental level due to the difficulty in collecting high-resolution vehicle speed profiles for computing acceleration noise. In this dissertation, the characteristics of speed variation, measured by acceleration noise, are investigated using the rich set of GPS data collected from the instrumented vehicles driven by the participants of the Commute Atlanta research program. The employment of the real-world vehicle activity data, composed of every second of vehicle operation, renders this research effort unique and provides an opportunity to investigate the various aspects of acceleration noise in the real-world context. The investigation is performed by relating acceleration noise to its three influential factors: traffic conditions, roadway, and driver/vehicles. In addition, a fuzzy inference system-based methodology, combining vehicle speed and acceleration noise from instrumented vehicles, is proposed as an approach to evaluating traffic flow quality.