A disproportionate number of Americans drive to work alone – at the individual state level, the figure ranges from a low of 58% in New York to 85% in Alabama. What factors explain this travel behavior and what sort of policy responses are required to effect changes? In responding to this question, we used multiple test beds and made the case for a demand side management approach to remedy parking problems particularly observed in cities central business districts. To this end, we provide an overview of travel behavior and information on policy levers by generating detailed profiles that capture the travel behavior of commuters in the Pacific states of the continental United States. Building off the result that revealed San Francisco as an outlier, we examine the efficacy of modifying parking rates, via elasticity measures, to influence the demand for parking by developing a two-stage panel data regression optimization model for managing parking in the City of San Francisco. A key contribution of the research is deriving these price elasticities of parking demand estimates using panel data methods. Coefficient estimates from the panel data regression are used to fit a linear prediction model that is the primary input to the optimization model. The balance of the thesis focuses on parking information by discussing the design and implementation of ParkPGH, a novel smart parking application that provides real time and predictive information on garage parking availability in downtown Pittsburgh. At its core is a predictive model that uses as input historical parking, weather and event data to provide estimates of available parking spaces. We provide an example of the model implementation using data from the Theater Square garage where we utilize neural network-based predictors and multiple net searches to generate both continuous and binary estimates of parking availability. Provision was made for the binary classifier given the need to reduce the possibility of Type II errors.

In the last several years, student mode choice has increasingly become an important area of study. Findings from these studies can be applied to regional travel demand modeling efforts, campus planning efforts, and sustainability initiatives, among others. This paper presents an analysis of student mode choice at the University of Texas at Austin, using statistical and geographic information systems analysis, based on the University of Texas Parking and Transportation Services mode choice survey administered during the spring 2014 semester. Results showed that within this sample, more students take alternative modes than drive alone, though the proportion of students driving alone to campus remains substantial. Among other conclusions, analysis also indicated clustering of respondent residential locations, and drive alone hotspots in several zip codes primarily in south/southeast Austin. These results point to a geographic area where it may be beneficial to concentrate resources aimed at inducing drivers to switch to an alternative mode of transportation, in order to support UT’s mobility and sustainability goals. / text

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The relationship between monthly transit pass ownership and home-work trip mode choice in the Greater Toronto Area was explored using a logit formulation. A Nested Logit model was specified with the primary mode (non-motorised, auto, transit, or auto access to transit) in the upper level and the pass ownership in the lower transit nests. Inclusive value parameters confirm the chosen structure, and a range of policy sensitive, statistically significant parameters having expected signs and magnitudes reveal differences between socio-economic characteristics of pass holders and non-pass holders. In particular, pass holders are less likely to possess a driver’s license or automobile than non-pass holders, implying that passes can be thought of as complementary mobility tools. Cost parameters, which include differentiated pricing for pass and non-pass holders, result in plausible in-vehicle values of time of approximately $31/hour, $33/hour and $8/hour for auto, auto access to transit, and transit all way, respectively.

The relationship between monthly transit pass ownership and home-work trip mode choice in the Greater Toronto Area was explored using a logit formulation. A Nested Logit model was specified with the primary mode (non-motorised, auto, transit, or auto access to transit) in the upper level and the pass ownership in the lower transit nests. Inclusive value parameters confirm the chosen structure, and a range of policy sensitive, statistically significant parameters having expected signs and magnitudes reveal differences between socio-economic characteristics of pass holders and non-pass holders. In particular, pass holders are less likely to possess a driver’s license or automobile than non-pass holders, implying that passes can be thought of as complementary mobility tools. Cost parameters, which include differentiated pricing for pass and non-pass holders, result in plausible in-vehicle values of time of approximately $31/hour, $33/hour and $8/hour for auto, auto access to transit, and transit all way, respectively.

Travel Demand Management (TDM) is now considered one of the most important aspects of transportation planning and operation. The prime objective of TDM is to develop a sustainable transportation system utilizing the existing infrastructure. It is now a well known fact that excessive use of single occupancy vehicle causes numerous problems like traffic congestion, environmental pollution etc. Thus, from TDM perspective, it is of great importance to analyze travel behaviour in order to influence people to reduce car use and choose more sustainable modes such as carpool, public transit, park & ride, walk, bike etc. This study attempts an in-depth analysis of commuting mode choice behaviour using workplace commuter survey data from the City of Edmonton. Unlike traditional mode choice models, this study uses both instrumental and latent variables to better understand the choice process and analyzes their sensitivities with respect to TDM policies. / Transportation Engineering

Trip chaining and mode choice are two important travel behavior decisions in activity-based travel demand modeling system. The hierarchy of these two decisions influences models predictive capability and policy sensitivity. This thesis is aimed at investigating the hierarchical relationship between these decisions and also the effects of socio-demographic characteristics on them. Structural Equation Modeling (SEM) technique is used for this investigation. A six week travel diary data collected in Thurgau, Switzerland in 2003 is used for model estimation. Model estimation results show that for work-tour, trip chain and mode choice decisions are simultaneous and it remains consistent across the six weeks. For weekdays non-work tour, mode choice precedes trip chain whereas for weekends non-work tour trip chain precedes mode choice. The investigation of the effect of a number of socio-demographic characteristics on trip chaining and mode choice behaviors is also found useful for better understanding of these behaviors. / Transportation Engineering

TRANSIMS is a disaggregate, behavioral transportation planning package developed under US DOT's and EPA funding at the Los Alamos National Laboratory (LANL). It is an integrated system of travel forecasting models designed to give transportation planners accurate, complete information on traffic impacts, congestion, and pollution by simulating second-by-second movements of every person and every vehicle through the transportation network of a large metropolitan area. There is no built-in module for travellers' mode choices In TRANSIMS. The modes going with the shortest path are always taken. In Portland Study, a mode choice methodology implemented by a series of feedback processes is proposed. However, it uses aggregate, deterministic mode choice model. There is little solid theoretic ground for the format and coefficients of the generalized costs used in the calibration process. The accessibility to a mode, especially to Transit, was also not included in the model. In the thesis, a disaggregate and deterministic mode choice methodology in TRANSIMS is developed. The accessibility to each mode is analyzed and included in the model. The methodology is then implemented on the Blacksburg transportation planning study, namely Blacksburg_Lite. The analysis of the result is based on the indicator of mode choice, mode split between Transit and Auto. The indicator is close to that in survey data and converged fast. Therefore, this mode choice methodology could be used within TRANSIMS framework. / Master of Science

<p>Problems associated with traffic, such as traffic congestionand pollution, have occurred in major urban areas in particulardue to the increased use of cars. One possible way to reducethe use of cars is to replace commuter trips by car with othermodes of transport, such as a combination of car and publictransport called Park&Ride. The aim of this thesis was tounderstand more about factors influencing the choice of modeand to find measures that could attract car drivers to Park&Ride. A stated preference survey has been conducted inorder to quantify some standard factors. The factors used inthis stated choice experiment were: security at the lot,availability of spaces at the parking lot, costs at the parkinglot and walking distances between the parking space and thestation. The results indicate that security at the Park&Ride facility is important. Both sexes assign a high value tosecure parking, but women are more willing to pay for lights atan unguarded parking lot. The results reveal that parkingfacilities, such as free parking and short distance betweenparking place and work at work, influence people’s choiceof mode. A general conclusion is that there is potential forincreasing the use of Park&Ride facilities, especiallyamong women and respondents over 30 years.</p><p><b>Key words:</b>Mode choice, valuation, traffic reduction,stated preference, factors, Park&Ride</p>