The Master's Thesis analyzes a logistic background of the Czech Republic in the context of the recent economic crisis and its influence on the development of selected indicators of the logistic market. The objective of the Thesis is to evaluate the impact of these aspects on lo-gistic competitiveness of the Czech Republic in Central and Eastern Europe. The Thesis de-scribes the current situation of the European logistic market together with the main future development trends. The recent development on logistics and industrial property market is worked out in detail, including the changes in attractiveness of logistics locations and criteria influencing developers' activities. Subsequently the Thesis analyzes the situation in logistics and transport infrastructure, characterizes the freight transport and presents current options for their further development. The final part of the Thesis introduces options for education in logistics available in the Czech environment.

This Master Thesis is focused on road, railway, air, river and bicycle transport infrastructure of Czech Republic with detailed focus on the city of Roudnice nad Labem and its sorroundings. Except for basic information about the infrastructure of transport modes in Roudnice nad Labem is the objective of the Thesis analysis of road transport and traffic situation in the city. The work gives a detailed analysis of the main city roads including their strengths and weaknesses, followed by a summary and comprehensive view of the traffic in the city, supported by traffic survey.

The current status of road transportation charging in the Czech Republic has been analyzed in terms of costs, which are caused by various categories of vehicles and incomes, which are generated by existing instruments of charging. Significant imbalance of theese indicators for different types of vehicles has been revealed. The measures proposed in thesis aim to eliminate this imbalance and to provide fair charging system that is based on actual costs caused by vehicle.

The Diploma Thesis is focused on description of public transport systems in Prague and Sydney and their final comparison. Theoretical part is describing development of transport, transport infrastructure, public transport priority, system of tariffs, means of transport etc. In practical part both systems are described in detail with focus on organization and functionality. Final comparison is focused on confrontation from many points of view to capture the most of identical or different aspects.

Description and evaluation of a traffic network of Pardubice in all transport sectors (air, water, railway, road and cycling) and its comparison with a network of Hradec Králové. Integration of both transport systems. Suggestions for improvement of traffic infrastructure and transport integration. Optimalization of connection of chosen urban neighbourhood with a town centre by urban mass transportation.

<p>  </p> <p>Advancements in technology have propelled the availability of enriched and more frequent information about traffic conditions as well as the external factors that impact traffic such as weather, emergency response etc. Most newer vehicles are equipped with sensors that transmit their data back to the original equipment manufacturer (OEM) at near real-time fidelity. A growing number of such connected vehicles (CV) and the advent of third-party data collectors from various OEMs have made big data for traffic commercially available for use. Agencies maintaining and managing surface transportation are presented with opportunities to leverage such big data for efficiency gains. The focus of this dissertation is enhancing the use of CV data and applications derived from fusing it with other datasets to extract meaningful information that will aid agencies in data driven efficient decision making to improve network wide mobility and safety performance.   </p> <p>One of the primary concerns of CV data for agencies is data sampling, particularly during low-volume overnight hours. An evaluation of over 3 billion CV records in May 2022 in Indiana has shown an overall CV penetration rate of 6.3% on interstates and 5.3% on non-interstate roadways. Fusion of CV traffic speeds with precipitation intensity from NOAA’s High-Resolution Rapid-Refresh (HRRR) data over 42 unique rainy days has shown reduction in the average traffic speed by approximately 8.4% during conditions classified as very heavy rain compared to no rain. </p> <p>Both aggregate analysis and disaggregate analysis performed during this study enables agencies and automobile manufacturers to effectively answer the often-asked question of what rain intensity it takes to begin impacting traffic speeds. Proactive measures such as providing advance warnings that improve the situational awareness of motorists and enhance roadway safety should be considered during very heavy rain periods, wind events, and low daylight conditions.</p> <p>Scalable methodologies that can be used to systematically analyze hard braking and speed data were also developed. This study demonstrated both quantitatively and qualitatively how CV data provides an opportunity for near real-time assessment of work zone operations using metrics such as congestion, location-based speed profiles and hard braking. The availability of data across different states and ease of scalability makes the methodology implementable on a state or national basis for tracking any highway work zone with little to no infrastructure investment. These techniques can provide a nationwide opportunity in assessing the current guidelines and giving feedback in updating the design procedures to improve the consistency and safety of construction work zones on a national level.  </p> <p>CV data was also used to evaluate the impact of queue warning trucks sending digital alerts. Hard-braking events were found to decrease by approximately 80% when queue warning trucks were used to alert motorists of impending queues analyzed from 370 hours of queueing with queue trucks present and 58 hours of queueing without the queue trucks present, thus improving work zone safety. </p> <p>Emerging opportunities to identify and measure traffic shock waves and their forming or recovery speed anywhere across a roadway network are provided due to the ubiquity of the CV data providers. A methodology for identifying different shock waves was presented, and among the various case studies found typical backward forming shock wave speeds ranged from 1.75 to 11.76 mph whereas the backward recovery shock wave speeds were between 5.78 to 16.54 mph. The significance of this is illustrated with a case study of  a secondary crash that suggested  accelerating the clearance by 9 minutes could have prevented the secondary crash incident occurring at the back of the queue. Such capability of identifying and measuring shock wave speeds can be utilized by various stakeholders for traffic management decision-making that provide a holistic perspective on the importance of both on scene risk as well as the risk at the back of the queue. Near real-time estimation of shock waves using CV data can recommend travel time prediction models and serve as input variables to navigation systems to identify alternate route choice opportunities ahead of a driver’s time of arrival.   </p> <p>The overall contribution of this thesis is developing scalable methodologies and evaluation techniques to extract valuable information from CV data that aids agencies in operational decision making.</p>