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The capacity of today’s transportation network in Alexandria cannot handle the increasing number of vehicles. The root of traffic congestion in Alexandria is most likely as result of urban planning failure, an inadequate public transportation network, strong population growth, lack of enforcement of traffic laws, complex spatial street network and poor road quality.The aim with this thesis is to simulate various traffic scenarios for the purpose of studying, evaluating and improving the traffic conditions on the intersection Al-Ibrahimeya, however, for long-term efficiency and improvement in Al-Ibrahimeya, the traffic conditions in the entire system be improved.In this thesis, a model was built in the microscopic software VISSIM and macroscopic software SYNCHRO. The model is calibrated based on data collected from video recording. Two alternative solutions to overcome the congested traffic conditions were tested. Signalization has been the main alternative solution performed for intersection Al- Ibrahimeya.The simulation results showed some improvements in terms of delay and travel time. Roundabouts are usually suitable for under low to mid traffic conditions. When there is a heavy traffic flow, as in this case, roundabouts are not suitable and may cause problem in the network. Implementing signals led to some decrease in the entering and exiting flows because the total network became more controlled. However, an organized and well-functioning signalization program helped to reduce delay and travel time in most of routes.

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<p dir="ltr">The transportation system is facing serious safety concerns at work zones and intersections, which are two major areas where accidents and fatalities occur. In addition, slow improvement in transportation industry workers’ performance is also a bottleneck to overall productivity. This dissertation aims to integrate artificial intelligence and human factors to improve the safety of mobile work zones and unsignalized intersections and monitor real-time worker’s performance.</p><p dir="ltr">To improve work zone safety, the Autonomous Truck Mounted Attenuator (ATMA) technology is explored with support from the Indiana Department of Transportation (INDOT). The ATMA can be driven automatically which removes drivers from the TMA truck to improve their safety. In this study, the ATMA system was tested under four mobile work zone operations, including trash pickup, crack sealing, Raised Pavement Marking (RPM) inspection, and drainage inspection with several roadway types, including interstate, trunk highway, and state road. During the testing, video, motion, and physiological data from the workers is collected. The data is used to develop models for transportation construction workers’ activity classification and physical fatigue level monitoring using various machine learning techniques. In addition, workers’ perception of the ATMA system is collected by a survey and the results found that more training or exposure to the ATMA system improved their evaluation of the system.</p><p dir="ltr">To improve unsignalized intersection safety, an in-vehicle warning system is developed and evaluated under various levels of aggressive vehicle behaviors across different warning conditions through a driving simulator study. A customized driving simulator is developed to support human driving experiment, which integrates SUMO and Webots. A real-world roundabout is built and calibrated in the simulator and both driving performance and eye movement data are collected from the experiments. The results indicate that advanced warnings can effectively influence vehicle speed, steering wheel control, and drivers’ attention on different areas of interests (AOIs). It is found that a proper warning time is critical to improve drivers’ safety and comfort. Gender differences are also identified from both types of data. Interestingly, although male drivers and female drivers demonstrate different driving behaviors, their safety performance in terms of minimum time to collision (TTC) is similar. Finally, to better facilitate the design of the advanced warning systems, two machine learning models are developed to predict minimum TTC and classify drivers’ perceived risk.</p><p dir="ltr">The contributions of this dissertation are summarized from the following four perspectives. First, this dissertation contributes to the body of knowledge by using a Deep Learning (DL)-based model for mobile work zone workers’ activity classification. The dissertation also innovatively integrates domain knowledge to refine the DL-based model’s performance. Second, this dissertation advances the application of feature-level data fusion in monitoring transportation construction workers. Specifically, the feature-level data fusion between kinematic and physiological data is found effective in improving model accuracy. Third, to improve mobile work zone safety, the ATMA system is tested with various road maintenance activities. This is the first ATMA test with a focus on mobile work zone operations with human workers working on the ground. The testing results are valuable for the future ATMA design and implementation. Fourth, this dissertation discloses the positive impacts of in-vehicle warning systems in roundabout merging scenarios. Furthermore, a customized driving simulator is developed to support human driving simulation experiments and is open-sourced for public use.</p>

Assuming that vehicle connectivity technology matures and connected vehicles hit the market, many of the running vehicles will be equipped with highly sophisticated sensors and communication hardware. Along with the goal of eliminating human distracted driving and increasing vehicle automation, it is necessary to develop novel intersection control strategies. Accordingly, the research presented in this dissertation develops an innovative system that controls the movement of vehicles using cooperative cruise control system (CACC) capabilities entitled: iCACC (intersection management using CACC). In the iCACC system, the main assumption is that the intersection controller receives vehicle requests from vehicles and advises each vehicle on the optimum course of action by ensuring no crashes occur while at the same time minimizing the intersection delay. In addition, an innovative framework has been developed (APP framework) using the iCACC platform to prioritize the movements of vehicles based on the number of passengers in the vehicle. Using CACC and vehicle-to-infrastructure connectivity, the system was also applied to a single-lane roundabout. In general terms, this application is considered quite similar to the concept of metering single-lane entrance ramps. The proposed iCACC system was tested and compared to three other intersection control strategies, namely: traffic signal control, an all-way stop control (AWSC), and a roundabout, considering different traffic demand levels ranging from low to high levels of congestion (volume-to-capacity ration from 0.2 to 0.9). The simulated results showed savings in delay and fuel consumption in the order of 90 to 45 %, respectively compared to AWSC and traffic signal control. Delays for the roundabout and the iCACC controller were comparable. The simulation results showed that fuel consumption for the iCACC controller was, on average, 33%, 45% and 11% lower than the fuel consumption for the traffic signal, AWSC and roundabout control strategies, respectively. In summary, the developed iCACC system is an innovative system because of its ability to optimize/model different levels of vehicle automation market penetrations, weather conditions, vehicle classes/models, shared movements, roundabouts, and passenger priority. In addition, the iCACC is capable of capturing the heterogeneity of roadway users (cyclists, pedestrians, etc.) using a video detection technique developed in this dissertation effort. It is anticipated that the research findings will contribute to the application of automated systems, connected vehicle technology, and the future of driverless vehicle management. Finally, the public acceptability of the new advanced in-vehicle technologies is a challenging task and this research will provide valuable feedback for researchers, automobile manufacturers, and decision makers in making the case to introduce such systems. / Ph. D.

The aim of my master's thesis is the design of traffic connection between newly emerging commercial and industrial area in Trnava and Nitranská street. The design of TURBO roundabout was demanded. Parking places for SAD drivers are also designed as well as the roads for pedestrians and the interchange with railway line.

The subject of the thesis is a design of variants of the solutions of the existing intersection streets of Masarykova, Sušilova and Nádražní in the town of Blansko. The reason for its processing is to find out the possibility of a prospective solution of the intersection. The output of the work is proposed two variants and their comparison in terms of capacity and traffic. The work also contains an evaluation of the traffic survey, capacity assessment of prospective intensities, price estimation of both variants and verification of the passage of the roundabout. The proposed variants improve static transport in the area.

Cyclists as vulnerable road users are oftentimes unprotected with exposed human body, can fall easily and sustain serious injuries when encountered collisions, especially with motorists. At roundabouts, accident reduction rate for cyclists is rather uncertain or sometimes less favorable compared to other road users (e.g. motorists, pedestrians). This thesis focuses on advancing the understanding of traffic safety issues for cyclists at roundabouts by identifying concerns faced by cyclists and evaluating their designs to find out which configuration has high or higher safety level towards cyclists. The research approach adopted in this work includes a wide review of relevant literature on cyclist safety and roundabouts and the implementation of empirical research, the latter was carried out through a Case Study in Norrköping city by obtaining cyclist related accident data from Swedish Traffic Accident Data Acquisition database to identify roundabouts with high cyclist-related accidents in the city assisted with PTV Visum Safety tool and fetching traffic volume from city network model operated by Norrköping Municipality for each identified roundabout. The main findings from this research conclude that single-lane roundabouts with separated cycle paths in high traffic volume setting provide better or higher safety performance for cyclists compared to other roundabout configurations.

This diploma thesis deals with the reconstruction of intersection streets Jeremenkova, Pasteurova and Černá cesta. This design is a new roundabout with three branches and one bypass. The aim of renovation is to improve traffic safety at the intersection and increasing continuity and respecting architectural principles. This project addresses the design of roundabout, analyzing problems and developer technical studies.

In the future, there should be a construction of bypasses for the residential areas of Rosice and Tetčice. The bypasses should be, according to the area planning, connected to road I/23 in the place of the existing T-junction of this road and road II/394, located to the east of the city Rosice. This connection will require the changing of the exisisting junction solutions. The thesis deals with the choice of the appropriate type of junctions and mainly contains the study of this designed interchange junction.