Dan Seedah

Improvement and Evaluation of Cell-Transmission Model for Operational Analysis of Traffic Networks: Freeway Case Study

The cell-transmission model (CTM), developed by Daganzo in 1994, has not been fully exploited as an operations model for analysis of largescale traffic networks. Because of its macroscopic and mesoscopic features, CTM offers calibration and computational advantages over microscopic models. This paper demonstrates specific improvements to the original form of CTM to increase its accuracy and realism of traffic flow representation. These improvements include modifications to provide flexibility in selection of cell lengths, noninteger movements of vehicles between cells, and algorithmic enhancements in the merging and diverging logics. The effect of such improvements on the performance of CTM was evaluated independently and comparatively. A sample freeway network of the I-10 corridor in Baton Rouge, Louisiana, was used to evaluate and compare the performance of the improved version of CTM versus CORSIM under heavily congested traffic conditions. The results showed comparable performance of both platforms in...

Approach to Classifying Freight Data Elements Across Multiple Data Sources

Multiple freight data sources, both public and private, are available to practitioners for understanding freight demand and evaluating current and future freight transportation capacity. The challenge of working with multiple data sources is dealing with the syntactic and semantic heterogeneity in these sources. To assist practitioners in addressing this challenge, a unified perspective from which data elements from multiple sources can be examined is proposed. The role-based classification schema (RBCS) organizes and classifies data elements within their respective parent databases such that similar data elements across multiple sources can be grouped. RBCS is based on two levels of classification: a primary group that characterizes data elements according to the type of object that they describe and a secondary group that differentiates between elements that identify objects and those that describe features related to the objects. When similar data elements are ascertained, the subsequent process of resolving syntactic and semantic heterogeneity becomes much clearer, especially with hundreds of data elements. The proposed schema was validated by classifying 1,624 data elements from 28 freight data sources, and it was compared with the existing mnemonic CODMRT, which defined key attributes of freight-related shipments: commodity, origin, destination, mode, route, and time. Examples of applications in the areas of data bridging and multidatabase querying are also presented.

Economic Analysis of Cargo Cycles for Urban Mail Delivery

Freight constitutes a large portion of urban daily traffic, contributing to emissions, noise, and safety concerns. Moreover, urban freight logistics are often hindered by the last mile, characterized by significant delays and high delivery costs. Firms in dense urban areas are therefore seeking more efficient and reliable modes for their last-mile services. One mode that has been gaining widespread interest is the cargo cycle. Current research on cargo cycles is limited; however, their success in effectively delivering urban goods is gaining recognition. An examination was done of the economic feasibility of using different types of cargo cycles in varying urban contexts. A case study that assessed replacing the U.S. Postal Service vehicles with cargo cycles for last-mile mail deliveries in three population densities is presented. With the use of existing depots, the results of the case study indicate that electric cargo trikes have the lowest net present value among the modes in congested areas with high population densities such as central business districts. Moreover, having a depot positioned within the delivery area was found to play a significant role in increasing the competitiveness of trikes compared with other modes.

Ontology for Querying Heterogeneous Data Sources in Freight Transportation

AbstractNavigating through multiple heterogeneous freight data sources to find the ones that are relevant to answering a question can be a challenging task when performed manually. It is highly dependent on the individual’s knowledge of all available data sources and the information contained in each one. Multiple factors contribute to freight data heterogeneity, including differences in data element definitions, level of disaggregation, and classification systems. This paper proposes a standardized knowledge representation of freight data sources using an ontology that both computer systems and domain experts can understand. The ontology is developed from a formal representation of data elements found to exist in freight data sources. The paper also presents a querying algorithm for searching through the ontology and determining relevant freight data sources that can be used for answering user queries. The proposed ontology and querying algorithm facilitate the querying and identification of relevant fre...

Modeling Rail Operating Costs for Multimodal Corridor Planning

Cost and delivery times are key variables used by shippers to determine freight mode choice. Unfortunately, transportation planners wishing to examine truck versus rail trade-offs on major state and regional corridors use models that rarely capture the effects of cargo weight, running speeds, network capacity, or route characteristics, even though they are key inputs to any logistical analysis. Moreover, current models are incapable of fully internalizing external or social costs into their calculations, a failure that becomes more important as sustainable strategies are sought by society. Therefore, in three critical areas of transportation planning—network capacity, route features, and operating characteristics—most existing models are deficient. This study gives planners a mechanistic method to determine variable rail costs on a single corridor. When this model is combined with the latest truck operating cost mechanistic models, the cost differentials that underlie the choice of truck versus rail will be revealed. The model, C-TRIT, is part of a study sponsored by the Texas Department of Transportation to support freight movement on the extensive state network of multimodal corridors.

Finding and Exploring Use of Commodity-Specific Data Sources for Commodity Flow Modeling

Commodity flow modeling studies rely on traditional data sources, such as the Commodity Flow Survey, the Freight Analysis Framework, Transearch, surveys, the U.S. census, county business patterns, and input–output models. The strengths and shortcomings of those data sources have been evaluated in the literature; the sources can be useful for modeling, but they do not necessarily support a supply chain approach or provide the level of detail or accuracy desired for modeling a particular commodity’s supply chain and flow on a city or state roadway network. This paper expands on the work of NCFRP Report 35: Implementing the Freight Transportation Data Architecture: Data Element Dictionary by finding existing data sources unique to specific commodities that identify key supply chain locations and industry relationships and that provide more detail about commodity quantity and movement to overcome the limitations of traditional freight data sources. The goal of the investigation was to find more data sets to use in commodity flow modeling. For each commodity, this paper describes data sources found, data attributes, and how those data were used to estimate flow from origins and destinations within supply chain links. The commodity-specific approach opens doors to sources of data not normally incorporated into transportation research.

Information extraction for freight-related natural language queries

The ability to retrieve accurate information from databases without an extensive knowledge of the contents and organization of each database is extremely beneficial to the dissemination and utilization of freight data. Advances in the artificial intelligence and information sciences provide an opportunity to develop query capturing algorithms to retrieve relevant keywords from freight-related natural language queries. The challenge is correctly identifying and classifying these keywords. On their own, current natural language processing algorithms are insufficient in performing this task for freight-related queries. High performance machine learning algorithms also require an annotated corpus of named entities which currently does not exist in the freight domain. This paper proposes a hybrid named entity recognition approach which draws on the individual strengths of models to correctly identify entities. The hybrid approach resulted in a greater precision for named entity recognition of freight entities-a key requirement for accurate information retrieval from freight data sources.

Basic Tool Kit for Estimation of Intermodal Rail Cost

Federal and state transportation planners and others seeking to analyze transportation systems find few publicly available rail analysis models to estimate the operational costs and environmental impacts of rail movements. Moreover, data to populate such models and to test public policy considerations for evaluating public–private partnerships are generally difficult to obtain. This paper, a product of a study funded by Region 6 of the University Transportation Center Program, offers stakeholders the building blocks to develop an integrated rail analysis model capable of testing railway operational and capital investment changes. The paper also reviews the current state of rail modeling, examines selected rail models, and presents the findings of a preliminary intermodal rail costing model developed in the work.

Topological and Operational Improvements to a Cell-Transmission-Based Simulation Model

The cell transmission model (CTM) developed by Daganzo in 1994, represents a reliable and efficient simulation environment mostly for transportation planning applications. This research study demonstrates that specific improvements can convert CTM into an operations model for large-scale traffic networks. These improvements include modification to allow for a variable cell length and adjustments to the flow advancing algorithms for a better representation of traffic flow. Evaluation and comparison of the improved version of CTM versus CORSIM has been performed using a freeway network of I-10 corridor in Baton Rouge. In addition, a sensitivity analysis demonstrates the model’s good performance under the improvements developed in this study.