Yung-Cheng Lai

Impact of Train Type Heterogeneity on Single-Track Railway Capacity

North American railroads are experiencing rapid growth in traffic demand and increasingly need to expand capacity to accommodate it. Efficient planning of new capacity requires understanding how the mixture of traffic interacts to affect capacity. Different train types can have substantially different operating characteristics, including maximum speed, power-to-ton ratio, and dispatching priority. Heterogeneity in the mix of characteristics of different train types creates greater delays than are created if traffic is homogeneous. Train dispatching simulation software was used to analyze the effect of various combinations of intermodal, unit, manifest, and passenger trains on a hypothetical, signalized, single-track line with characteristics typical of a North American railroad subdivision. Analyses included the influence on delay by various traffic and train characteristics. As has been shown by previous investigators, heterogeneity increases delay, but different types of heterogeneity had differing effects, which has implications for capacity planning. This paper attempts to provide a better understanding of the impacts of various aspects of train type heterogeneity to enable more effective planning and efficient rail operations. The results also suggest certain operating strategies that may reduce the delays caused by train type heterogeneity.

Enhanced Parametric Railway Capacity Evaluation Tool

Many railroad lines are approaching the limits of practical capacity, and estimated future demand is projected to increase 84% by 2035. Therefore, identifying a good multiyear capacity expansion plan has become a particularly timely and important objective for railroads. An enhanced parametric capacity evaluation tool has been developed to assist railroad companies in capacity expansion projects. This evaluation tool is built on the Canadian National Railway Company parametric model by incorporating enumeration, cost estimation, and impact analysis modules. Based on the subdivision characteristics, estimated future demand, and available budget, the proposed tool will automatically generate possible expansion alternatives, compute line capacity and investment costs, and evaluate their impact. For a particular subdivision, there are two outputs from this decision support tool: a plot that depicts the delay–volume relationship for each alternative and an impact and benefit table that shows the impact of the future demand on the subdivision with different upgrading alternatives. The decision support tool is highly beneficial for budget management of North American railroads.

Optimal Locations of Railroad Wayside Defect Detection Installations

Railroads have been using wayside inspection technologies for many years and recently new technologies are proliferating. Efficient deployment of these technologies is important if railroads are to derive the maximum benefit from their investment. This paper presents a network optimization model that selects cost-effective installation sites for wayside defect detection system over a railroad network. The objective is to maximize the total inspection benefits possible under any given investment budget. We develop efficient solution techniques based on Lagrangian Relaxation to solve the problem. The paper also presents a case study using empirical data to illustrate the technique. The computational results show that the model can be solved efficiently, and hence has the capability of being applied to full-scale railroad networks at either regional or national levels. There are a variety of ways that railroads can use this model to help them more efficiently invest in wayside inspection technology so as to maximize the safety and economic benefits of these technologies.

Options for Improving the Energy Efficiency of Intermodal Freight Trains

Intermodal trains are typically the fastest trains operated by North American freight railroads. Ironically, these trains tend to have the poorest aerodynamic characteristics. Because of constraints imposed by equipment design and diversity, intermodal trains incur greater aerodynamic penalties and increased fuel consumption than other trains. Improving the loading patterns of intermodal trains has the potential to improve aerodynamic characteristics and thus fuel efficiency. Train aerodynamics and resistance analyses were conducted on several alternative intermodal train-loading configurations. Matching intermodal loads with cars of an appropriate length reduces the gap length between loads and thereby improves airflow. Filling empty slots with empty containers or trailers also reduces aerodynamic resistance and improves energy efficiency, despite the additional weight penalty and consequent increase in bearing and rolling resistance. Depending on the particular train configuration, train resistance can be lowered by as much as 27% and fuel savings by 1 gal/mi per train.

Machine vision analysis of the energy efficiency of intermodal freight trains

Abstract Intermodal (IM) trains are typically the fastest freight trains operated in North America. The aerodynamic characteristics of many of these trains are often relatively poor resulting in high fuel consumption. However, considerable variation in fuel efficiency is possible depending on how the loads are placed on railcars in the train. Consequently, substantial potential fuel savings are possible if more attention is paid to the loading configuration of trains. A wayside machine vision (MV) system was developed to automatically scan passing IM trains and assess their aerodynamic efficiency. MV algorithms are used to analyse these images, detect and measure gaps between loads. In order to make use of the data, a scoring system was developed based on two attributes - the aerodynamic coefficient and slot efficiency. The aerodynamic coefficient is calculated using the Aerodynamic Subroutine of the train energy model. Slot efficiency represents the difference between the actual and ideal loading configuration given the particular set of railcars in the train. This system can provide IM terminal managers feedback on loading performance for trains and be integrated into the software support systems used for loading assignment.

A Rolling Horizon Model to Optimize Aerodynamic Efficiency of Intermodal Freight Trains with Uncertainty

Aerodynamic efficiency of intermodal freight trains can be significantly improved by minimizing the adjusted gap lengths between adjacent loads. This paper first develops a static model to optimize load placement on a sequence of intermodal trains that have scheduled departure times. This model applies when full information on all trains and loads is available. Then, we develop a dynamic model to account for the more realistic situation in which there is incomplete or uncertain information on future trains and incoming loads. This paper develops methodology to balance between (i) the advantage from optimizing multiple trains together and (ii) the risk of making suboptimal decisions due to incomplete future information. We propose a rolling horizon scheme to address this challenge, where exponentially decreasing weights are assigned to the objective functions of future trains. Numerical results based on empirical data show significant aerodynamic efficiency benefits from these optimization models.

Railway Capacity Model and Decision Support Process for Strategic Capacity Planning

The demand for railway transportation is expected to increase significantly worldwide and railway agencies are looking for better tools to allocate their capital investments in capacity planning in the best possible way. A capacity model has been developed to evaluate the network capacity of a conventional railway system with predominantly passenger trains. A capacity planning process is presented to help planners enumerate possible expansion options and to determine the optimal network investment plan for meeting future demand. Use of this capacity evaluation tool and capacity planning process will help railway agencies provide satisfactory service to their customers and pleasing returns on shareholder investments.

Development of Base Train Equivalents to Standardize Trains for Capacity Analysis

A conventional railway system usually has multiple train types with various service patterns operating on the same line. Differences in train characteristics lead to varied capacity effects on the system. “Rail line capacity” is commonly defined as the maximum number of trains that can be operated on a section of track with an expected level of service within a given time period. However, a particular unit (trains/hour or trains/ day) does not reflect the train type the unit refers to. In this study, a new concept is proposed, namely, the base train equivalent (BTE), along with a standardization process to classify different train types in accordance with the particular type defined by the user. This concept is similar to the passenger car equivalent, which converts trucks to passenger car units in classifying highway transportation. A delay-based approach is also developed to determine BTEs on the basis of results obtained from two common capacity evaluation methods: parametric capacity analysis and simulation. With the proposed method, capacity measurements from different lines or systems can be compared and evaluated, resulting in meaningful and useful attributes.

Optimizing Train Network Routing with Heterogeneous Traffic

The expected increase in long-term demand for rail traffic in North America will lead to capacity constraints. Although both infrastructure investment and operational changes can relieve congestion, careful consideration of how operational practices can affect or mitigate demand is critical for cost-effective planning for new capacity, especially when the high cost required to build and maintain infrastructure is considered. A critical aspect of capacity management is understanding the effect of heterogeneous traffic on capacity. Greater heterogeneity on a line increases interference between trains and creates more delays than would occur if all trains had similar characteristics. The present research takes into account the impact of heterogeneity and presents a new optimization framework to identify optimal train network routing. This tool will help service design managers with traffic routing and capacity utilization. The computational results show that the use of this tool can successfully reduce operational costs and provide reliable services.

Effect of train-type heterogeneity on single-track heavy haul railway line capacity

North American heavy haul railroads are experiencing growth in traffic demand and increasingly facing capacity constraints. A key factor influencing railroad operations is heterogeneity in train characteristics. Different train types can have substantially different operating characteristics including maximum speed, power-to-ton ratio and dispatching priority. This heterogeneity causes conflicts between trains that increase delays and reduce capacity. Dispatching simulation software was used to analyze the effect of various combinations of intermodal and bulk trains on a hypothetical, signalized, single-track line with characteristics typical of a North American freight railroad subdivision. This assessment studied the relationship between volume, heterogeneity and delay. Further work identified the key factors that contribute to the increased delays due to heterogeneity. The train characteristics of speed, acceleration, braking and priority were considered for their effect on the increased delays due to heterogeneity. Understanding these factors that affect delay allows for more effective network capacity planning and efficient rail operations. The results also suggest certain railway operating strategies that may reduce the delays caused by train-type heterogeneity thereby improving service reliability.