Economic Effects of Lifting the Spring Load Restriction Policy in Minnesota

Spring load restrictions (SLR) regulate the weight per axle carried by heavy trucks during the spring thaw period. This policy aims to reduce pavement damage caused by heavy vehicles and extend the useful life of roads, but it also imposes costs on the trucking industry due to detouring or increased number of truckloads. Although the policies have been implemented for many years, their resulting economic effect has been unclear. The Minnesota Local Road Research Board (LRRB) and the Minnesota Department of Transportation (Mn/DOT) sponsored a cost/benefit study of spring load restrictions in Minnesota. The study, based on the results of surveys of industry costs, a pavement performance model, and a freight demand model, concludes that the benefits of lifting the existing SLR policy outweigh the additional costs. Roadways operating at 5-tons require additional study; however, current analysis warrants repealing SLR and keeping roadways operating year-round at 9-tons. The cost of additional damage should be recovered from those who benefit from the change in policy.

National and international freight transport models: overview and ideas for further development

This paper contains a review of the literature on freight transport models, focussing on the types of models that have been developed since the nineties for forecasting, policy simulation and project evaluation at the national and international level. Models for production, attraction, distribution, modal split and assignment are discussed in the paper. Furthermore, the paper also includes a number of ideas for future development, especially for the regional and urban components within national freight transport models

Economic Effects of Lifting the Spring Load Restriction Policy in Minnesota

Spring load restrictions (SLR) regulate the weight per axle carried by heavy trucks during the spring thaw period. This policy aims to reduce pavement damage caused by heavy vehicles and extend the useful life of roads, but it also imposes costs on the trucking industry. A cost/benefit study, based on the results of surveys of industry costs, a pavement performance model, and a freight demand model, concludes that the benefits of lifting the existing SLR policy outweigh the additional costs. The cost of additional damage should be recovered from those who benefit from the change in policy

A freight origin-destination synthesis model with mode choice

This paper develops a novel procedure to conduct a Freight Origin-Destination Synthesis (FODS) that jointly estimates the trip distribution, mode choice, and the empty trips by truck and rail that provide the best match to the observed freight traffic counts. Four models are integrated: (1) a gravity model for trip distribution, (2) a binary logit model for mode choice, (3) a Noortman and Van Es’ model for truck, and (4) a Noortman and Van Es’ model for rail empty trips. The estimation process entails an iterative minimization of a nonconvex objective function, the summation of squared errors of the estimated truck and rail traffic counts with respect to the five model parameters. Of the two methods tested to address the nonconvexity, an interior point method with a set of random starting points (Multi-Start algorithm) outperformed the Ordinary Least Squared (OLS) inference technique. The potential of this methodology is examined using a hypothetical example of developing a nationwide freight demand model for Bangladesh. This research improves the existing FODS techniques that use readily available secondary data such as traffic counts and link costs, allowing transportation planners to evaluate policy outcomes without needing expensive freight data collection. This paper presents the results, model validation, limitations, and future scope for improvements

It's about time: Investing in transportation to keep Texas economically competitive - Appendices

APPENDIX A : PAVEMENT QUALITY (Zhanmin Zhang, Michael R. Murphy, Robert Harrison), 7 pages -- APPENDIX B : BRIDGE QUALITY (Jose Weissmann, Angela J. Weissmann), 6 pages -- APPENDIX C : URBAN TRAFFIC CONGESTION (Tim Lomax, David Schrank), 32 pages -- APPENDIX D: RURAL CORRIDORS (Tim Lomax, David Schrank), 6 pages -- APPENDIX E: ADDITIONAL REVENUE SOURCE OPTIONS FOR PAVEMENT AND BRIDGE MAINTENANCE (Mike Murphy, Seokho Chi, Randy Machemehl, Khali Persad, Robert Harrison, Zhanmin Zhang), 81 pages -- APPENDIX F: FUNDING TRANSPORTATION IMPROVEMENTS (David Ellis, Brianne Glover, Nick Norboge, Wally Crittenden), 19 pages -- APPENDIX G: ESTIMATING VEHICLE OPERATING COSTS AND PAVEMENT DETERIORATION (by Robert Harrison), 4 page

Urban Freight Transport Demand Modelling: a State of the Art

The paper provides a review of freight transport demand models for applications in urban and metropolitan areas. The perspective adopted is the short-term one of public decision-makers involved in transport planning and traffic management. The paper recalls the general methodology to be used for assessing the city logistics scenario and the features of models in relation to the planning horizons: strategic, tactical and operative. The focus is on the transport demand models able to support the assessment of short-term policies/measures. Several models and methods have been proposed. They usually refer to the multi-stage modelling approach and can be classified in terms of reference unit: truck/vehicle, commodity/quantity, delivery and mixed. The paper offers an analysis of pros and cons of each above classes of models. The research prospects are also identified

Simulation and optimization of a multi-agent system on physical internet enabled interconnected urban logistics.

An urban logistics system is composed of multiple agents, e.g., shippers, carriers, and distribution centers, etc., and multi-modal networks. The structure of Physical Internet (PI) transportation network is different from current logistics practices, and simulation can effectively model a series of PI-approach scenarios. In addition to the baseline model, three more scenarios are enacted based on different characteristics: shared trucks, shared hubs, and shared flows with other less-than-truckload shipments passing through the urban area. Five performance measures, i.e., truck distance per container, mean truck time per container, lead time, CO2 emissions, and transport mean fill rate, are included in the proposed procedures using real data in an urban logistics case. The results show that PI enables a significant improvement of urban transportation efficiency and sustainability. Specifically, truck time per container reduces 26 percent from that of the Private Direct scenario. A 42 percent reduction of CO2 emissions is made from the current logistics practice. The fill rate of truckload is increased by almost 33 percent, whereas the relevant longer distance per container and the lead time has been increased by an acceptable range. Next, the dissertation applies an auction mechanism in the PI network. Within the auction-based transportation planning approach, a model is developed to match the requests and the transport services in transport marketplaces and maximize the carriers’ revenue. In such transportation planning under the protocol of PI, it is a critical system design problem for decision makers to understand how various parameters through interactions affect this multi-agent system. This study provides a comprehensive three-layer structure model, i.e. agent-based simulation, auction mechanism, and optimization via simulation. In term of simulation, a multi-agent model simulates a complex PI transportation network in the context of sharing economy. Then, an auction mechanism structure is developed to demonstrate a transport selection scheme. With regard of an optimization via simulation approach and sensitivity analysis, it has been provided with insights on effects of combination of decision variables (i.e. truck number and truck capacity) and parameters settings, where results can be drawn by using a case study in an urban freight transportation network. In the end, conclusions and discussions of the studies have been summarized. Additionally, some relevant areas are required for further elaborate research, e.g., operational research on airport gate assignment problems and the simulation modelling of air cargo transportation networks. Due to the complexity of integration with models, I relegate those for future independent research

A Quantitative Framework for Assessing Vulnerability and Redundancy of Freight Transportation Networks

Freight transportation networks are an important component of everyday life in modern society. Disruption to these networks can make peoples’ daily lives extremely difficult as well as seriously cripple economic productivity. This dissertation develops a quantitative framework for assessing vulnerability and redundancy of freight transportation networks. The framework consists of three major contributions: (1) a two- stage approach for estimating a statewide truck origin-destination (O-D) trip table, (2) a decision support tool for assessing vulnerability of freight transportation networks, and (3) a quantitative approach for measuring redundancy of freight transportation networks.The dissertation first proposes a two-stage approach to estimate a statewide truck O-D trip table. The proposed approach is supported by two sequential stages: the first stage estimates a commodity-based truck O-D trip table using the commodity flows derived from the Freight Analysis Framework (FAF) database, and the second stage uses the path flow estimator (PFE) concept to refine the truck trip table obtained from the first stage using the truck counts from the statewide truck count program. The model allows great flexibility of incorporating data at different spatial levels for estimating the truck O- D trip table. The results from the second stage provide us a better understanding of truck flows on the statewide truck routes and corridors, and allow us to better manage the anticipated impacts caused by network disruptions.A decision support tool is developed to facilitate the decision making system through the application of its database management capabilities, graphical user interface, GIS-based visualization, and transportation network vulnerability analysis. The vulnerability assessment focuses on evaluating the statewide truck-freight bottlenecks/chokepoints. This dissertation proposes two quantitative measures: O-D connectivity (or detour route) in terms of distance and freight flow pattern change in terms of vehicle miles traveled (VMT). The case study adopts a “what-if” analysis approach by generating the disruption scenarios of the structurally deficient bridges in Utah due to earthquakes. In addition, the potential impacts of disruptions to multiple bridges in both rural and urban areas are evaluated and compared to the single bridge failure scenarios.This dissertation also proposes an approach to measure the redundancy of freight transportation networks based on two main dimensions: route diversity and network spare capacity. The route diversity dimension is used to evaluate the existence of multiple efficient routes available for users or the degree of connections between a specific O-D pair. The network spare capacity dimension is used to quantify the network- wide spare capacity with an explicit consideration of congestion effect. These two dimensions can complement each other by providing a two-dimensional characterization of freight transportation network redundancy. Case studies of the Utah statewide transportation network and coal multimodal network are conducted to demonstrate the features of the vulnerability and redundancy measures and the applicability of the quantitative assessment methodology

Planning of Truck Platoons: a Literature Review and Directions for Future Research

A truck platoon is a set of virtually linked trucks that drive closely behind one another using automated driving technology. Benefits of truck platooning include cost savings, reduced emissions, and more efficient utilization of road capacity. To fully reap these benefits in the initial phases requires careful planning of platoons based on trucks’ itineraries and time schedules. This paper provides a framework to classify various new transportation planning problems that arise in truck platooning, surveys relevant operations research models for these problems in the literature and identifies directions for future research