Transportation

Every passenger vehicle must rely on a safe and optimal trajectory to eliminate traffic incidents and congestion as well as to reduce environmental impact, and travel time. Autonomous intersection management systems (AIMS) enable large scale optimization of vehicular trajectories with connected and autonomous vehicles (CAVs). The first contribution of this dissertation is the fastest trajectory planner (FTP) method which is geared for computing the fastest waypoint trajectories via performing graph search over a discretized space-time (ST) graph (Gt), thereby constructing collision-free space-time trajectories with variable vehicular speeds adhering to traffic rules and dynamical constraints of vehicles. The benefits of navigating a connected and autonomous vehicle (CAV) truly capture effective collaboration between every CAV during the trajectory planning step. This requires addressing trajectory planning activity along with vehicular networking in the design phase. For complementing the proposed FTP method in decentralized scenarios, the second contribution of this dissertation is an application layer V2V solution using a coordinator-based distributed trajectory planning method which elects a single leader CAV among all the collaborating CAVs without requiring a centralized infrastructure. The leader vehicular agent calculates and assigns a trajectory for each node CAV over the vehicular network for the collision-free management of an unsignalized road intersection. The proposed FTP method is tested in a simulated road intersection scenario for carrying out trials on scheduling efficiency and algorithm runtime. The resulting trajectories allow high levels of intersection sharing, high evacuation rate, with a low algorithm single-threaded runtime figures even with large scenarios of up to 1200 vehicles, surpassing comparable systems.

This thesis examined the road impact fee realities of 11 of Palm Beach County’s public and private sector land development stakeholders. To learn more about how the county’s road impact fee ordinance works in practice, in 2021, 11 stakeholders were interviewed about their experiences with the county’s road impact fee program. Transportation impact fee programs may help relieve development-driven traffic externalities and cost burdens, so long as suitable methodologies are applied (Burge & Ihlanfeldt, 2013; Stahl, 2021). In 2021, Palm Beach County’s road impact fee ordinance required all county development applicants to pay a specified road impact fee dollar amount, regardless of the proposed project’s location and traffic impact, with exceptions (Moore, 2021b; Salour, 2021). Key arguments for and against the county’s road impact fees touch on differences between travel needs, land use patterns, and transit potential in the county’s urban and rural/suburban communities (Clemente, 2021; Hernandez, 2021; Salour, 2021).

For many modern Americans, the passenger train is but a distant memory, an artifact of the past. In the postwar United States, the status of passenger rail service deteriorated significantly. There were many reasons for this decline, but large subsidies enabled by federal highway and air transportation policies greatly favored alternate forms of traffic at the passenger train's expense. Realizing that rail service in this country was either on the verge of extinction or nationalization, Congress and President Richard M. Nixon sought to preserve a modest network of passenger trains through the Rail Passenger Service Act of 1970, which created the publicly subsidized corporation Amtrak. This study looks at changing transportation policies following World War II and ultimately identifies the role that politics played in the decline of the passenger train and the creation of Amtrak.

Ports and container terminals have very complex and dynamic operations. Effective and efficient berth schedules are essential for profitable and sustainable operations. This research studies berth scheduling under uncertainties in arrival and handling times. Port operators usually face challenges in the development of berth schedules. This thesis presents a model formulation of discrete berth space that accounts for uncertainty in arrival and handling times. The problem is reformulated as a biobjective bi-level optimization berth scheduling problem. A solution approach is presented using evolutionary algorithms and heuristics. The objective of the formulation is to provide a robust berth schedule by minimizing the average and the range of the total service times for all vessels served at the terminal. Simulation is utilized to evaluate the proposed berth scheduling policy and compare it to two first-come-first-served policies. Results showed that the proposed berth schedules outperform under high congestion.

the decades after World War II the United States became the most prosperous nation in the world. Yet, that prosperity and growth had a negative impact on the environmental quality of the nation. By the mid 1960s there was a rise in concern over environmental issues in the American public. Consequently, President Richard M. Nixon in his determination to give the American people what they sought decided to enact policies to bring the environmental crisis to an end. Among the environmental policies of the Nixon Administration was the Clean Air Act of 1970, a highly controversial piece of legislation that placed tough regulations on the automobile industry. Due to the significant role of the auto industry in the American economy, and Nixon's concerns over reelection, there were two major shifts in business/government relations during this era. The first one was characterized by determination to protect the environment with little attention to complaints from the industry. The second one was about protecting the profitability of the industry while giving little attention to environmental problems.

The demand on transportation infrastructure is dramatically increasing due to population growth causing the transportation systems to be pushed to their limits. With the projected population growth, not only for the U.S. but especially for the higher education field, university campuses are of great importance for transportation engineers. Urban univeristy campuses are considered major trip generators and with the population forecast many challenges are bound to arise. The implementation of an improved transit system provides a lower-cost solution to the continuously increasing congestion problems in university campus road networks and surrounding areas. This paper presents a methodology focused on the development of a hybrid system concentrated in three main aspects of transit functionality : access to bus stop location, reasonable travel time and low cost. Two methods for bus stop locations assessment are presented for two levels of analysis : microscopic and mesoscopic. The resulting travel time from the improved bus stop locations is analyzed and compared to the initial conditions by using a microsimulation platform. The development of a mathematical model targets the overall system's cost minimization, including user and operator cost, while maximizing the service coverage. The results demonstrate the benefits of the bus stop assessment by the two applied methods, as well as, the benefits of the route and headway selection based on the mathematical model. Moreover, the results indicate that the generation of routes using travel time as the impedance factor generates the optimal possible routes to obtain the minimum system's overall cost.