Title: Monitoring the frequency of set in the practice and before the match. The diploma thesis focuses on monitoring the activities of coaches in the performance and top categories. The subsequent comparison of the results was based on the answers from the questionnaire survey. The questionnaire has ten questions in Czech and English, which are focused on the topic. The evaluation was depicked in graphs, which are supplemented by a verbal evaluation. Of the four hypotheses developed, three were confirmed and one was not. The overall comparison turned out to be that foreign coaches pay more attention to the setting, either in the training unit or before the match. Then the licensed trainers and / or the trained trainers pay attention to the setting in the same way, and the priority parameter for creating a training unit is mostly the setting. Keywords: set, beachvolleyball, practice, warm up before match

Increasing amounts of food waste is becoming a problem in developed countries. This research project is about how to reduce food waste by tracking fridge inventory and the best-before date of fridge stored food by a smartphone application. Food waste occurs in several different ways. It can be found in the household, retail stores and in the catering and events sector. Food waste can also be classified as avoidable waste, possibly avoidable waste and unavoidable waste. This project focuses on the household sector and the use of a mobile application to track fridge inventory and best-before date. The purpose of the application is to try to reduce household food waste. There is previous research about reducing household food waste using mobile applications and they all take different approaches. This study focuses on building upon these previous approaches together with data gathered from our own questionnaire with Sweden as primary focus. The combined data results in our own mobile application solution that has been tested by users in Swedish households. The study’s research question is addressed by the use of the application during a period of one-week observation. Our data collection consists of the participants being interviewed at the end of the observation period. The interviews gathered information related to whether the users successfully reduced food wastage in their households.

While weaving maneuvers occur on every type of roadway, most studies have focused on freeway maneuvers. Weaving occurring on non-freeway facilities, such as arterial streets, can cause significant operational problems. Arterial streets weaving typically occur when vehicles coming from a side street at an upstream intersection attempt to enter the main street from one side to reach access points on the opposite site at a downstream intersection by crossing one or more lanes. This dissertation investigates the type of problems occurring on arterial streets due to the weaving movements and recommends a new design to alleviate weaving on arterial streets. Firstly, the dissertation examined the different weaving movements occurring between two close-spaced intersections at two sites in Florida and explained the breakdown conditions caused by the weaving movements at the two sites. Secondly, the dissertation proposed a new design, Right Turn Split (RTS), to alleviate the delay caused by the weaving movements. The new design proposed separating the worst weaving movement entering the arterial from the other movements and providing a separate path for this movement. The new method is easy to implement and does not require much right of way. Thirdly, the dissertation compared two microscopic models, SimTraffic and VISSIM, to choose the most suitable model to be used to study the operational benefits of the RTS design. Based on the results of the comparison, it was decided to use SimTraffic for the analysis. Fourthly, the dissertation proposed a new calibration and validation procedure for microscopic simulation models. The procedure was applied on SimTraffic using the traffic data from the two studied sites. The proposed procedure appeared to be properly calibrating and validating the SimTraffic simulation model. Finally, the calibrated and validated model was used to study the operational benefits of the RTS design. Using a wide range of geometric and volume conditions, 729 before and after pairs were created to compare the delay of similar scenarios before and after applying the RTS design. The results were analyzed graphically and statistically. The findings of the analysis showed that the RTS design provided lower delay on the arterial street than the original conditions.

The purpose of this thesis is to explore how the installations of traffic signals affect crash experience at intersections, to identify those factors which help predict crashes after a signal is installed, and to develop a crash prediction model. It is the intent of this thesis to supplement the Manual on Uniform Traffic Control Devices Signal Warrant procedure and aid the traffic engineer in the signal installation decision making process. Crash data, as well as operational and geometric factors were examined for 32 state road intersections in the northeast Florida area before and after signal installation. Signal warrant studies were used as sources for traffic volumes, geometric information and crash history, before signal installation. The Florida Department of Transportation's Crash Analysis Reporting System (CARS) was used to gather crash data for the time period after signal installation. On average, the 32 intersections experienced a 12% increase in the total number of crashes and a 26% reduction in crash rate after signals were installed. The change in the number of crashes was not significant, but the rate change was significant with 90% confidence. Angle crash frequency dropped by 60% and the angle crash rate dropped by 66%, both are significant. Left-turn crashes dropped by 8% and their rate by 16%, although neither was significant. Rear-end crashes increased by 86% and the rear-end crash rate decreased by 5%. Neither of these changes was statistically significant. When crash severity was examined, it was found that the number of injury crashes increased by 64.8% and the rate by only 0.02%. Neither change was significant. Both the number of fatal crashes and the rate decreased by 100% and were significant. Property Damage Only (PDO) crashes increased by 96%, after signalization, but this change was not significant. The PDO rate, however, decreased by 46.5% and is significant. Operational factors such as AADT, turning movement counts, and speed limits; and geometric factors such as medians, turn lanes and numbers of lanes were considered to determine their effect on crashes at signalized intersections. Smaller roads, with low AADT, fewer lanes, and a rural character were found to benefit from signalization more than busier urbanized roads, in terms of crash rate reduction. The AADT, roadway cross section, number of lanes, medians, speed limit and left turn volume were all found to be important factors influencing crash rates. This thesis recommends: 1) the use of crash prediction models to supplement the MUTCD Crash Warrant, 2) the addition of a left-turn warrant to the MUTCD signal warranting procedure, and 3) development of an intersection database containing crash data as well as operational and geometric information to aid in future research.

This research explores the red light running phenomena and offer a better understanding of the factors associated with it. The red light running is a type of traffic violation that can lead to angle crash and the most common counter measure is installing a red light running cameras. Red light running cameras some time can reduce the rates of red light running but because of the increased worry of the public towards crossing the intersection it can cause an increase in rear end crashes. Also the public opinion of the red light running cameras is that they are a revenue generator for the local counties and not a concern of public safety. Further more, they consider this type of enforcement as violation of privacy. There was two ways to collect the data needed for the research. One way is through a tripod cameras setup temporarily placed at the intersection. This setup can collect individual vehicles caught in the change phase with specific information about their reactions and conditions. This required extensive manual analysis for the recorded videos plus data could not be collected during adverse weather conditions. The second way was using traffic monitoring cameras permanently located at the site to collect red light running information and the simultaneous traffic conditions. This system offered more extensive information since the cameras monitor the traffic 24/7 collecting data directly. On the other hand this system lacked the ability to identify the circumstances associated with individual red light running incidents. The research team finally decided to use the two methods to study the red light running phenomena aiming to combine the benefits of the two systems. During the research the team conducted an experiment to test a red light running countermeasure in the field and evaluate the public reaction and usage of this countermeasure. The marking was previously tested in a driving simulator and proved to be successful in helping the drivers make better stop/go decisions thus reducing red light running rates without increasing the rear-end crashes. The experiment was divided into three phases; before marking installation called "before", after marking installation called "after", and following a media campaign designed to inform the public about the use of the marking the third phase called "after media" The behavior study that aimed at analyzing the motorist reactions toward the signal change interval identified factors which contributed to red light running. There important factors were: distance from the stop bar, speed of traffic, leading or following in the traffic, vehicle type. It was found that a driver is more likely to run red light following another vehicle in the intersection. Also the speeding vehicles can clear the intersection faster thus got less involved in red light running violations. The proposed "Signal Ahead" marking was found to have a very good potential as a red light running counter measure. The red light running rates in the test intersection dropped from 53 RLR/hr/1000veh for the "before" phase, to 24 RLR/hr/1000veh for the "after media" phase. The marking after media analysis period found that the marking can help the driver make stop/go decision as the dilemma zone decreased by 50 ft between the "before" and the "after media" periods. Analysis of the traffic condition associated with the red light running it revealed that relation between the traffic conditions and the red light running is non-linear, with some interactions between factors. The most important factors included in the model were: traffic volume, average speed of traffic, the percentage of green time, the percentage of heavy vehicles, the interaction between traffic volume and percentage of heavy vehicles. The most interesting finding was the interaction between the volume and the percent of heavy vehicles. As the volume increased the effect of the heavy vehicles reversed from reducing the red light running to increasing the red light. This finding may be attributed to the sight blocking that happens when a driver of a passenger car follows a larger heavy vehicle, and can be also explained by the potential frustration experienced by the motorist resulting from driving behind a bigger vehicle.

In recent years, the particle filter has gained prominence in the area of target tracking because it is robust to non-linear target motion and non-Gaussian additive noise. Traditional track filters, such as the Kalman filter, have been well studied for linear tracking applications, but perform poorly for non-linear applications. The particle filter has been shown to perform well in non-linear applications. The particle filter method is computationally intensive and advances in processor speed and computational power have allowed this method to be implemented in real-time tracking applications. This thesis explores the use of particle filters to detect and track stealthy targets in noisy imagery. Simulated point targets are applied to noisy image data to create an image sequence. A particle filter method known as Track-Before-Detect is developed and used to provide detection and position tracking estimates of a single target as it moves in the image sequence. This method is then extended to track multiple moving targets. The method is analyzed to determine its performance for targets of varying signal-to-noise ratio and for varying particle set sizes. The simulation results show that the Track-Before-Detect method offers a reliable solution for tracking stealthy targets in noisy imagery. The analysis shows that the proper selection of particle set size and algorithm improvements will yield a filter that can track targets in low signal-to-noise environments. The multi-target simulation results show that the method can be extended successfully to multi-target tracking applications. This thesis is a continuation of automatic target recognition and target tracking research at Cal Poly under Dr. John Saghri and is sponsored by Raytheon Space and Airborne Systems.

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