Dynamic blocking for railyards: Part I. Homogeneous traffic

This paper and its companion present a study of railroad classification yard strategies that allow for blocks of destinations to be assigned to classification tracks in different ways, depending on the time of day, week or month. With the same number of tracks, more classifications can be handled by this method. The paper examines homogeneous traffic; that is, traffic patterns where all blocks have the same amount of traffic, where cars for all blocks depart equally frequently from the yard and where the overall traffic flow does not change with time. The results represent the beginning of a better understanding of yard operations, which should be useful for designing new yards, planning expansions of existing ones and evaluating the impact of changes (planned and unplanned) on traffic patterns. The paper concentrates on two sorting strategies: sorting by train (perhaps the most commonly used strategy in the United States today), and triangular sorting. For both strategies, formulas are given for the minimum number of tracks, number of switches and for the total space requirements. For triangular sorting, the yard delay and total space depend on the time chosen between reswitches. These two measures of performance can be reduced if one is willing to accept a sorting effort slightly higher than minimum. The trade-off can be explored numerically. For sorting by train, yard delay and total space are not significantly affected by the sorting method; there is no such trade-off. It appears that sorting by train results in less work, delay and space requirements than triangular sorting, at least in most instances when either could be used. Triangular sorting, however, can be used when there are not enough tracks to allow sorting by train.     

Development of a differential route share model for railroad freight traffic

This paper summarizes work undertaken towards development and calibration of a model to predict the distribution of rail freight traffic among competing routes. The model is designed for use in analyzing the traffic effects of changes in the level-of-service on selected rail lines. The model predicts route shares based on the overall network configuration of each railroad participating in a given market. The model selects feasible routes, discards those routes which appear to be too circuitous or costly, and then assigns traffic to the remaining routes in accordance with several network characteristics. It is designed to be sensitive to level-of-service changes, and to simulate the response of shippers and railroads to a competitive environment. A multiple route-finding algorithm was used to find possible routes based on the number of railroads operating at the originating and terminating end of a market. Multiple routes were determined and matched with observed traffic flows from the ICC One-Percent Waybill Sample. Physical network characteristics for each route, including distance, junction frequency, and “impedance,” were calculated from the network model and were correlated with the traffic share observed on each route in the market. A two-stage model was developed to find feasible routes from the set of possible routes and to allocate traffic to feasible routes based on levels-of-service. The model was calibrated on 9,793 routes from 1,199 markets with twenty or more carloads from the 1977 One-Percent Carload Waybill Sample. Model calibration supported the hypothesis that network route characteristics did indeed influence shipper choice of route, and that a normative model could be used to assess relative attractiveness of routes under various railroad corporate ownership restructuring scenarios.     

A heuristic for the train pathing and timetabling problem

In a railroad system, train pathing is concerned with the assignment of trains to links and tracks, and train timetabling allocates time slots to trains. These important tasks were traditionally done manually, but there is an increasing move toward automated software based on mathematical models and algorithms. Most published models in the literature either focus on train timetabling only, or are too complicated to solve when facing large instances. In this paper, we present an optimization heuristic that includes both train pathing and train timetabling, and has the ability to solve real-sized instances. This heuristic allows the operation time of trains to depend on the assigned track, and also lets the minimum headway between the trains to depend on the trains’ relative status. It generates an initial solution with a simple rule, and then uses a four-step process to derive the solution iteratively. Each iteration starts by altering the order the trains travel between stations, then it assigns the services to the tracks in the stations with a binary integer program, determines the order they pass through the stations with a linear program, and uses another linear program to produce a timetable. After these four steps, the heuristic accepts or rejects the new solution according to a Threshold Accepting rule. By decomposing the original complex problem into four parts, and by attacking each part with simpler neighborhood-search processes or mathematical programs, the heuristic is able to solve realistic instances. When tested with two real-world examples, one from a 159.3 km, 29-station railroad that offers 44 daily services, and another from a 345 km, eight-station high-speed rail with 128 services, the heuristic obtained timetables that are at least as good as real schedules.     

A container terminal simulation model with animation capabilities

The objective of this paper is to introduce a computer simulation model with on-screen animation graphics, which can simulate the operations of a container terminal equipped with straddle carriers. The movements of the equipment are simulated as realistically as possible, to include time losses due to the mismatch in the sequence of equipment movements and to traffic congestion. Trucks are normally served in a specified area, but in some cases, straddle carrier drivers can call the truck to be served directly in the container storage areas. The experience of operators is incorporated in the model, in the form of a knowledge base, that is used to simulate the above process and determine the service discipline. The model was designed to evaluate different configurations (changes in yard layout, equipment number and productivity, truck arrival pattern and service discipline) of the simulated system. The proposed model was used to examine the differences between “the observed” operations strategy and the strategy dictated by the operational rules of the port of Piraeus. The results indicate that “the observed” strategy leads to shorter truck service time but increase the traffic conflicts in the terminal's internal transport networks.     

Train design and routing optimization for evaluating criticality of freight railroad infrastructures

Freight transportation by railroads is an integral part of the U.S. economy. Identifying critical rail infrastructures can help stakeholders prioritize protection initiatives or add necessary redundancy to maximize rail network resiliency. The criticality of an infrastructure element, link or yard, is based on the increased cost (delay) incurred when that element is disrupted. An event of disruption can cause heavy congestion so that the capacity at links and yards should be considered when freight is re-routed. This paper proposes an optimization model for making-up and routing of trains in a disruptive situation to minimize the system-wide total cost, including classification time at yards and travel time along links. Train design optimization seeks to determine the optimal number of trains, their routes, and associated blocks, subject to various capacity and operational constraints at rail links and yards. An iterative heuristic algorithm is proposed to attack the computational burden for real-world networks. The solution algorithm considers the impact of volume on travel time in a congested or near-congested network. The proposed heuristics provide quality solutions with high speed, demonstrated by numerical experiments for small instances. A case study is conducted for the network of a major U.S. Class-I railroad based on publicly available data. The paper provides maps showing the criticality of infrastructure in the study area from the viewpoint of strategic planning.     

Management's role in U.S. rail passenger decline, 1920–1941

Opinions vary as to whether the decline of American railroad passenger service can be attributed primarily to consumer choice or partly to structural impedances to the supply. Results are reported from testing the hypothesis that railroad management supplied service inappropriate in the new motor era: that management catered to a small, high-priced market, whereas it should have catered to a mass, low-priced market. An aggregate demand model with non-linear elasticity characteristics is estimated on railroad traffic between a sample of American cities for 1933. The model is sensitive to speed, fare and headway variables under the control of railroad management and reveals that there was a unique fare for a service of a given speed that maximized gross revenues. The observed fare for most of the 187 cases in the study was near or below the optimal fare, showing that rail managers judged their markets well, at least in the short run.     

Sequencing twin automated stacking cranes in a block at automated container terminal

In the considered automated container terminal (ACT) that is designed for Shanghai Yangsha Terminal, two automated stacking cranes (ASCs) are configured for each block and they interact with automated lifting vehicles (ALVs) at the two ends of a block individually. To increase the capacity, container yards with multiple rows of blocks perpendicular to the terminal’s shoreline are considered. To utilize the yard spaces, the twin ASCs are devised to share the same tracks installed at the two sides of a block, while interferences between the ASCs challenge the routing and sequencing operations. To isolate the control and simplify the coordination of the two ASCs, the interference between ASCs is formulated by analyzing the minimal temporal intervals between any two tasks. Three models are then established to sequence the container handling tasks under the minimization of the makespan. An exact algorithm and a genetic algorithm are designed to solve the problem. Numerical experiments show that the algorithms are competitive comparing to on-the-shelf solvers. Practical implications are investigated based on the formulations and experimental results. The managerial implications and technological aspects of applying the formulations and algorithms to practical situations to real-world ACTs are discussed.     

Evaluating the assumption of independent turning probabilities

Several urban traffic models make the convenient assumption that turning probabilities are independent, meaning that the probability of turning right (or left or going straight through) at the downstream intersection is the same for all travelers on that roadway, regardless of their origin or destination. In reality most travelers make turns according to planned routes from origins to destinations. The research reported here identifies and quantifies the deviations that result from this assumption of independent turning probabilities.An analysis of this type requires a set of reasonably realistic “original” route flows, which were obtained by a static user-equilibrium traffic assignment and an entropy maximization condition for most likely route flows. These flows are compared with those route flows resulting from the Assumption of Independent Turning Probabilities (ITP). A small subnetwork of 3 km by 5 km in Tucson, Arizona, was chosen as a case study. An overall “typical ratio” of 2.2 between original route flows and ITP route flows was obtained. Aggregating route flows to origin–destination flows led to an overall “typical ratio” of 1.7. Such deviations are particularly high for routes that go back-and-forth, reaching a ratio of more than 3 in certain time periods. Substantial deviations for origins and destinations that are on the same border of the subnetwork are also observed in the analyses. In addition, under the ITP assumption, morning rush hour traffic peaking is the same in all directions, while in the original flows some directions do not exhibit a peak in the morning rush hour period. Overall, the conclusion of the paper is that the assumption of independent turning probabilities leads to substantial deviations both at the route level and at the origin–destination level, even for such a small network of the case study. These deviations are particularly detrimental when a network is being modeled and studied for route-based measures of effectiveness such as the number and types of routes passing a point – for monitoring specified vehicles and/or managing detouring strategies.     

Storage space allocation in container terminals

Container terminals are essential intermodal interfaces in the global transportation network. Efficient container handling at terminals is important in reducing transportation costs and keeping shipping schedules. In this paper, we study the storage space allocation problem in the storage yards of terminals. This problem is related to all the resources in terminal operations, including quay cranes, yard cranes, storage space, and internal trucks. We solve the problem using a rolling-horizon approach. For each planning horizon, the problem is decomposed into two levels and each level is formulated as a mathematical programming model. At the first level, the total number of containers to be placed in each storage block in each time period of the planning horizon is set to balance two types of workloads among blocks. The second level determines the number of containers associated with each vessel that constitutes the total number of containers in each block in each period, in order to minimize the total distance to transport the containers between their storage blocks and the vessel berthing locations. Numerical runs show that with short computation time the method significantly reduces the workload imbalance in the yard, avoiding possible bottlenecks in terminal operations.     

The real-time urban traffic control system CRONOS: Algorithm and experiments

The real-time urban traffic control algorithm CRONOS has been evaluated on an intersection by comparison of two reference control strategies, a local one and a centralized one. Recurrent traffic situations, from peak hour traffic to low traffic, have been studied, and the impact on the traffic from a fluidity point of view has been investigated using various criteria. The average behavior of CRONOS has also been analyzed by crossing the traffic signal colors with traffic variables. Several of the criteria are innovative, thanks to the real-time, accurate video-based traffic data collected.The results show high benefits of CRONOS on the total delay compared to the two reference control strategies, and benefits are also obtained on the total number of stops and percentage of stops, especially in comparison with the local strategy. All traffic situations (peak to low traffic) are concerned by these results. The analysis of the average behavior of CRONOS shows a higher average number of cycles per hour, more global green duration per hour at the center of the intersection, to the detriment of the entries. Moreover, CRONOS switches more often from amber to red when no vehicles are present on the link in percentage of cycles or in number of cycles per hour; it switches more often from green to amber when vehicles are present on the link in percentage of cycles per hour.     

Railroad noise: economic valuation and policy

In developed countries noise annoyance is an important source of environmental concern. Research on noise annoyance caused by railroad traffic is relatively underdeveloped. Here, a causal chain model is presented in which railroad traffic density, noise emission, noise immission and noise annoyance are causally related. Noise level, habituation and railroad usage are determinant factors. Noise annoyance causes social and economic costs, such as property value depreciation. Policy measures, aimed at reducing social and economic costs, are incorporated in various stages of the causal model. These measures can be subdivided into noise regulation and direct prevention measures. Stricter threshold values lead to higher total costs, but may lower social costs per capita. Economic feasibility of policy measures is usually analyzed by means of a cost-benefit case study. Methods of analysis used are diverse and ad hoc. Therefore, results of different case studies are not easily compared in terms of research synthesis.     

Scheduling lane conversions for bus use on city-wide scales and in time-varying congested traffic

The paper explores what can occur when select street lanes throughout a city are periodically reserved for buses. Simulations of an idealized city were performed to that end. The city’s time-varying travel demand was studied parametrically. In all cases, queues formed throughout the city during a rush, and dissipated during the off-peak period that followed. Bus lanes were activated all at once across the city, and were eventually deactivated in like fashion. Activation and deactivation schedules varied parametrically as well. Schedules that roughly balanced the trip-time savings to bus riders against the added delays to car travelers were thus identified.Findings reveal why activating conversions near the start of a rush can degrade travel, both by car and by bus. Balance was struck by instead activating lane conversions nearer the end of the rush, when vehicle accumulation in the city was at or near its maximum. Most of the time savings to bus riders accrued after the conversions had been left in place for only 30 min. Leaving them for longer durations often brought modest additional savings to bus travelers. Yet, the added delays to cars often grew large as a result.These findings held even when buses garnered high ridership shares. This was the case when lane conversions gradually induced new bus trips among residents who formerly did not travel. It was also true when high ridership was a pre-existing feature of the city. Activating conversions a bit earlier in a rush was found to make sense only if commuters shifted from cars to buses in very large numbers. Findings also unveiled how to fine-tune activation and deactivation schedules to suit a city’s congestion level. Guidelines for scheduling conversions in real settings are furnished. So is discussion on how these schedules might be adapted to daily variations in city-wide traffic states. Roles for technology are discussed as well.     

Multi-period yard template planning in container terminals

This paper is about yard management in container ports. As a tactical level decision-making tool in a port, a yard template determines the assignment of spaces (subblocks) in a yard for arriving vessels, which visit the port periodically. The objective of yard template planning is to minimize the transportation cost of moving containers around the yard. To handle yard template planning, a mixed integer programming model is proposed that also takes into account traffic congestion in the yard. A further complication is that the cycle time of the vessels' periodicities is not uniform and varies among them, perhaps being one week, ten days, or two weeks, etc. However, this multiple cycle time of the periodicities of vessel arrival patterns, which complicates the yard template decision, is also considered in the model. Moreover, a local branching based solution method and a Particle Swarm Optimization based solution method are developed for solving the model. Numerical experiments are also conducted to validate the effectiveness of the proposed model, which can save around 24% of the transportation costs of yard trucks when compared with the commonly used First-Come-First-Served decision rule. Moreover, the proposed solution methods can not only solve the proposed model within a reasonable time, but also obtain near-optimal results with about 0.1–2% relative gap.     

Probabilistic analysis of the release of liquefied natural gas (LNG) tenders due to freight-train derailments

Liquefied natural gas (LNG) has emerged as a possible alternative fuel for freight railroads in the United States, due to the availability of cheap domestic natural gas and continued pursuit of environmental and energy sustainability. A safety concern regarding the deployment of LNG-powered trains is the risk of breaching the LNG tender car (a special type of hazardous materials car that stores fuel for adjacent locomotives) in a train accident. When a train is derailed, an LNG tender car might be derailed or damaged, causing a release and possible fire. This paper describes the first study that focuses on modeling the probability of an LNG tender car release incident due to a freight train derailment on a mainline. The model accounts for a number of factors such as FRA track class, method of operation, annual traffic density level, train length, the point of derailment, accident speed, the position(s) of the LNG tender(s) in a train, and LNG tender car design. The model can be applied to any specified route or network with LNG-fueled trains. The implementation of the model can be undertaken by the railroad industry to develop proactive risk management solutions when using LNG as an alternative railroad fuel.     

On the macroscopic stability of freeway traffic

A simple model of traffic flow is used to analyze the spatio-temporal distribution of flow and density on closed-loop homogeneous freeways with many ramps, which produce inflows and allow outflows. As we would expect, if the on-ramp demand is space-independent then this distribution tends toward uniformity in space if the freeway is either: (i) uncongested; or (ii) congested with queues on its on-ramps and enough inflow to cause the average freeway density to increase with time. In all other cases, however, including any recovery phase of a rush hour where the freeway’s average density declines, the distribution of flow and density quickly becomes uneven. This happens even under conditions of perfect symmetry, where the percentage of vehicles exiting at every off ramp is the same. The flow-density deviations from the average are shown to grow exponentially in time and propagate backwards in space with a fixed wave speed. A consequence of this type of instability is that, during recovery, gaps of uncongested traffic will quickly appear in the unevenly congested stream, reducing average flow. This extends the duration of recovery and invariably creates clockwise hysteresis loops on scatter-plots of average system flow vs. density during any rush hour that oversaturates the freeway. All these effects are quantified with formulas and verified with simulations. Some have been observed in real networks. In a more practical vein, it is also shown that the negative effects of instability diminish (i.e., freeway flows increase) if (a) some drivers choose to exit the freeway prematurely when it is too congested and/or (b) freeway access is regulated in a certain traffic-responsive way. These two findings could be used to improve the algorithms behind VMS displays for driver guidance (finding a), and on-ramp metering rates (finding b).     

Comparative evaluation of resource cycle strategies on operating and environmental impact in container terminals

This paper examines the use of single and dual cycle operations for three types of resources, namely, quay cranes, vehicles, and yard cranes to improve the operating efficiency and reduce the energy consumption in a container terminal. Various cycle strategies are proposed and their corresponding estimation models, describing the stowage distributions of outbound and inbound containers on a ship and the storage sharing level of blocks in the yard, are formulated to estimate the total number of cycles for the resources. Statistical analyses are conducted to evaluate and compare the effect of different cycle strategies on the cycle reductions. From the experiment results, it was found that collaboration between resources with the single cycle operation always outperforms that under the dual cycle operation without collaboration.     

Local online kernel ridge regression for forecasting of urban travel times

Accurate and reliable forecasting of traffic variables is one of the primary functions of Intelligent Transportation Systems. Reliable systems that are able to forecast traffic conditions accurately, multiple time steps into the future, are required for advanced traveller information systems. However, traffic forecasting is a difficult task because of the nonlinear and nonstationary properties of traffic series. Traditional linear models are incapable of modelling such properties, and typically perform poorly, particularly when conditions differ from the norm. Machine learning approaches such as artificial neural networks, nonparametric regression and kernel methods (KMs) have often been shown to outperform linear models in the literature. A bottleneck of the latter approach is that the information pertaining to all previous traffic states must be contained within the kernel, but the computational complexity of KMs usually scales cubically with the number of data points in the kernel. In this paper, a novel kernel-based machine learning (ML) algorithm is developed, namely the local online kernel ridge regression (LOKRR) model. Exploiting the observation that traffic data exhibits strong cyclic patterns characterised by rush hour traffic, LOKRR makes use of local kernels with varying parameters that are defined around each time point. This approach has 3 advantages over the standard single kernel approach: (1) It allows parameters to vary by time of day, capturing the time varying distribution of traffic data; (2) It allows smaller kernels to be defined that contain only the relevant traffic patterns, and; (3) It is online, allowing new traffic data to be incorporated as it arrives. The model is applied to the forecasting of travel times on London’s road network, and is found to outperform three benchmark models in forecasting up to 1 h ahead.     

The corridor problem: Preliminary results on the no-toll equilibrium

Consider a traffic corridor that connects a continuum of residential locations to a point central business district, and that is subject to flow congestion. The population density function along the corridor is exogenous, and except for location vehicles are identical. All vehicles travel along the corridor from home to work in the morning rush hour, and have the same work start-time but may arrive early. The two components of costs are travel time costs and schedule delay (time early) costs. Determining equilibrium and optimum traffic flow patterns for this continuous model, and possible extensions, is termed “The Corridor Problem”. Equilibria must satisfy the trip-timing condition, that at each location no vehicle can experience a lower trip price by departing at a different time. This paper investigates the no-toll equilibrium of the basic Corridor Problem.     

Inhalable railroad particles at ground level and subterranean stations - Physical and chemical properties and relation to train traffic

The paper compares PM10 concentrations in railroad environments with EU air quality standards and characterizes particle concentrations and particle properties in relation to train traffic. The results show that PM10 concentrations in ground-level railroad environments do not exceed the EU directive 24-h limit value, while on the platforms of the two subterranean stations PM10 concentrations were far above the outdoor limit value. Diurnal and weekly patterns in PM10 concentration could be identified, co-varying with train traffic intensity. The particle mass size distribution peaked at around 2-6 μm. The elemental composition of PM10 at the subterranean stations was dominated by Fe.     

Traffic flow on signalized streets

This paper considers a signalized street of uniform width and blocks of various lengths. Its signals are pretimed in an arbitrary pattern, and traffic on it behaves as per the kinematic-wave/variational theory with a triangular fundamental diagram. It is shown that the long run average flow on the street when the number of cars on the street (i.e. the street’s density) is held constant is given by the solution of a linear program (LP) with a finite number of variables and constraints. This defines a point on the street’s macroscopic fundamental diagram. For the homogeneous special case where the block lengths and signal timings are identical, all the LP constraints but one are redundant and the result has a closed form. In this case, the LP recipe matches and simplifies the so-called “method of cuts”. This establishes that the method of cuts is exact for homogeneous problems. However, in the more realistic inhomogeneous case the difference between the two methods can be arbitrarily large.The paper uses the LP method to obtain the macroscopic fundamental diagrams arising under four different traffic coordination schemes for streets with four different block length configurations. It is found that the best scheme depends on the prevailing density. Curiously, the popular scheme in which all the traffic green phases are started synchronously wins only in rare circumstances. Its performance is particularly underwhelming when the street’s blocks are long. The paper also presents density-aware numerical methods to optimize the signal offsets for 1-way and 2-way streets. For 1-way streets operated with a common cycle the method reduces to a simple graphical construction . In this case the resulting flow matches the flow that would arise if all of the street’s intersections except one with the shortest green phase had been eliminated.