As the population grows and the travel demands increase, alternative interchange designs are becoming increasingly popular. The diverging diamond interchange is one alternative design that has been implemented in the United States. This design can accommodate higher flow and unbalanced flow as well as improve safety at the interchange. As the diverging diamond interchange is increasingly considered as a possible solution to problematic interchange locations, it is imperative to investigate the safety effects of this interchange configuration. This report describes the selection of a comparison group of urban diamond interchanges, crash data collection, calibration of functions used to estimate the predicted crash rate in the before and after periods and the Empirical Bayes before and after analysis technique used to determine the safety effectiveness of the diverging diamond interchanges in Utah. A discussion of pedestrian and cyclist safety is also included. The analysis results demonstrated statistically significant decreases in crashes at most of the locations studied. This analysis can be used by UDOT and other transportation agencies as they consider the implementation of the diverging diamond interchanges in the future.

The before-after study is still the most popular method used by traffic engineers and transportation safety analysts for evaluating the effects of an intervention. However, this kind of study may be plagued by important methodological limitations, which could significantly alter the study outcome. They include the regression-to-the-mean (RTM) and site-selection effects. So far, most of the research on these biases has focused on the RTM. Hence, the primary objective of this study consists of presenting a method that can reduce the site-selection bias when an entry criterion is used in before-after studies for continuous (e.g. speed, reaction times, etc.) and count data (e.g. number of crashes, number of fatalities, etc.). The proposed method documented in this research provides a way to adjust the Naive estimator by using the sample data and without relying on the data collected from the control group, since finding enough appropriate sites for the control group is much harder in traffic-safety analyses. In this study, the proposed method, a.k.a. Adjusted method, was compared to commonly used methods in before-after studies. The study results showed that among all methods evaluated, the Naive is the most significantly affected by the selection bias. Using the CG, the ANCOVA, or the EB method based on a control group (EBCG) method can eliminate the site-selection bias, as long as the characteristics of the control group are exactly the same as those for the treatment group. However, control group data that have same characteristics based on a truncated distribution or sample may not be available in practice. Moreover, site-selection bias generated by using a dissimilar control group might be even higher than with using the Naive method. The Adjusted method can partially eliminate site-selection bias even when biased estimators of the mean, variance, and correlation coefficient of a truncated normal distribution are used or are not known with certainty. In addition, three actual datasets were used to evaluate the accuracy of the Adjusted method for estimating site-selection biases for various types of data that have different mean and sample-size values.

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.

Soil fauna provides processes of crucial importance for ecosystem functions, but our ability to observe their actions often depend on destructive methods where the integrity of the studied environment (the soil) is compromised. In this study, I develop and test a new generation of environmental monitoring tools that utilize vibrations made by soil macrofauna to inform about their performance and health. Three hypotheses were tested on forest ants (Formica sp.): (i) vibrations on a naturally occurring substrate can be used to measure the activity of ants, (ii) the vibrational signature of ants can inform us about the ants’ health, and (iii) behavior (locomotory activity, foraging etc.) of ants is correlated to specific vibrational signal characteristics. Vibrational signals from ant sub-populations (5 individuals/sample) were recorded on natural substrates (leaves) before and after exposure to sub-lethal levels of a contaminant with known negative effects on ants (imidacloprid). Activity was successfully detected from the inferred vibration oscillograms. However, neither the number of vibrational signals captured, or the signal characteristics changed after imidacloprid exposure, indicating that either the exposure was too low to generate a change in behavior or that the technique was unable to detect subtle changes in behavior. Signals of short duration and amplitude were generated by locomotory activity, but their intensity was dependent on the distance to the vibrometers laser focus point. Longer signal segments were either continuous, random, or rhythmic in their distribution. I suggest that these signals are a result of methodological artifacts, movement of multiple ants, and stridulation/drumming on the substrate, respectively. My findings suggest that this advanced monitoring tool is sensitive enough to capture activity from only a few ants, but the characteristics and number of captured signals are strongly affected by the measured substrate

Two way left turn lanes (TWLTL) and raised medians are common median treatments on roadways. This research focused on evaluating the safety effectiveness of conversion of TWLTLs into raised medians using Before-After and Cross Sectional Studies. In the Before-After Studies, we evaluated the effect of this treatment using the Naive, Before-After with Comparison Group (CG), and Before-After with Empirical Bayes (EB) Methods. In order to apply these methods, a total of 33 segments of a treated group and 109 segments of a comparison group have been collected. Also, safety performance functions (SPFs) have been developed using the negative binomial model in order to calibrate crash modification factors (CMF) using the Before-After with Empirical Bayes Method. This research also evaluated the safety effectiveness of this treatment on four and six lane roads using Before-After with CG and Before-After with EB. The type of raised medians was further evaluated using Before-After with CG and EB. In sum, the results from this study show that applying the before-After and Cross Sectional studies have proved that the conversion from a TWLTL to a raised median helped to reduce total, fatal and injury, head on, angle, and left turn crashes. It significantly reduces crashes for head-on and left turn crashes, by restricting turning maneuvers. Also, this study has proved that the treatment is more effective on four rather than six lane roads. Furthermore, two types of raised medians, concrete and lawn curb, were evaluated after the conversion from TWLTLs. It was found that both medians have similar effects due to the conversion, and both median types helped in reducing the number of crashes.

This thesis acts as one of the first studies that analyzes the safety effects of Edge Lane Roads (ELR) for all road users. This is important since ELRs can be a solution to many issues, such as alleviating congestion, increasing multimodality along roadways, and reducing maintenance costs. ELRs in both North America and Australia were observed. Starting with the North American ELRs, the following study designs were employed to estimate the safety of ELRs: (a) yoked comparison where each ELR installation was matched with at least two comparable 2-lane roads to serve as comparison sites and (b) an Empirical Bayes (EB) before/after analysis for ELR sites where requisite data on AADT and other relevant characteristics were available. Crash data was collected and compiled into four different groups: ELR before implementation, ELR after implementation, comparison site before ELR implementation, and comparison site after ELR comparison. The yoked comparison showed 9 of the 13 sites that had lower crash counts compared to their respective comparison sites. The EB analysis showed all 11 ELRs that were observed demonstrated a reduction in crashes. Moving to the Australian ELRs, the following study designs were employed: (c) analysis of general crash counts/trends, and (d) reverse EB analysis. The analysis of general crash counts and trends showed that each of the Australian ELRs exhibited very low amounts of crashes for 5 years, which further shows how safe these facilities are. Moving forward to the reverse EB analysis, 5 of the 8 ELR sites demonstrated a reduction in crashes. Overall, the results were generally favorable and indicated that ELRs provided a safer experience for cyclists, drivers, and pedestrians. More analysis is recommended as more data becomes available on these ELRs. Examples of this include using pedestrian and bicycle data to better understand the safety effects VRUs experience on North American facilities or gathering enough crash data to conduct 3-year reverse EB analyses for ELRs that were expanded to 2-lane roads. Hence, a recommendation can be made to implement a few experimental ELRs in rural locations throughout the State of California to help it meet its SB-1 objectives.

This work treats about before/after shool clubs educational programmes key competences classification and work out. In its theoretical part, the work aims at before/after school club´s characterization, role, function and its objectives´ definition. There is marginally before/after school club documentation mentioned as well. In more details, it pays attention to school eductaional programme that is worked out by before/after shool club. The work points out connection of before/after school club´s educational programme with elemntary school´s educational programme. There are highlited several attitudes to incorporation of key competences into the document ? is it obligation, or not? Different ways of key competences development in before/after school club are introduced here as well. The field part is aimed at particular processing of key competences in before/after school clubs´ school educational programmes in the whole Czech Republic. The documents were clasified into several groups according to their classification profundity and according to their key competences´elaboration. Further, the work is aimed only at the third group, exploring the key competences´ content, style and porcessing extent. The shortcomings in connection between particular activities and developed competences are in this work pointed out as well.

Les notions de plateforme, de marché bifaces ou même multi-faces sont aujourd’hui au cœur des discussions économiques du fait de l’explosion du e-commerce lié à l’essor des nouvelles technologies de l’information. Ces plateformes en lignes offrent de nouvelles opportunités et soulèvent de nombreuses questions (stratégie tarifaire, règlementation, etc.). Les deux premiers chapitres de cette thèse s’intéressent aux plateformes de réservation en ligne et plus particulièrement à l’impact concurrentiel des clauses de parités tarifaire. Ces dernières, mises en place par les plateformes, imposent aux vendeurs de proposer son bien ou service via la plateforme au meilleur prix disponible sur tous les autres canaux de ventes. Dans le premier chapitre, je montre que, d'un point de vue théorique, l'effet concurrentiel des clauses de parité est majoritairement négatif mais peut devenir positif en fonction du pouvoir de négociation de chacun des acteurs. Dans un second temps, une analyse empirique reposant sur une base de données unique de plus de 6 millions de prix, me permet de montrer que la suppression des clauses de parité à Paris a engendré une baisse tarifaire moyenne des hôtels de -3,1% à - 4,5%. Cette baisse peut en partie s'expliquer par une augmentation des stratégies de discrimination tarifaire. En effet, les hôtels ont augmenté de 1,4 à 2,3% la discrimination entre plateformes et ils ont augmenté de 2,1% à 3,6% leurs stratégies de discrimination inter-temporelle. Le dernier chapitre de cette thèse est dédié à l'analyse des amendes décidées par l'Autorité de la Concurrence entre 2006 et 2018 pour des pratiques de cartels. Nous montrons que ces amendes sont sous optimales car elles ne satisfassent pas les critères de dissuasion et de compensation. / The Internet technology and the web economy create new types of markets and new relationships between market players. The majority of these new markets can be associated to platforms where two or more sides of the same market meet. Such “multi-sided” industries raise specific issues. Determining the optimal pricing strategy for both the platform and the users selling goods through the platform is one of the main challenges of this new economy. The first two chapters of my thesis analysis Price Parity Agreement (PPA) from a theoretical and an empirical point of view. I first study the effect of Price Parity Agreements from a theoretical perspective. I demonstrate that PPAs on the online booking market are detrimental to consumers if platforms have most of the bargaining power. They attenuate competition between platforms, lead to higher commission fees and higher hotel rooms’ prices. However, MFN clauses may also be welfare improving when hotels own the bargaining power and competition between them is high. The second chapter is dedicated to an empirical analysis of the effects of PPAs. Using a before-after design and controlling for external shocks, I demonstrate that the end of Price Parity Agreements imposed by public authorities to OTAs causes a decrease of about 3.1% to 4.5% in the average level of prices set by hotels. This decrease may be explained by an increase of price discrimination. I show that the level of price discrimination across OTAs increases by 2.3% to 1.4% after the drop of Price Parity Agreements and that the degree of inter-temporal price discrimination also increases by 3.6% to 2.1%. The last chapter of my thesis is focused on the analysis of the financial fines imposed by the French Autorité de la Concurrence to cartels in France between 2006 and 2018. We show that the level of these fines is sub-optimal and doesn’t meet the deterrence objective in the majority of the cases.

Traffic safety is a major concern for the public, and it is an important component of the roadway management strategy. In order to improve highway safety, extensive efforts have been made by researchers, transportation engineers, Federal, State, and local government officials. With these consistent efforts, both fatality and injury rates from road traffic crashes in the United States have been steadily declining over the last six years (2006~2011). However, according to the National Highway Traffic Safety Administration (NHTSA, 2013), 33,561 people died in motor vehicle traffic crashes in the United States in 2012, compared to 32,479 in 2011, and it is the first increase in fatalities since 2005. Moreover, in 2012, an estimated 2.36 million people were injured in motor vehicle traffic crashes, compared to 2.22 million in 2011. Due to the demand of highway safety improvements through systematic analysis of specific roadway cross-section elements and treatments, the Highway Safety Manual (HSM) (AASHTO, 2010) was developed by the Transportation Research Board (TRB) to introduce a science-based technical approach for safety analysis. One of the main parts in the HSM, Part D, contains crash modification factors (CMFs) for various treatments on roadway segments and at intersections. A CMF is a factor that can estimate potential changes in crash frequency as a result of implementing a specific treatment (or countermeasure). CMFs in Part D have been developed using high-quality observational before-after studies that account for the regression to the mean threat. Observational before-after studies are the most common methods for evaluating safety effectiveness and calculating CMFs of specific roadway treatments. Moreover, cross-sectional method has commonly been used to derive CMFs since it is easier to collect the data compared to before-after methods. Although various CMFs have been calculated and introduced in the HSM, still there are critical limitations that are required to be investigated. First, the HSM provides various CMFs for single treatments, but not CMFs for multiple treatments to roadway segments. The HSM suggests that CMFs are multiplied to estimate the combined safety effects of single treatments. However, the HSM cautions that the multiplication of the CMFs may over- or under-estimate combined effects of multiple treatments. In this dissertation, several methodologies are proposed to estimate more reliable combined safety effects in both observational before-after studies and the cross-sectional method. Averaging two best combining methods is suggested to use to account for the effects of over- or under- estimation. Moreover, it is recommended to develop adjustment factor and function (i.e. weighting factor and function) to apply to estimate more accurate safety performance in assessing safety effects of multiple treatments. The multivariate adaptive regression splines (MARS) modeling is proposed to avoid the over-estimation problem through consideration of interaction impacts between variables in this dissertation. Second, the variation of CMFs with different roadway characteristics among treated sites over time is ignored because the CMF is a fixed value that represents the overall safety effect of the treatment for all treated sites for specific time periods. Recently, few studies developed crash modification functions (CMFunctions) to overcome this limitation. However, although previous studies assessed the effect of a specific single variable such as AADT on the CMFs, there is a lack of prior studies on the variation in the safety effects of treated sites with different multiple roadway characteristics over time. In this study, adopting various multivariate linear and nonlinear modeling techniques is suggested to develop CMFunctions. Multiple linear regression modeling can be utilized to consider different multiple roadway characteristics. To reflect nonlinearity of predictors, a regression model with nonlinearizing link function needs to be developed. The Bayesian approach can also be adopted due to its strength to avoid the problem of over fitting that occurs when the number of observations is limited and the number of variables is large. Moreover, two data mining techniques (i.e. gradient boosting and MARS) are suggested to use 1) to achieve better performance of CMFunctions with consideration of variable importance, and 2) to reflect both nonlinear trend of predictors and interaction impacts between variables at the same time. Third, the nonlinearity of variables in the cross-sectional method is not discussed in the HSM. Generally, the cross-sectional method is also known as safety performance functions (SPFs) and generalized linear model (GLM) is applied to estimate SPFs. However, the estimated CMFs from GLM cannot account for the nonlinear effect of the treatment since the coefficients in the GLM are assumed to be fixed. In this dissertation, applications of using generalized nonlinear model (GNM) and MARS in the cross-sectional method are proposed. In GNMs, the nonlinear effects of independent variables to crash analysis can be captured by the development of nonlinearizing link function. Moreover, the MARS accommodate nonlinearity of independent variables and interaction effects for complex data structures. In this dissertation, the CMFs and CMFunctions are estimated for various single and combination of treatments for different roadway types (e.g. rural two-lane, rural multi-lane roadways, urban arterials, freeways, etc.) as below: 1) Treatments for mainline of roadway: - adding a thru lane, conversion of 4-lane undivided roadways to 3-lane with two-way left turn lane (TWLTL) 2) Treatments for roadway shoulder: - installing shoulder rumble strips, widening shoulder width, adding bike lanes, changing bike lane width, installing roadside barriers 3) Treatments related to roadside features: - decrease density of driveways, decrease density of roadside poles, increase distance to roadside poles, increase distance to trees Expected contributions of this study are to 1) suggest approaches to estimate more reliable safety effects of multiple treatments, 2) propose methodologies to develop CMFunctions to assess the variation of CMFs with different characteristics among treated sites, and 3) recommend applications of using GNM and MARS to simultaneously consider the interaction impact of more than one variables and nonlinearity of predictors. Finally, potential relevant applications beyond the scope of this research but worth investigation in the future are discussed in this dissertation.

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