A methodology to estimate time varying user responses to travel time and travel time reliability in a road pricing environment

Road pricing has emerged as an effective means of managing road traffic demand while simultaneously raising additional revenues to transportation agencies. Research on the factors that govern travel decisions has shown that user preferences may be a function of the demographic characteristics of the individuals and the perceived trip attributes. However, it is not clear what are the actual trip attributes considered in the travel decision- making process, how these attributes are perceived by travelers, and how the set of trip attributes change as a function of the time of the day or from day to day. In this study, operational Intelligent Transportation Systems (ITS) archives are mined and the aggregated preferences for a priced system are extracted at a fine time aggregation level for an extended number of days. The resulting information is related to corresponding time-varying trip attributes such as travel time, travel time reliability, charged toll, and other parameters. The time-varying user preferences and trip attributes are linked together by means of a binary choice model (Logit) with a linear utility function on trip attributes. The trip attributes weights in the utility function are then dynamically estimated for each time of day by means of an adaptive, limited-memory discrete Kalman filter (ALMF). The relationship between traveler choices and travel time is assessed using different rules to capture the logic that best represents the traveler perception and the effect of the real-time information on the observed preferences. The impact of travel time reliability on traveler choices is investigated considering its multiple definitions. It can be concluded based on the results that using the ALMF algorithm allows a robust estimation of time-varying weights in the utility function at fine time aggregation levels. The high correlations among the trip attributes severely constrain the simultaneous estimation of their weights in the utility function. Despite the data limitations, it is found that, the ALMF algorithm can provide stable estimates of the choice parameters for some periods of the day. Finally, it is found that the daily variation of the user sensitivities for different periods of the day resembles a well-defined normal distribution.

Leaf gas exchange characteristics of three neotropical mangrove species in response to varying hydroperiod

We determined how different hydroperiods affected leaf gas exchange characteristics of greenhouse-grown seedlings (2002) and saplings (2003) of the mangrove species Avicennia germinans (L.) Stearn., Laguncularia racemosa (L.) Gaertn. f., and Rhizophora mangle L. Hydroperiod treatments included no flooding (unflooded), intermittent flooding (intermittent), and permanent flooding (flooded). Plants in the intermittent treatment were measured under both flooded and drained states and compared separately. In the greenhouse study, plants of all species maintained different leaf areas in the contrasting hydroperiods during both years. Assimilation-light response curves indicated that the different hydroperiods had little effect on leaf gas exchange characteristics in either seedlings or saplings. However, short-term intermittent flooding for between 6 and 22 days caused a 20% reduction in maximum leaf-level carbon assimilation rate, a 51% lower light requirement to attain 50% of maximum assimilation, and a 38% higher demand from dark respiration. Although interspecific differences were evident for nearly all measured parameters in both years, there was little consistency in ranking of the interspecific responses. Species by hydroperiod interactions were significant only for sapling leaf area. In a field study, R. mangle saplings along the Shark River in the Everglades National Park either demonstrated no significant effect or slight enhancement of carbon assimilation and water-use efficiency while flooded. We obtained little evidence that contrasting hydroperiods affect leaf gas exchange characteristics of mangrove seedlings or saplings over long time intervals; however, intermittent flooding may cause short-term depressions in leaf gas exchange. The resilience of mangrove systems to flooding, as demonstrated in the permanently flooded treatments, will likely promote photosynthetic and morphological adjustment to slight hydroperiod shifts in many settings.

Turning Passive Detection Systems into Field Experiments: An Application Using Wetland Fishes and Enclosures to Track Fine-Scale Movement and Habitat Choice

Understanding habitat selection and movement remains a key question in behavioral ecology. Yet, obtaining a sufficiently high spatiotemporal resolution of the movement paths of organisms remains a major challenge, despite recent technological advances. Observing fine-scale movement and habitat choice decisions in the field can prove to be difficult and expensive, particularly in expansive habitats such as wetlands. We describe the application of passive integrated transponder (PIT) systems to field enclosures for tracking detailed fish behaviors in an experimental setting. PIT systems have been applied to habitats with clear passageways, at fixed locations or in controlled laboratory and mesocosm settings, but their use in unconfined habitats and field-based experimental setups remains limited. In an Everglades enclosure, we continuously tracked the movement and habitat use of PIT-tagged centrarchids across three habitats of varying depth and complexity using multiple flatbed antennas for 14 days. Fish used all three habitats, with marked species-specific diel movement patterns across habitats, and short-lived movements that would be likely missed by other tracking techniques. Findings suggest that the application of PIT systems to field enclosures can be an insightful approach for gaining continuous, undisturbed and detailed movement data in unconfined habitats, and for experimentally manipulating both internal and external drivers of these behaviors.

A framework for policy based coordinated adaptation in mobile systems

Adaptation is an important requirement for mobile applications due to the varying levels of resource availability that characterizes mobile environments. However without proper control, multiple applications can each adapt independently in response to a range of different adaptive stimuli, causing conflicts or sub optimal performance. In this thesis we presented a framework, which enables multiple adaptation mechanisms to coexist on one platform. The key component of this framework was the 'Policy Server', which has all the system policies and governs the rules for adaptation. We also simulated our framework and subjected it to various adaptation scenarios to demonstrate the working of the system as a whole. With the help of the simulation it was shown that our framework enables seamless adaptation of multiple applications.