Kuilin Zhang

Dynamic Network Simulation-Assignment Platform for Multiproduct Intermodal Freight Transportation Analysis

This paper develops a dynamic freight network simulation–assignment platform for the analysis of multiproduct intermodal freight transportation systems. At the core of the platform is a model framework for the mode–path assignment problem in multimodal freight transportation networks. The framework consists of three main components: a multimodal freight network simulation component, a multimodal freight assignment component, and a multiple product intermodal shortest path procedure. The freight network simulation component incorporates a bulk queuing model to evaluate transfer delay experienced by shipments at intermodal transfer terminals, classification yards, and ports. The multimodal freight assignment component determines the network flow pattern from a mode–path alternative set calculated by the multiple product intermodal shortest path procedure, based on the link travel costs and node transfer delays from the multimodal freight network simulation component. This model can represent individual shipment mode–path choice behavior, consolidation policy, conveyance link moving, and individual shipment terminal transfer in an iterative solution framework.

Time-Dependent Origin–Destination Demand Estimation: Challenges and Methods for Large-Scale Networks with Multiple Vehicle Classes

This paper proposes a modified bi-level optimization algorithm to estimate the time-dependent origin–destination trip matrices for large-scale networks with multiple vehicle classes. Methodologies are presented to overcome the challenges caused by the scale of the problem. The upper-level problem, a bound-constrained quadratic problem, had many variables and parameters for a network with around 68,000 links, 28,000 nodes, and 3,700 zones. Techniques to reduce the number of variables and parameters are described in this study, along with an approach to reduce the time and memory requirement of the lower-level problem. Furthermore, the basic approach, which had been applied only to a single vehicle class, was extended and adapted in this study to estimate matrices for single-occupancy and high-occupancy vehicles jointly. Two solution packages, MINOS and KNITRO, were tested for the upper-level problem. The solution package KNITRO was run with an option to use an interior point–conjugate gradient algorithm, which was well suited to large-scale nonlinear problems. The modified bi-level algorithm was applied to estimate the time-dependent demand patterns for the New York City regional network.

Congestion Pricing, Heterogeneous Users, and Travel Time Reliability: Multicriterion Dynamic User Equilibrium Model and Efficient Implementation for Large-Scale Networks

With the increasing interest in road pricing strategies to alleviate congestion and improve network performance, this study develops a multi-criterion dynamic user equilibrium (MDUE) traffic assignment model that explicitly considers heterogeneous users who seek to minimize three essential decision attributes: travel time, out-of-pocket cost, and travel time reliability in the underlying path choice framework. The value of time in this study is treated as a continuous random variable distributed across the population of trip makers, and travel time reliability is estimated at a path level. Furthermore, the proposed MDUE model is capable of considering different vehicle classes, namely, low-occupancy vehicles and high-occupancy vehicles; thus, with greater realism in trip makers’ path choice behavior, the MDUE model is applicable for analyzing a variety of road pricing scenarios. To address the practical application aspects for large-scale congested networks, novel implementation techniques are proposed to overcome computational obstacles to real-world application. An application to the New York metropolitan regional network is demonstrated, and a set of numerical experiments is conducted on this network to explore the convergence behavior, solution quality, and required computational time of the MDUE algorithm.

Probit-Based Time-Dependent Stochastic User Equilibrium Traffic Assignment Model

This study presents a time-dependent stochastic user equilibrium (TDSUE) traffic assignment model within a probit-based path choice decision framework that explicitly takes into account temporal and spatial correlation (traveler interactions) in travel disutilities across a set of paths. The TDSUE problem, which aims to find time-dependent SUE path flows, is formulated as a fixed-point problem and solved by a simulation-based method of successive averages algorithm. A mesoscopic traffic simulator is employed to determine (experienced) time-dependent travel disutilities. A time-dependent shortest-path algorithm is applied to generate new paths and augment a grand path set. Two vehicle-based implementation techniques are proposed and compared in order to show their impact on solution quality and computational efficiency. One uses the classical Monte Carlo simulation approach to explicitly compute path choice probabilities, and the other determines probabilities by sampling vehicles’ path travel costs from an assumed perception error distribution (also using a Monte Carlo simulation process). Moreover, two types of variance-covariance error structures are discussed: one considers temporal and spatial path choice correlation (due to path overlapping) in terms of aggregated path travel times, and the other uses experienced (or empirical) path travel times from a sample of individual vehicle trajectories. A set of numerical experiments are conducted to investigate the convergence pattern of the solution algorithms and to examine the impact of temporal and spatial correlation on path choice behavior.

Train Slot Cooperation in Multicarrier, International Rail-Based Intermodal Freight Transport

Collaborative decision-making (CDM) strategies are proposed for the collaborative operation of international rail-based intermodal freight services by multiple carriers. The benefits of the proposed techniques are assessed using a carrier collaboration simulation—assignment framework on a real-world European intermodal network spanning 11 countries from Scandinavia to Greece through Bulgaria, Czech Republic, Hungary, Poland, Romania, and Slovakia. This is termed the REORIENT corridor. Three CDM strategies are presented in this work: (a) train slot cooperation, (b) train space leasing, and (c) train slot swapping. Results of numerical experiments indicate that these strategies are expected to result in significant improvements in terms of shipments that are attracted to the proposed services. The best-performing CDM strategy, train slot swapping, resulted in a more than 40% increase in terms of ton-kilometers attracted to proposed services. Such CDM strategies result in a win–win situation for all parties. In addition to attracting more demand, cost savings in terms of rolling stock and labor and reduced shipment delays can be achieved. The potential of such strategies for a real-world application is discussed.

Application and Validation of Dynamic Freight Simulation—Assignment Model to Large-Scale Intermodal Rail Network: Pan-European Case

A dynamic intermodal multiproduct freight network simulation–assignment model is presented with application to a large-scale inter-modal rail network. Methodology pertaining to the simulation–assignment framework and representation and implementation considerations in dealing with large networks are discussed. The model is applied to a pan-European rail network spanning 11 countries from Scandinavia to Greece. Shipper decisions are disaggregated to an individual shipment level using a dynamic microassignment methodology in which a joint mode, path, service, and carrier choice is made. A mode choice function for this joint choice is calibrated, and issues relating to heterogeneity of freight characteristics are discussed. The model is validated by analyzing convergence patterns and measures of performance, namely, mode splits, compared with other studies. Two examples demonstrate the role of the model as a policy and decision support tool. The impact of expedited operations at international borders and infrastructure improvements on rail services is quantified.

Market Potential for International Rail-Based Intermodal Services in Europe: From Sea to Shining Sea

This paper examines the market potential for international rail-based intermodal services along the REORIENT Corridor, which spans 11 countries from the Baltic (Scandinavia) to the Mediterranean (Greece) through the accession countries of the European Union. The main approach followed in this assessment is to conduct scenario analyses using a state-of-the-art intermodal freight network modeling capability, which allows the evaluation of various service supply strategies under varying operational and policy scenarios. New service design options, developed through a combination of market-based research and expert opinion, are evaluated in regard to the potential addressable market demand and the likelihood of successfully competing for that demand. The analyses provide realistic assessments of the potential competitiveness of rail in attracting freight demand resulting from (a) operational considerations that pertain to the proposed services and (b) implementation of interoperability directives and barrier-removing or barrier-reducing improvements in physical, operational, or managerial aspects and business practices of the rail system that are aimed toward achieving European Commission policy objectives. In addition, the analysis points to characteristics of the demand, which is most likely to shift toward rail, in regard to commodity types and geographic location. The key question the paper seeks to answer is under what operational and policy conditions can pan-European intermodal rail freight services be competitive? Results show that prerequisites for success are a combination of favorable rail policies and the intermodal operations’ high level of service.