Throughout United States and world history, disasters have caused not only significant loss of life, property but also enormous financial loss. The tsunami that occurred on December 26, 2004 is a telling example of the devastation that can occur unexpectedly. This unexpected natural event never happened before in this area. In addition, there was a lack of an emergency response plan for events of that magnitude. Therefore, this event resulted not only in a natural catastrophe for the people of South and Southeast Asia, but it is also considered one of the greatest natural disasters in world history. After the giant wave dissipated, there were more than 230,000 people dead and more than US$10 billion in property damage and loss. Another significant event was the terrorist incident on September 11, 2001 (commonly referred to as 9/11) in United States. This event was unexpected and an unnatural, i.e., man-made event. It resulted in approximately 3,000 lives lost and about US$21 billion in property damage. These and other unexpected (or unanticipated) events give emergency management officials short- or no-notice to prevent or respond to the situation. These and other facts motivate the need for better emergency evacuation route planning (EERP) approaches in order to minimize the loss of human lives and property in short- or no-notice emergency situations. This research considers aspects of evacuation routing that have received little attention in research and, more importantly, in practice. Previous EERP models only either consider unidirectional evacuee flow from the source of a hazard to destinations of safety or unidirectional emergency first responder flow to the hazard source. However, in real-life emergency situations, these heterogeneous, incompatible flows occur simultaneously over a bi-directional capacitated lane-based travel network, especially in short- and no-notice emergencies. After presenting a review of the work related to the multiple flow EERP problem, mathematical formulations are presented for the EERP problem where the objective for each problem is to identify an evacuation routing plan (i.e., a traffic flow schedule) that maximizes evacuee and responder flow and minimizes network clearance time of both types of flow. In addition, we integrate the general human response behavior flow pattern, where the cumulative flow behavior follows different degrees of an S-shaped curve depending upon the level of the evacuation order. We extend the analysis to consider potential traffic flow conflicts between the two types of flow under these conditions. A conflict occurs when flow of different types occupy a roadway segment at the same time. Further, with different degrees of flow movement flow for both evacuee and responder flow, the identification of points of flow congestion on the roadway segments that occur within the transportation network is investigated.

Roads can negatively impact the survival of wildlife populations through additional mortality from road kill and population fragmentation caused by road avoidance behaviors. The 11.9 mile section of State Route 101 between the towns of San Luis Obispo and Atascadero, CA, USA, cross a mountain lion movement corridor and an area important to maintaining ecological connectivity between protected lands in the Los Padres National Forest to the north and south. I examined the spatial patterns and landscape and roadway factors associated with road kill occurrence for six taxa; large mammals, mesocarnivores, squirrels, rabbits, birds and raptors. Between 1 May 2009 and 30 June 2010 road kills were documented using vehicle-based surveys. Small mammals were the most common road kill (58.3%), followed by mesocarnivores (10.9%), birds (10.6%), rabbits (5.1%), large mammals (3.3%) and raptors (3.2%). Twenty-nine large mammal road kills were observed during the survey period; eighteen mule deer, six black bears and five feral pigs. Road kill was highest in the middle of the survey area between the top of Cuesta Grade and the southern edge of Atascadero and lowest along the Cuesta Grade. I modeled road kill occurrence using logistic regression to determine which landscape and roadway characteristics were associated with road kill locations. Large mammal and mesocarnivore road kills were more likely to occur near riparian corridors. Mesocarnivore and squirrel road kills were associated with locations with greater roadside tree cover. Squirrel and rabbit road kills were more likely to occur along sections of the road with large grassy center medians. I documented animal activity patterns around the roadway during three survey periods (summer 2009, fall 2009 and spring 2010) using remote cameras placed on game trails and underpasses along the roadway. Mule deer displayed crepuscular activity patterns with peaks in activity in the morning between 05:00h and 07:00h and in the evening between 16:00h and 18:00h. Mesocarnivores generally displayed a nocturnal activity patterns with the majority of activity occurring between 18:00h and 06:00h. I used logistic regression to determine if there was a relationship between animal activity patterns and traffic patterns while controlling for time of day, day of the week, and season. Mule deer and mesocarnivore activity patterns varied significantly by time of day and mule deer activity also varied significantly by season; however only mesocarnivore activity varied significantly in relation to traffic volume suggesting that mesocarnivores are less activity when traffic volume is high. Using traffic volume and animal activity patterns I calculated a collision potential value for both mule deer and mesocarnivores. Collision potential for mule deer was high in the morning, between 06:00h and 08:00h, and in the evening, between 16:00h and 18:00h in all three seasons. Collision potential for mesocarnivores was high in the evening in fall 2009 (18:00h and 21:00) and spring 2010 (17:00h), and high in the morning in summer 2009 (09:00h).

The accurate modeling of travelers’ route choice decision making when faced with unreliable (risky) travel times is necessary for the assessment of policies aimed at improving travel time reliability. Two major objectives are studied in this thesis. The first objective is to evaluate the applicability of a process model to route choice under risk where the actual process of decision making is captured. Traditionally, we adopt “as-if” econometric models to predict people’s route choice decisions. The second objective is to investigate travelers’ capability to incorporate future real-time traffic information into their current route choice decision making. Two separate stated preference (SP) surveys were conducted for each objective. The first SP survey used an interactive map in a computer based test. The second SP survey used a full-scale high-fidelity driving simulator. Compared with econometric models, process models have been rarely investigated in travel decision making under risk. A process model aims to describe the actual decision making procedure and could potentially provide a better explanation to route choice behavior. A process model, Priority Heuristic (PH), developed by Brandstatter et al. (2006) is introduced to the travel choice context and its probabilistic version, Probabilistic Priority Heuristic (PPH), is developed and estimated in this study. With data collected from a stated preference (SP) survey which is based on an animated computer interface, one econometric model, Rank-Dependent Expected Utility (RDEU) model, and two other alternative models were compared with the PPH model in a cross validation test to investigate their data-fitting and predictive performance. Our results show that the PPH model outperforms the RDEU model in both data-fitting and predictive performance. This suggests that the process modeling paradigm could be a promising new area in travel behavior research. With the advance of information and telecommunication technology, real-time traffic information is increasingly more available to help travelers make informed route choice decisions when faced with unreliable travel times. A strategic route choice refers to a decision taking into account future diversion possibilities at downstream nodes based on real-time information not yet available at the time of decision-making. Based on the data collected from a driving simulator experiment and a matching PCbased experiment, a mixed Logit model with two latent classes, strategic and nonstrategic route choice, is specified and estimated. The estimates of the latent class probabilities show that a significant portion of route choice decisions are strategic and subjects can learn to make more strategic route choice as they have more experience with the decision scenarios. Non-parametric tests additionally show that network complexity adversely affects travelers’ strategic thinking ability in a driving simulator environment but not in a PC environment and a parallel driving task only affects strategic thinking ability in a difficult scenario but not a simple one. In addition, we find that people’s strategic thinking ability are influenced by their gender and driving experience (mileage) in the non-parametric analysis, but not in the modeling work. These findings suggest that a realistic route choice model with real-time traffic information should consider both strategic and non-strategic behavior, which vary with the characteristics of both the network and the driver.

Dans En route, (1895) de J.-K. Huysmans, Durtal, le protagoniste, est à la recherche de ce que l’on pourrait appeler son idéal esthétique. Cette recherche, qui est l’une des étapes de sa conversion, le mène d’église en église, à travers Paris et jusqu’à l’abbaye Notre-Dame de l’Âtre, en quête d’art religieux, du plain-chant le plus authentique, des messes les plus touchantes, des plus belles figures de piété. Or, on observe que cette recherche obsessionnelle d’un idéal esthétique est l’un des leitmotivs de la littérature décadentiste. Comment expliquer qu’elle ait une importance aussi grande dans En route, sachant que la conversion, ainsi que le laisse entendre la fin célèbre d’À rebours, signale la fin des obsessions du décadentisme ? Ce mémoire s’attarde à cerner les objets auxquels s’attache Durtal, à examiner leur rapport avec ceux auxquels s’attache le décadentisme et à déterminer si la conversion, dans En route, peut être considérée comme une extension de la crise du sujet décadentiste. Il interroge la figure du personnage huysmansien, les notions de poétique propres au décadentisme huysmansien et ce que Freud identifie dans l’essai Un souvenir d’enfance de Léonard de Vinci (1910) comme une tendance de l’homme célibataire à sublimer ses pulsions sexuelles en une forme d’idéalisation et d’enthousiasme pour l’art, en une soif difficilement contentée d’art, de beauté et de connaissance. L’enjeu de ce travail est de démontrer que la quête de l’idéal esthétique, dans En route, se situe entre l’obsession décadentiste et la sublimation du désir. / In J.-K Huysmans 1895 novel En route, Durtal, the protagonist, is in search of what one might call an aesthetic ideal. This quest, which is one of the stages of his conversion, takes him from church to church, through Paris and ultimately to the Abbey of Notre-Dame de l’Âtre, in search of religious art, of the most authentic Gregorian chant, the most touching masses, the most beautiful figures of piety. This obsessive search for the aesthetic ideal is one of the leitmotifs of decadent literature. However, how can we explain that it has such great importance in En Route, given that religious conversion, as the famous ending of À rebours suggests, should be the end of the decadent movement’s obsessions? This research focuses on identifying the art to which Durtal is attracted, and will examine their relationship with decadent art to determine whether conversion, in En Route, can be considered as an extension of the crisis of the decadent subject. It also studies the figure of the Huysmansian character, the notions of poetics specific to Huysmansian decadentism and what Freud identifies in the essay Leonardo da Vinci and a Memory of His Childhood (1910) as a tendency of the celibate man to sublimate his sexual drives into a form of idealization and enthusiasm for art, a hard-satisfied thirst for art, beauty and knowledge. The goal of this research is to demonstrate that the quest for the aesthetic ideal, in En Route, lies between the old decadent’s obsessions and the sublimation of sexual desire.

The studies reported in this thesis aim to provide insights on the process of navigation while driving. Driving requires processing and monitoring multiple tasks and sources of information. Navigation while driving increases the cognitive load of the driving task. Offloading the task of navigation to navigation aid systems such as GPS has potential disadvantages for our spatial memory skills. In this thesis, we introduce useful cues and skills to improve the performance of drivers in a variety of situations where they must navigate without the help of GPS. We used a motion simulator with six degrees of freedom to simulate various virtual reality driving scenarios that combine both visual and vestibular cues. In the following chapters, we report the effects of landmark cues, vestibular cues, self-reported mood disorders (e.g., depression, anxiety, and stress), individual differences at the visual spatial level (e.g., working memory span and mental rotation skills), age, and self-reported navigation skills on drivers’ route learning. We showed that successful navigation in various navigational situations depends on the type of landmarks available in the environment and the specific visual-spatial skills of drivers. We showed that vestibular self-motion cues improve egocentric route learning. Depression, anxiety, and stress affected drivers' route learning ability and dependency on GPS. We observed no deficit in age-related navigation performance when older drivers were able to use an egocentric frame of reference, however there was less optimal navigation performance of older drivers when wayfinding required an allocentric frame of reference. Overall, the application of the findings of this thesis may lead to an increase in efficacy and success in navigation performance and wayfinding while driving. / Thesis / Candidate in Philosophy / This thesis focuses on enhancing our understanding of wayfinding while driving in young and older adults. Using a driving simulator, we ran various virtual reality experiments to examine the underlying mechanisms of navigation while driving and ways to improve wayfinding of drivers. We identified useful cues for route learning in different environments where there were no navigation aid systems. We examined correlations between various spatial skills and performance that may improve drivers' wayfinding in unfamiliar environments. Furthermore, we assessed age-related effects on route learning and potential interventions to improve navigation in older drivers. The findings from the experiments reported in this thesis introduce the principle of route learning while driving in terms of how various internal and external factors can affect it. Drivers can incorporate these findings into their navigation tasks to overcome the wayfinding challenges that they encounter when driving in unfamiliar environments.

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