This study is concerned with the safety risk of reduced visibility on roadways. Inclement weather events such as fog/smoke (FS), heavy rain (HR), high winds, etc, do affect every road by impacting pavement conditions, vehicle performance, visibility distance, and drivers’ behavior. Moreover, they affect travel demand, traffic safety, and traffic flow characteristics. Visibility in particular is critical to the task of driving and reduction in visibility due FS or other weather events such as HR is a major factor that affects safety and proper traffic operation. A real-time measurement of visibility and understanding drivers’ responses, when the visibility falls below certain acceptable level, may be helpful in reducing the chances of visibility-related crashes. In this regard, one way to improve safety under reduced visibility conditions (i.e., reduce the risk of visibility related crashes) is to improve drivers’ behavior under such adverse weather conditions. Therefore, one of objectives of this research was to investigate the factors affecting drivers’ stated behavior in adverse visibility conditions, and examine whether drivers rely on and follow advisory or warning messages displayed on portable changeable message signs (CMS) and/or variable speed limit (VSL) signs in different visibility, traffic conditions, and on two types of roadways; freeways and two-lane roads. The data used for the analyses were obtained from a self-reported questionnaire survey carried out among 566 drivers in Central Florida, USA. Several categorical data analysis techniques such as conditional distribution, odds’ ratio, and Chi-Square tests were applied. In addition, two modeling approaches; bivariate and multivariate probit models were estimated. The results revealed that gender, age, road type, visibility condition, and familiarity with VSL signs were the significant factors affecting the likelihood of reducing speed following CMS/VSL instructions in reduced visibility conditions. Other objectives of this survey study were to determine the content of messages that iv would achieve the best perceived safety and drivers’ compliance and to examine the best way to improve safety during these adverse visibility conditions. The results indicated that "Caution-fog ahead-reduce speed" was the best message and using CMS and VSL signs together was the best way to improve safety during such inclement weather situations. In addition, this research aimed to thoroughly examine drivers’ responses under low visibility conditions and quantify the impacts and values of various factors found to be related to drivers’ compliance and drivers’ satisfaction with VSL and CMS instructions in different visibility and traffic conditions. To achieve these goals, Explanatory Factor Analysis (EFA) and Structural Equation Modeling (SEM) approaches were adopted. The results revealed that drivers’ satisfaction with VSL/CMS was the most significant factor that positively affected drivers’ compliance with advice or warning messages displayed on VSL/CMS signs under different fog conditions followed by driver factors. Moreover, it was found that roadway type affected drivers’ compliance to VSL instructions under medium and heavy fog conditions. Furthermore, drivers’ familiarity with VSL signs and driver factors were the significant factors affecting drivers’ satisfaction with VSL/CMS advice under reduced visibility conditions. Based on the findings of the survey-based study, several recommendations are suggested as guidelines to improve drivers’ behavior in such reduced visibility conditions by enhancing drivers’ compliance with VSL/CMS instructions. Underground loop detectors (LDs) are the most common freeway traffic surveillance technologies used for various intelligent transportation system (ITS) applications such as travel time estimation and crash detection. Recently, the emphasis in freeway management has been shifting towards using LDs data to develop real-time crash-risk assessment models. Numerous v studies have established statistical links between freeway crash risk and traffic flow characteristics. However, there is a lack of good understanding of the relationship between traffic flow variables (i.e. speed, volume and occupancy) and crashes that occur under reduced visibility (VR crashes). Thus, another objective of this research was to explore the occurrence of reduced visibility related (VR) crashes on freeways using real-time traffic surveillance data collected from loop detectors (LDs) and radar sensors. In addition, it examines the difference between VR crashes to those occurring at clear visibility conditions (CV crashes). To achieve these objectives, Random Forests (RF) and matched case-control logistic regression model were estimated. The results indicated that traffic flow variables leading to VR crashes are slightly different from those variables leading to CV crashes. It was found that, higher occupancy observed about half a mile between the nearest upstream and downstream stations increases the risk for both VR and CV crashes. Moreover, an increase of the average speed observed on the same half a mile increases the probability of VR crash. On the other hand, high speed variation coupled with lower average speed observed on the same half a mile increase the likelihood of CV crashes. Moreover, two issues that have not explicitly been addressed in prior studies are; (1) the possibility of predicting VR crashes using traffic data collected from the Automatic Vehicle Identification (AVI) sensors installed on Expressways and (2) which traffic data is advantageous for predicting VR crashes; LDs or AVIs. Thus, this research attempts to examine the relationships between VR crash risk and real-time traffic data collected from LDs installed on two Freeways in Central Florida (I-4 and I-95) and from AVI sensors installed on two vi Expressways (SR 408 and SR 417). Also, it investigates which data is better for predicting VR crashes. The approach adopted here involves developing Bayesian matched case-control logistic regression using the historical VR crashes, LDs and AVI data. Regarding models estimated based on LDs data, the average speed observed at the nearest downstream station along with the coefficient of variation in speed observed at the nearest upstream station, all at 5-10 minute prior to the crash time, were found to have significant effect on VR crash risk. However, for the model developed based on AVI data, the coefficient of variation in speed observed at the crash segment, at 5-10 minute prior to the crash time, affected the likelihood of VR crash occurrence. Argument concerning which traffic data (LDs or AVI) is better for predicting VR crashes is also provided and discussed.

Marine transportation in EU currently emits 18% of the total global marine CO2 emissions, which is approximately 140 million tonnes of CO2. In response to this, new regulations aim to reduce carbon emissions by 40% by the year 2030, therefore, green innovations in marine technology are more important than ever. However, reducing carbon emissions requires people to accept these new technologies. In this paper, I explore the role of human-centred design in technology acceptance by using some methods in the design process. The design process included various methods such as user-, heuristic evaluations, expert reviews, role-playing, parallel prototyping, and prototyping. I studied, evaluated, and redesigned the interface of EcoPilot, that is a product which calculates, decreases, and optimizes fuel consumption in marine transportation. The design process of EcoPilot resulted in increased knowledge about the current user experience of marine technology aimed at reducing carbon emissions, as well as conclusions and reflections on how human-centred Design can improve the experience and promote the acceptance of new green technology.

Being inconspicuous in the dark outdoors can cause accidents including physical injuries. To prevent pedestrian being involved in accidents it is necessary to make them most visible to approaching people.This Master’s Thesis examines the use of retroreflective clothing in a semi-dark urban environment to provide safety through conspicuity. Through analysing the lighting situation in Stockholm, the ability of the human vision, reactions and existing products it has led to experiments and surveys to find the most efficient line placement and pattern to make an individual recognizable as human on approach.The results were that body outlines and horizontal lines along joints made a human most identifiable. Most conspicuity was given when lines were wider than 2cm and patterns contrasted to the surroundings.As the experiment was conducted in a semi-dark setting, different retroreflective design solutions might be more adequate for other lighting scenarios with more or less light

Examination concerning the possibility of finding prehistoric children as considerable actors through the medium of neolithic clay figurines which were discovered in the archaeological remains regarding a pitted-ware settlement excavated in Tråsättra, Stockholm parish in the year 2016. The main aim for this study is to pay attention to a group of individuals most often overlooked in archaeological research as a whole, by searching to find new angles of incidence in a material previously interpreted from a ritual perspective.

Estimates of abundance are critical to manage and conserve waterfowl and their habitats. Most surveys of wintering waterfowl do not use probability sampling; therefore, development of more rigorous methods is needed. In response, I designed and evaluated an aerial transect survey to estimate abundance of wintering ducks in western Mississippi during winters 2002?2004. I designed a probability-based survey using stratified random and unequal probability sampling of fixed-width transects. To correct for visibility bias inherent in aerial surveys, I conducted an experiment to model bias and incorporated correction factors into estimation procedures to produce adjusted estimates. Bias-corrected estimates were most accurate. Precision of abundance estimates of total ducks met a priori goals (CV ≤ 15%) in 10 of 14 surveys. Based on a simulation study, the implemented survey design provided the most precise estimates, yet certain refinements remained possible. I also illustrated potential applications of survey results in the context of conservation and management of wintering waterfowl populations and habitats. I described patterns of abundance within and among winters, including a comparison with surveys conducted during winters 1988?1990 that revealed mallard abundance decreased 65% from the late 1980s. I developed a method to illustrate population abundance spatially for scientific and public education. I attempted to explain temporal variation in abundance estimates relative to variables potentially representing hypotheses explaining regional distributions of ducks. I concluded the data provided stronger support for factors related to energy conservation by ducks than factors related to energy acquisition. Finally, I determined associations between duck distributions and habitat and landscape features in accordance with the habitat-complex conceptual model. Landscapes with greater interspersion and diversity of wetlands attracted increased numbers of ducks, a though other factors such as wetland area also were important. I concluded that this study advanced methodologies to survey wintering waterfowl. Although improvements were warranted, I recommend this survey design for continued monitoring of wintering ducks in western Mississippi. Furthermore, I suggest habitat management on public and private lands should include complexes of seasonally flooded cropland, moist-soil, forested, and permanent wetlands to potentially increase wintering duck numbers in western Mississippi.

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