In the last 15 years, the use of rail infrastructure by different train operating companies (shared railway system) has been proposed as a way to improve infrastructure utilization and to increase efficiency in the railway industry. Shared use requires coordination between the infrastructure manager and multiple train operators. Such coordination requires capacity planning mechanisms that determine which trains can access the infrastructure at each time, capacity allocation, and the access charges they have to pay, capacity pricing. The objective of this thesis is to contribute to the field of shared railway systems coordination by 1) developing a framework to analyze the performance of shared railway systems under alternative capacity pricing and allocation mechanisms, and 2) using this framework to understand the implications of representative capacity pricing and allocation mechanisms in representative shared railway systems. There are strong interactions between capacity planning and infrastructure operations in the railway industry; the operations on the infrastructure determine the available capacity in the system. As a consequence, the framework developed in this thesis to evaluate the performance of shared railway systems under alternative capacity pricing and allocation consists of two models: 1) a train operator model and 2) an infrastructure manager model. The train operator model is a financial model that anticipates how train operators would respond to the capacity pricing and allocation mechanisms and determine their demand for infrastructure use. The infrastructure manager model is a network optimization model that determines the optimal train timetable (infrastructure manager's decisions) that accommodates the train operators' demands for scheduling trains, considering the topology of the system, safety constraints, and other technical aspects of the infrastructure for shared railway systems. To be able to solve the train timetabling optimization problem in meaningful instances, this thesis develops a novel approximate dynamic programming algorithm based on linear programming that extends previous algorithms proposed in the literature to effectively solve large network optimization problems. This thesis then uses the train operator model to compare the operational decisions of train operators in shared railway systems with the operational decisions of even-handed integrated railway companies. We show that train operators in shared railway system access charges reflect variable infrastructure manager's costs to operate trains on the infrastructure. We also identify two cases in which the train operators may have incentives to deviate from the integrated railway systems' operational decisions: 1) when the infrastructure manager needs to recover part of the infrastructure management fixed costs, or 2) when the railway system is congested. This motivates the choice of the two case studies of this thesis, one based on the Central Corridor in Tanzania, and the other one based on the Northeast Corridor in the US. We then show how to use the framework proposed in this thesis to analyze the trade-offs associated with the use of alternative mechanisms in these two cases. To our knowledge, this is the first effort to compare alternative mechanisms to price and allocate capacity in the same shared railway system. The results of this thesis show that there are important trade-offs associated with each mechanism and none of them is superior to the other on all dimensions. We thus recommend that system stakeholders carefully analyze the implications of alternative capacity pricing and allocation mechanisms before locking the system into one of them. This is particularly important today since several countries are currently restructuring their railway sector to allow shared use. We claim that the improved understanding of the system performance gained with the framework proposed in this thesis is important to be able to design adequate capacity pricing and allocation mechanisms that can mitigate the coordination problems of shared railway systems while maintaining the benefits of shared infrastructure in the railway industry.