Lazar N Spasovic

Scheduling material handling vehicles in a container terminal

Increasing global trade has created the need for efficient container ports. The goal of the port is to move containers as quickly as possible and at the least possible cost. Goods that are delayed at the port are inevitably tardy when delivered to the customer, and thus sanctioned by late charges. Two key activities in the port are (i) unloading of containers from truck and then storage in the export area, and (ii) removal of containers from import storage and then loading onto the trucks. Since containers are large and heavy, specialized material handling vehicles are required for transporting them within the terminal. The focus of this paper is on port terminals where straddle carriers are primarily used to move containers. Container terminals typically have well developed computer and communication networks. Through these networks a terminal scheduler will control and schedule the movement of the straddle carrier fleet in real time. The objective of the terminal scheduler is to minimize the empty travel of straddle carriers, while at the same time minimizing any delays in servicing customers. This paper presents a straddle scheduling procedure that can be used by a terminal scheduler to control the movement of straddle carriers. At its core, the procedure is driven by an assignment algorithm that dynamically matches straddle carriers and trucks, as each becomes available. The procedures were developed and tested in collaboration with the largest container terminal operator in the Port of New York and New Jersey. Using a simulation model of the real system, the superiority of the proposed procedure over two alternative scheduling strategies is illustrated.

OPTIMIZATION OF BUS ROUTE PLANNING IN URBAN COMMUTER NETWORKS

Bus routing is one of the most important elements of public transit system planning. This article presents a model of optimizing service headway and a bus route serving an area with a commuter (many-to-one) travel pattern. The bus route is optimized by minimizing the total system cost, including operator and user costs, while considering diagonal links in the study network. A method is developed for transforming this network into a pure grid, which enables construction of pure grid network models applicable to irregular grid networks. A case is presented to demonstrate the application of the model. Results show that the optimal bus route is sensitive to demand distribution over the service area. The developed model is particularly useful for planning a new bus service and evaluating an existing one in many cities embedded with general grid networks.

EVALUATION OF FEEDER BUS SYSTEMS WITH PROBABILISTIC TIME - VARYING DEMANDS AND NONADDITIVE TIME COSTS

Optimal fixed-route conventional bus (CBS) and flexible-route subscription bus (SBS) systems are compared. The average cost, including operator and user costs, is defined as the objective function to be minimized. The decision variables are route spacing and vehicle size in CBS, but service area and vehicle size in SBS. The systems serve probabilistic demand that varies over a 10-h operating period with high demand in the morning and afternoon peak hours. Passengers are assumed to have nonadditive value of time. Average cost per trip is calculated for a numerical example designed to compare the suitability of a particular service under various demand conditions. For this particular example, the CBS provides the lower-cost service. However, the operator can further reduce the cost of daily operation by providing the CBS service in periods of high demand and operating the SBS during off-peak periods. In general, the threshold value of demand at which one system is more cost-effective than another is readily calculated. A sensitivity analysis is conducted to show the effect of varying model parameters on the objective functions and the decision variables.

Optimizing Distance-Based Fares and Headway of an Intercity Transportation System with Elastic Demand and Trip Length Differentiation

An efficient fare structure combined with good service quality can stimulate demand and increase revenue. This paper presents an optimization approach for an intercity transportation system where demand is sensitive to fare and wait time and the fare sensitivity further varies with trip length. The approach jointly optimizes service headway and distance-based fare structure to maximize total profit, subject to service capacity and fleet size constraints. The optimal fares are also differentiated on the basis of trip length. An efficient solution method is developed and applied to solve the profit maximization problem. The model is applied to a case study of the Taiwan High-Speed Rail System. Numerical results, including optimal solutions and sensitivity analyses, are presented. Insights that may lead to managerial decisions are discussed.

TOLL-DESIGN PROBLEM WITH STOCHASTIC ROUTE CHOICE

Congestion pricing has been regarded as an effective method of reducing network-wide travel cost. Previous work on the toll-design problem focused on the deterministic case, that is, it is assumed that travelers have perfect information on the cost of traveling on every route of the network and they always choose the one with the least cost. Limited literature is available on the stochastic case and most of it is focused on marginal social cost pricing with the underlying assumption that all links can be tolled. In this study, a toll-design problem based on stochastic route-choice behavior for multiple user groups is presented under a more realistic context—only a subset of links can be tolled. The methodology is tested with real-world network data. The performance of various algorithms is also discussed.

Commodity-Specific Disaggregation of 2002 Freight Analysis Framework Data to County Level in New Jersey

The second generation of the Freight Analysis Framework, known as FAF2, is a continuation of the original Freight Analysis Framework developed by the U.S. Department of Transportation, Federal Highway Administration. FAF2 provides trip interchanges for commodity flows between 114 domestic zones, 17 additional international gateways at which imports enter and exports depart the United States, and seven international regions. This paper presents methods for disaggregating the FAF2 data to the county level by developing different disaggregation factors for different commodity types. These new methods are also compared with other disaggregation methods. The objective is to enable state and local governmental agencies to utilize FAF2 commodity origin–destination data for a quick desktop analysis and to devise further strategies in collecting and acquiring local commodity data. The focus area of this study is the state of New Jersey. The study developed and applied different methods to disaggregate FAF2 commodity data down to the New Jersey county level. The results of the disaggregation were then compared with Global Insights Transearch Database and other disaggregation methods previously developed and presented as part of this study. Findings indicate that no one disaggregation method produces the best results for trip productions and attractions. Disaggregating each commodity using commodity-specific industry employment data yielded the best results in matching the Transearch database for flow origins. However, simple non-commodity-specific factors, such as truck vehicle miles traveled, total employment, or adjusted population data, generally yielded better results in disaggregating flow attractions.

AN IMPLEMENTATION OF THE MODE-SPLIT TRAFFIC-ASSIGNMENT METHOD

This paper presents the exact formulation and solution of an integrated mode-choice traffic-assignment model. The model incorporates theoretically sound behavioral principles governing mode and route selection. The paper also demonstrates how to implement the model within powerful mathematical programming software and use it to analyze an intermodal transportation network. Results of the analysis show that the model is an excellent educational tool in aiding the understanding of traveler behavioral principles. As a practical tool, the model can be used to provide insights in the analysis of intermodal commuter corridors.

Artificial Neural Network Model for Estimating Temporal and Spatial Freeway Work Zone Delay Using Probe-Vehicle Data

Highway lane closures due to road reconstruction and the resulting work zones have been a major source of nonrecurring congestion on freeways. It is extremely important to calculate the safety and cost impacts of work zones: the use of new technologies that track drivers and vehicles make that possible. A multilayer feed-forward artificial neural network (ANN) model is developed in this paper to estimate work zone delay by using the probe-vehicle data. The probe data include the travel speeds under normal and work zone conditions. Unlike previous models, the proposed model estimates temporal and spatial delays, which are applied to a real world case study in New Jersey. The work zone data (i.e., starting time, duration, length, and number of closed lanes) were collected on New Jersey freeways in 2014 together with actual probe-vehicle speeds. A comparative analysis was conducted; the results indicate that the ANN model outperforms the traditional deterministic queuing model in terms of the accuracy in estimating travel delays. The ANN model can be used to calculate contractor penalty in terms of cost overruns as well as incentivize a reward schedule in case of early work competition. The model can assist work zone planners in designing optimal start and end time of work zone as function of time of day. In assessing the performance of work zones, the model can assist transportation engineers to better develop and evaluate traffic mitigation and management plans.

Developing a Market-Sensitive Intelligent Transportation Systems Educational Program

Results of research undertaken to evaluate the educational needs of the emerging field of Intelligent Transportation Systems (ITSs) are presented, and whether course offerings in academic programs meet these needs is ascertained. A survey was conducted to determine needs for ITS education among public- and private-sector entities and to assess the perception of the academic sector on the type and level of ITS education to be offered. The results indicate that academic programs are aware of the educational needs of the private and public sectors in ITS and have been reacting to those needs. A traditional civil engineering curriculum is inadequate to educate engineers in ITS, thus the ITS educational program must be inter-(or cross-) disciplinary. Focus should be on the areas that are not traditionally part of civil engineering education such as communications, traffic surveillance, systems analysis, and social and institutional issues. The results are intended primarily to provide a guideline for universities to develop the content of an ITS program by identifying the type of program structure as well as the topics to be covered in the courses. A case study is presented of how such a program was implemented at the graduate level at the New Jersey Institute of Technology.

Modeling and optimizing urban bus transit considering headway variation for cost and service reliability analysis

ABSTRACT Due to the stochastic nature of traffic conditions and demand fluctuations, it is a challenging task for operators to maintain reliable services, and passengers often suffer from longer travel times. A failure to consider this issue while planning bus services may lead to undesirable results, such as higher costs and a deterioration in level of service. Considering headway variation at route stops, this paper develops a mathematical model to optimize bus stops and dispatching headways that minimize total cost, consisting of both user and operator costs. A Genetic Algorithm is applied to search for a cost-effective solution in a real-world case study of a bus transit system, which improves service reliability in terms of a reduced coefficient of variation of headway.