Holistic rail network operation by integration of train automation and traffic management

Abstract

Nowadays, railways play an increasingly important role in our daily lives. Many experts and engineers are making their own efforts to optimise railways whether it involves increasing capacity, saving energy and reducing costs. However, the experts from different fields have their own intention, method and evaluation on optimisation. This thesis aims to analyse these differences systematically in order to build a more holistic optimisation method, with special focus on two specific areas: traffic management and train operation.</br>It has been proved that traffic management and train operation work well separately, but not collaboratively. Traffic management’s strength lies in traffic conflict prevention and resolution, but it lacks sufficient on-board computing power and real-time transmitted train data, which will reduce the accuracy of traffic plan execution. On the contrary, train operation has sufficient on-board computing power and real-time train data transmission, but it has no knowledge of other trains’ status to prevent or resolve conflicts. Therefore, the optimisation strategies of traffic management and train operation are complementary.</br>The thesis endeavours to integrate the two fields by proposing an integrated optimisation model, which highlights the importance of the bidirectional communication between traffic management and train operation. The former provides the strategy of conflict resolution for the latter, while the latter offers real-time feedback of train characteristics to the former. Moreover, the thesis introduces a decision-making structure into the integrated optimisation model by using the Analytical Hierarchy Process (AHP) method. Therefore, it can adapt to different optimisation circumstances and achieve a balance in multidimensional, at times contradicted optimisation goals. Furthermore, the thesis develops a lab-demonstrator to prove the feasibility of the integrated optimisation model.</br>In addition, the thesis contributes to the railway capacity study. It proposes a new classification of capacity definitions, which distinguishes the dynamic capacity influenced by different optimisation methods from the theoretical capacity influenced by different infrastructure conditions. This classification can reduce the impact of confusion of capacity definitions in the discussion of capacity, especially when it involves experts from different backgrounds. Moreover, the thesis proposes a new 4-quadrant capacity model, which provides a new method to evaluate the trade-off between dynamic capacity and quality in traffic planning and operations. Furthermore, the thesis proves the feasibility of the new 4-quadrant capacity model in a practical case study.</br>To sum up, the integrated optimisation model and the proposed 4-quadrant capacity model both indicate that the tendency of railway optimisation is not to maximise the capacity at the expense of quality, but to increase the capacity and improve the quality at the same time.