Exploring the intra-platoon planning problem for heterogeneous train traffic under virtual coupling in the railway network via simulation

Study on the platoon planning of virtual coupling (VC) is indispensable for both passenger and freight railway operation in terms of capacity, scheduling, and timetabling. As an advanced technology in train operation and control systems, VC can significantly improve the performance of rail operations, with regards to capacity, flexibility and robustness. In this study, we mainly focus on the former one, i.e., to maximize the capacity gains, by employing the relative braking distance based spacing policy for heterogenous train traffic. To our knowledge, this article is the first to address the VC intra-platoon planning problem for a railway network. The main function/purpose of this study is to decide a leader train and allocate an order to the heterogeneous follower trains for the virtually coupled platoon in the off-line mode. The objective is transformed to minimize and compare the sum of minimum safe distance for platoons on the common shared route sections in the railway network from various perspectives, so as to seek the desirable orders of potential train consists within the platoons from the perspective of the whole railway network. Our contributions are mainly threefold. First, the conditions for train platooning under virtual coupling are synthesized. Second, the solution flow charts and algorithms for simulation are proposed, including general framework for simulation, classification of prioritizing the shared common route section, and flow charts and algorithms for decision of coupling order to train platoons. Finally, the proposed methodology was tested and discussed on the designed computational experiment (i.e., numerical simulations of a typical case study with two sets of test examples) via NetLogo platform. The numerical simulation results series revealed some key findings and validated the effectiveness of the proposed methodology. Results of this study can provide guidance to decision makers in timetabling and potential capacity bottleneck identification under VC. We believe that it is worth investigating and further advancing this research direction in the future.