Theses and Dissertations at Montana State University (MSU)
Permanent URI for this collectionhttps://scholarworks.montana.edu/handle/1/733
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Item Inference of passenger ridership, O-D flows, wait times, and travel times using Wi-Fi and GPS signals(Montana State University - Bozeman, College of Engineerng, 2019) Videa Martinez, Aldo Alejandro; Chairperson, Graduate Committee: Yiyi WangReal-time data collection of transportation parameters is a vital element of research and industrial applications. A real-time ridership data collection would facilitate the planning of trips and optimization of routes for transportation agencies. Riders also would have the ability to plan their trips more easily. With the advent of smartphone technologies, societies have obtained a new infrastructure that is based on wireless networks. This infrastructure can be used as a platform to obtain information. In our case, we are exploring the Wi-Fi networks that surround a space to obtain traffic data. Our research focuses on scanning IEEE 802.11 networks with a sniffing software and then we classified the different signals into passengers and not passengers. To do so, we used the various attributes obtained with our sniffing software on a Raspberry Pi computer and filtered the signals that would not belong to passengers. Afterward, we implemented machine learning algorithms on the pre-processed data to understand the intrinsic nature of the data and evaluate if there could be some traits that would be utilized to perform an unsupervised classification that corresponded to the passengers' smartphones. In the unsupervised learning algorithm, the parameters were reduced into two with arithmetic operations and principal component decomposition. The results with the rule-based methodology are more accurate than the unsupervised methodology. We believe this is due to many router signals that are similar to the passengers' smartphones. Our proposed methodology has some limitations like some riders not carrying smartphones, and overestimation resulted from the noise of other signals. However, with the devices that were detected, we have demonstrated that the time of detection is accurate which helped us infer the origin-destination flows from a portion of our subjects. Additionally, we used the GPS traces to estimate travel time between buses and wait time of passengers at a bus stop.Item Travel behavior and decision-making biases of lift access backcountry skiers on Saddle Peak, Bridger Mountains, Montana, USA(Montana State University - Bozeman, College of Letters and Science, 2018) Sykes, John Massey; Chairperson, Graduate Committee: Jordy Hendrikx; Jordy Hendrikx, Jerry Johnson and Karl Birkeland were co-authors of the article, 'Travel behavior and decision-making biases of lift access backcountry skiers' submitted to the journal 'Applied geography' which is contained within this thesis.Backcountry skiers recreate in a complex environment, with the goal of minimizing the risk of avalanche hazard and maximizing recreational opportunities. Traditional backcountry outings start and end in uncontrolled backcountry settings, with responsibility for avalanche safety and rescue falling in the hands of each group of skiers. Lift access backcountry skiing (LABC) is a particular genre of the sport in which ski resort lifts are utilized to access backcountry recreation sites. By shifting skiers mentality from the traditional backcountry setting to a LABC setting, the line between whether the ski resort provides avalanche mitigation and rescue services or not, becomes less clearly defined in the minds of skiers. We observe the travel behavior and evaluate the decision-making biases of LABC skiers via GPS tracking and survey responses. Participants were recruited in the field, at the boundary between the relative safety of the ski resort and the uncontrolled backcountry terrain beyond. A geographic information system (GIS) is implemented to analyze the travel behavior of participants, with the aim to detect changes in behavior, as indexed via terrain used under different levels of avalanche hazard. Logistic regression and multiple linear regression are used to model travel behavior and decision-making biases as a function of observed terrain metrics. Data was collected over 19 days from February 2017 to February 2018 at Saddle Peak backcountry area, a prime LABC location at the southern boundary of Bridger Bowl Ski Area, Montana, USA. Avalanche hazard during data collection was either moderate (119 tracks) or considerable (20 tracks). Regression models indicate subtle changes in the terrain preferences of participants under elevated avalanche hazard, with increased travel on ridge features and decreased use of convex features. These indicate a positive response, minimizing the risk of an avalanche involvement by managing slope shape. Survey responses indicate that female participants and those with greater backcountry experience have a significantly lower percentage of their total GPS track in complex avalanche terrain as defined using the avalanche terrain exposure scale. Participants who perceived the ski patrol as providing avalanche mitigation in the backcountry area adjacent to the resort had a significantly higher percentage of GPS track in complex avalanche terrain.Item Development of GIS/GPS methodology of minesite soil salvaging(Montana State University - Bozeman, 1994) Lindberg, Steven Dennis; Chairperson, Graduate Committee: D. J. DollhopfItem Invasive plant mapping : a standardized system(Montana State University - Bozeman, College of Agriculture, 2002) Cooksey, DianaItem Software development for automatic steering and implement control of agricultural equipment utilizing the global positioning system and a geographic information system(Montana State University - Bozeman, College of Agriculture, 1994) Mosdal, Brian ThomasItem Terrain analysis in support of precision farming(Montana State University - Bozeman, College of Letters & Science, 1995) Spangrud, Damian JeremiahItem Focused investigations of relativistic electron burst intensity, range, and dynamics space weather mission global positioning system(Montana State University - Bozeman, College of Engineering, 2011) Wilz, Mackenzie Charles; Chairperson, Graduate Committee: Joseph A. ShawThe FIREBIRD mission (Focused Investigations of Relativistic Electron Burst Intensity, Range, and Dynamics) is a low earth orbit, space weather, CubeSat mission which is comprised of a two satellite constellation. This constellation is responsible for the measurement of relativistic electron microbursts with very fine spatial and temporal resolution. To achieve the spatial and temporal requirements of the mission, a global positioning system (GPS), for the purpose of navigation position and timing, is to be implemented on both satellites within the constellation. The integration and testing of this subsystem is integral to the mission's success. The GPS hardware must be capable of fulfilling the requirements of the mission in order for the science data to be interpreted reliably. This means that the GPS hardware must not only be accurate but precise as well. Also, a driver must be implemented in software in order for this data from the GPS hardware to be received, interpreted, and stored by the command and data handling subsystem.Item Terrain based routing protocol for sparse ad-hoc intermittent network (TRAIN)(Montana State University - Bozeman, College of Engineering, 2005) Dawra, Gaurav; Chairperson, Graduate Committee: Brendan MumeyTraditionally, routing protocols for ad-hoc networks have been developed without taking into consideration the effects of the surrounding environment. In this thesis, we propose and investigate a new approach of terrain and location based routing and its effect on the routing layer on sparse ad-hoc networks. This approach is particularly important for sparse networks, where relatively large node separations can result in periods of disconnectivity. Terrain blockage compounds the problem, as the likelihood of inter node communication is further diminished. We anticipate that terrain and location based routing would cause significant decrease in latency and would increase the throughput of sparse ad-hoc mobile nodes. It would also provide a new area of research which would provide more realistic and intelligent view of the surrounding. The use of terrain maps from U.S. geographical survey provides a realistic view of the network environment, through which a node can determine whether there is a Line of Sight (LOS) or Non Line of sight (NLOS) path to another node by combining location awareness and terrain data. When nodes are mobile, knowledge of trajectories can be used to predict future locations, and combined with terrain information, to forecast link conditions at a future time. As an additional feature of our routing protocol; when a node has data to send it calculates the stability of the link based on terrain and trajectory information and deterministically predicts the duration for which this link is going to be stable. For the performance assessment of using location, trajectory and terrain information, a simulation model including the terrain map of Yellowstone National Park have been developed using the discrete event simulator OPNET Modeler TM 10.5. Simulation scenarios have been created for single hop as well as for multi-hop networks based on the characteristics of 802.11 wireless technology. From the results, we have observed that using the terrain and location information provides nodes with an intelligent and realistic view of the network topology. Our approach has proved effective in make deterministic routing decisions based on LOS predictability, thus increasing the reliability, stability, and throughput of the network.Item The use of GPS to predict energy expenditure for outdoor walking(Montana State University - Bozeman, College of Education, Health & Human Development, 2007) McKenzie, James Michael; Chairperson, Graduate Committee: Daniel P. HeilThe purpose of this study was to determine the ability of GPS-reported position and elevation to estimate actual energy expenditure (EEACT) for outdoor walking. An accurate method for assessing EE in the field could greatly influence the scope of future studies of free-living activities. Thirteen subjects (8 male, 5 female) completed a 2303 m course of varying grades at slow and fast self-selected paces. Data from a portable metabolic unit was used to compare the GPS-predicted EE (EEGPS). Calculations of EEGPS were made by compiling an equation accounting for ground speed, grade, (Minetti, et al., 2002) and wind resistance (Pugh, 1970). Differences between EEACT and EEGPS were statistically and practically significant for the slow walking trials. Fast trials showed no significant differences. The combined data differed significantly from EEACT, but was similar to the error for accelerometer-based activity monitors. The wrist and hip-worn GPS monitors provided similar results for EEGPS throughout the data set. Separating the data by grade type showed that EEGPS was most problematic for uphill walking.