Leveraging Connected Highway Vehicle Platooning Technology to Improve the Efficiency and Effectiveness of Train Fleeting Under Moving Blocks

Future advanced Positive Train Control systems may allow North American railroads to introduce moving blocks with shorter train headways. This research examines how closely following trains respond to different throttle and brake inputs. Using insights from connected automobile and truck platooning technology, six different following train control algorithms were developed, analyzed for stability, and evaluated with simulated fleets of freight trains. While moving blocks require additional train spacing beyond minimum safe braking distance to account for train control actions, certain following train algorithms can help minimize this distance and balance fuel efficiency and train headway by changing control parameters

Dispatching logic, corridor simulation, and train following algorithms to quantify the benefits of virtual and moving block control systems on North American freight railroad mainlines

This thesis presents research evaluating the effectiveness of virtual and moving block railway control systems on North American freight railroad mainline corridors. Virtual and moving block control systems are one potential strategy for improving mainline operations such that corridors currently operating at capacity can maintain performance under a projected 24% increase in freight traffic volume by 2045. Properly characterizing the potential benefits and technical challenges associated with developing and implementing virtual and moving block systems on freight railroads is critical for railroad industry practitioners to make optimal decisions regarding investments in these advanced control systems. To address this research need, a novel deadlock-free train dispatching algorithm was first developed to support a new corridor simulation and evaluation tool. To provide accurate train traversal time estimates to this dispatching algorithm, a custom train performance calculator was also developed. The newly developed dispatching algorithm was designed to run over longer corridors and require substantially less computation time than existing industry automated dispatching tools, while retaining a similar quality of dispatch solution. A detailed train corridor simulation tool was subsequently developed to utilize this dispatching algorithm and train performance calculator. Compared to existing commercial tools, the developed corridor simulation tool has the novel ability to simulate moving blocks and various densities of virtual blocks overextended mainline corridors. Leveraging this novel capability, the simulation tool compared the performance of fixed, virtual, and moving block systems on two US Class I railroad mainline corridors, each over 2,000 miles in length. Future traffic volumes were tested under each control system to explicitly quantify their mainline performance and capacity benefit. Virtual and moving block systems have the ability to increase mainline capacity and preserve current average train speeds as traffic grows on each corridor. Much of the benefit of a moving block system can also be provided by a virtual block system that subdivides each existing fixed signal block into a small number of virtual blocks. To support the temporal and geographic scope of the corridor-level simulation, the custom train performance calculator necessarily made simplifications regarding train control and interactions between closely following trains. Due to discrete throttle notches, slow brake applications, and complex in-train forces, train following behavior is intricate and requires specific freight train control algorithms designed for moving block operation. To address this need, a new and more detailed multi-train performance model was developed to improve locomotive tractive effort and train brake simulation. A test scenario found that a control algorithm that could only choose full throttle or full dynamic braking failed to adequately control the simulated train fleet. To develop a successful train following controller for freight train operation in moving blocks, inspiration was taken from the highway vehicle following domain. A proportional derivative controller successfully controlled the train fleet but ran trains at large headways. A modified version of this controller was developed in addition to a novel controller derived from first principles. Each of these controllers exhibited better performance, achieving very near the theoretical maximum performance of a moving block system.U of I OnlyAuthor requested U of Illinois access only (OA after 2yrs) in Vireo ETD syste

Leveraging connected vehicle platooning technology to improve the efficiency and effectiveness of train fleeting under moving blocks

This paper leverages emerging highway vehicle platooning technology to improve the efficiency and effectiveness of fleeting trains at minimum headways under moving blocks. The research aims to better understand how closely following trains respond to different throttle and brake control algorithms, and, using insights gained from automobile and truck platooning technology, develop improved train control algorithms balancing fuel efficiency and train headway. To do so, a detailed multi-train performance simulator is developed to evaluate following train control algorithms and then adapt highway vehicle platooning control methods to the heavy haul freight rail domain. Five following train control algorithms under two different communication topologies are formulated to more intelligently consider information on the status of the train ahead when specifying throttle or brake settings for each following train. With string stability, following trains attenuate the actions of preceding trains and each successive train requires less aggressive acceleration and braking rates to maintain headways. The simulation results suggest that certain families of control laws are better than others at managing train separation and fuel consumption within train fleets. The results of this research will allow industry practitioners to develop improved locomotive driver advisory and semi-autonomous adaptive train cruise control systems for the operation of fleets of trains under moving blocks, and railroad operators to make more informed decisions regarding the potential fuel efficiency and capacity benefits of these systems