Kaisar, Evangelos I.

This study aims to address the unique challenges of transportation in rural and disconnected communities through innovative data-driven methodologies. The primary methods employed in this research involve Geographic Information Systems (GIS) tools and simulation techniques to model and assess the impact of flood zones on rural traffic dynamics. The study recognizes the distinct mobility patterns and limited infrastructure prevalent in rural areas, emphasizing the need for tailored solutions to manage flood-induced disruptions. By leveraging GIS tools, the study intends to spatially analyze existing transportation networks, population distribution, flood-prone areas, and key points of interest to formulate a comprehensive understanding of the local context. Simulation-based approaches using the PTV VISSIM platform will be employed to model and assess various flood scenarios and their effects on traffic flow and accessibility. This study’s outcomes aim to contribute valuable insights into improving accessibility, efficiency, and safety in transportation for these underserved areas during flood events. By combining GIS tools and simulation techniques, this research seeks to provide a robust framework for data-driven decision-making and policy formulation in the realm of rural and disconnected community mobility, particularly in the context of flood risks.

Intermodal facilities, including port operations, play a significant role in the economic framework of the United States by making substantial contributions to the country's GDP, but face challenges managing increased freight volumes. However, increased transportation time within port facilities leads to higher costs, emissions, and impacts on efficiency and sustainability. This thesis aims to develop a concept of operations (ConOps) for improving the efficiency of heavy truck movement outside ports, with goals of reducing congestion, considering greenhouse gas (GHG) emissions, and addressing issues faced by the truck drivers. The study proposes integrating technological solutions to streamline heavy truck traffic at intermodal port facilities, including scheduled truck arrivals and departures, truck stop and rest areas near ports, real-time traffic information, implementation of dedicated truck lanes, and autonomous truck platooning. The focus is improving communication, efficiency, and safety for trucking companies, operations managers, and truck drivers. Using microsimulation modeling in PTV VISSIM (2023), a traffic impact study is also conducted, focusing on a case study near the Port of Miami. A base scenario is developed to represent current traffic conditions, and additional scenarios are implemented to evaluate different strategies, such as dedicated and exclusive truck lanes, freeway lane restrictions, and autonomous truck platooning. Simulation findings emphasize the positive impact of these strategies on travel times and delays, and forecast scenarios account for increased truck volumes. Dedicated truck lanes and truck platooning demonstrate promising results in reducing congestion and improving overall traffic flow. This research supports decision-making for government officials and logistics service providers in sustainable and efficient intermodal freight planning. The study also suggests opportunities for future extensions, including emerging technologies and tailored solutions for different port locations and contexts.

Urban freight system constitutes an essential component for both economic and social aspects of the urban areas. However, the driving forces of globalization and ecommerce have adversely affected the volume of freight vehicles in urban roads over the past few decades impacting the sustainability and efficiency of last-mile deliveries. At the same time, the last-mile problem of goods distribution from companies to customers comprises one of the most costly and highest polluting components of the supply chain. Over the past few years, different innovative concepts of autonomous vehicles were introduced to improve last-mile logistic inefficiencies such as traffic congestion and pollution externalities. The objective of this study is to optimize a distribution network consisting of a set of depots and customers by utilizing Autonomous Delivery Robots (ADRs). For that reason, a Mixed Integer Linear Programming model was developed in GAMS for solving the vehicle routing problem while minimizing the total delivery and delay costs of ADRs. This optimization model is based on the route assignment and the required number of ADRs within the network. A heuristic solution algorithm based on the cluster-first, route-second technique was developed in MATLAB for solving the NP-hard problem efficiently. First the customers were clustered to depots based on their maximum distance from them and the maximum allowed number of customers per cluster. After the clustering, the mathematical model was implemented in each cluster providing an exact solution. Three different medium-sized scenarios of 200, 300 and 400 customers were tested under three different clustering instances of a maximum of 20, 30 and 40 customers per cluster and their results were presented and discussed in detail.

Transit Signal Priority (TSP) is an operational strategy that facilitates the movement of transit vehicles, either buses or streetcars, through traffic-signal controlled intersections. As transportation demand increases various transportation networks are facing increasing congestion. To mitigate the high-density impact of congestion on transit operations, TSP is a significant solution and has been widely applied to improve transit service quality and increase bus ridership. TSP can be planed and implemented considering many variables to achieve several valuable benefits such as: reducing transit travel times, better schedule adherence, and better transit efficiency. The objective of this research is to develop warrants and performance standards for transit agencies to implement signal priority based on identified decision factors. The research assesses existing guidelines and provides new guidelines for TSP implementation. Furthermore, this research evaluates the effectiveness of TSP in improving the performance of public transportation bus lines. The improvements are assessed by comparing the total travel time and total delay on the same single corridor with and without TSP applied utilizing microscopic analysis. The results show significant improvements in reducing the travel times and delays for the buses as a result of applying the TSP.

The Freight Mobility Research Institute’s (FMRI) contribution focuses on promoting smart cities, improving multimodal connections, system integrations and security, data modeling, and analytical tools. The ultimate goal of the FMRI is to optimize freight movements for improving the overall freight transportation efficiency. The FMRI's mission is to address critical issues affecting planning, design, operation, and safety of the nation’s intermodal freight transportation systems, in order to strengthen nation’s
economic competitiveness.

The Freight Mobility Research Institute’s (FMRI) contribution focuses on promoting smart cities, improving multimodal connections, system integrations and security, data modeling, and analytical tools. The ultimate goal of the FMRI is to optimize freight movements for improving the overall freight transportation efficiency. The FMRI's mission is to address critical issues affecting planning, design, operation, and safety of the nation’s intermodal freight transportation systems, in order to strengthen nation’s
economic competitiveness.

Efficient freight mobility plays a major role in the economy, and its performance is closely related to the quality of the transportation system. Requirements for funding transportation infrastructure projects often do not specify the analytical tools planners should use to request funding. Critical Urban and Rural Freight Corridors are sections of the National Highway Freight Network providing critical connectivity of goods and must have improved system performance. This research study offers a method for identifying these corridors considering temporal and spatial inputs. For this end, a multi-criteria spatial decision support system (MC-SDSS) was developed. This framework attributes a score to highway corridors (links) based on policy eligibility and prioritization. We apply the Analytic Hierarchy Process (AHP) to structure the problem and consider different stakeholder preferences and available data. The product of this study is a tool for decisionmakers to optimize the selection of critical freight corridors and analyze alternatives. It also offers flexibility to manipulate the framework to meet various agency goals, using the State of Florida as a case study.

The transportation system is particularly vulnerable to disruptive events, while at the same time it is the primary sector for preparedness management and mitigation. The objective of this research is to quantify the changes in vehicle movement during non-recurrent events (Hurricane Irma 2017, Hurricane Michael 2018, and the COVID-19 pandemic in 2020) by comparing with recurrent period for different categories of vehicles, with an emphasis on freight vehicles. This research sought to identify where and when different classes of vehicles were traveling leading up to hurricane landfall and post-storm re-entry. Moreover, this study aims to understand the impact of the pandemic based on different decision made by government and how this decision was affected by the changes in the daily number of cases. The most significant findings showed that the transportation system is very exposed to disruptive events and needs considerable time to recover and adapt. In addition, it was found that freight vehicle transport experience significant changes after the evacuation and the last phases of the pandemic. The less impacted vehicles are those who belong to vehicle category 9 . This category did not have many days with significant changes. On the other hand, the most affected categories were vehicles in category 5 for evacuations and vehicles in categories 5 and 8 for the pandemic. These findings indicate the vehicle category is a parameter that should be taken into consideration in various emergency event management. The guidance of each vehicle group should have a unique design in order to increase management success by the competent authorities.

Different innovative concepts are aiming to improve last-mile urban logistics and reduce traffic congestion. Congested metropolitan cities are implementing last-mile delivery robots to make the delivery cheaper and faster. A key factor for the success of Automated Delivery Robots (ADRs) in the last-mile is its ability to meet the fluctuating demand for robots at each micro-hub. Delivery companies rent robots from micro-hubs scattered around the city, use them for deliveries, and return them at micro-hubs. This paper studies the dynamic assignment of the robots to satisfy their demands between the micro-hubs. A Mixed-Integer Linear Programming (MILP) model is developed, which minimizes the total transportation costs by determining the optimum required fleet size. The result determines the number of robots required for each planning period to meet all the demands. It provides algorithms to operate and schedule the robot-sharing system in the last leg of the delivery in dense urban areas.

Lately, the attractiveness of cities has contributed to a rise in vehicle movements to and from cities. The growth of freight movements in cities predictably will be one of the critical issues of the near future. Congestion caused by the increased movements of freight impacts the flow of private and transit vehicles. Thus, it is crucial to reduce the congestion on multimodal corridors. Components of the Intelligent Transportation System (ITS) such as Freight Signal Priority (FSP) and Transit Signal Priority (TSP) that promote the freight and transit vehicles may not only help solve these conditions but may assist with the sustainability of the system. The primary objective of this research is to develop guidelines for traffic agencies to implement signal priorities based on identified decision factors on certain corridors. Besides, this study evaluates the efficiency of FSP and TSP in improving the performance of freight and transit systems. Finally, inclusive guidelines are drawn up based on the literature and the conducted simulation. The developed guidelines apply to corridors where freight delay plays a vital role in the assessment of corridor benefits.