The Impacts of Increased Adverse Weather Events on Freight Movement

Freight transportation is a major economic backbone of the United States and is vital to sustaining the nation’s economic growth. Ports, as one of the primary components of freight transportation and important means of integrating into the global economic system, have experienced significant growth and increased capacity during the past two decades. The study addresses an important national freight mobility goal to enhance the resilience of the port transportation operations in the event of extreme weather events. This study develops an adaptable resilience assessment framework that evaluates the impact of a disruptive event on transportation operations. The framework identifies dynamic performance levels over an extended period of an event including five distinct phases of responses- staging, reduction, peak, restoration, and overloading. This study applies the framework to the port complex in Houston, Texas, during a major hurricane event, Harvey, and two holiday events in 2017. The framework evaluates proactive and reactive responses of port truck activities during the disruptions and provides a comprehensive assessment of resilience and adaptability in port truck operations. Evaluating response systems and resilience of port truck activities during severe weather events such as Hurricane Harvey represents the first step for designing plans that support a fast system recovery that minimizes the economic, social, and human impacts

Mixing quantitative and qualitative methods for sustainable transportation in Smart Cities

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Criticality of infrastructure networks under consideration of resilience-based maintenance strategies using the example of inland waterways

Transportation infrastructures as backbone of modern, globalized, and networked societies ensure flows of people and goods and thus sustain social and economic prosperity. Concurrently, more and more infrastructure construction assets are facing the problem of systematic obsolescence due to deficient structural conditions, maintenance backlogs, and a lack of or misallocation of resources for the construction and maintenance of infrastructure buildings. This problem construct necessitates a resilience-based maintenance strategy for the asset portfolio. In particular, inland navigation as a mode of transport features large transport volumes and few redundancies. Combined with its increasing importance due to its comparatively high environmental friendliness, a predestined, yet in the literature underrepresented research subject results. This dissertation aims to investigate essential factors of infrastructure management and thereby identify the potential for improvement in the complex construct of maintenance management and related areas. The emphasis is on enhancing the resilience of inland waterways as a complex System-of-Systems with all its interdependencies. Thus, a holistic risk and resilience assessment is essential and is underlined with the aspects infrastructure availability and business decisions (Study A, B, C and D) and stakeholder communication and risk analysis (Study E, F, G) which are addressed by seven studies published as companion articles. Study A deals with assessing the reliability of transport infrastructure networks as part of supply chains, highlighting the importance of available and thus maintained infrastructure assets for functioning supply chains. Study B aims to identify critical warning times before closures of transport infrastructure networks and therefore suggests a mixed-methods approach, making it possible to derive and evaluate critical thresholds. Study C examines the corresponding company decisions, i.e., decisions as reaction towards neglected maintenance of public transport infrastructure, which comprises risk coping strategies, examined by empirical investigations. Study D extends this problem observation by showing that companies could see incentives for outsourcing if they face a lack of access to available transport infrastructure. Hence, the study analyzes facility relocation problems in dependence on infrastructure availability. Study E heads toward stakeholder communication and risk analysis and examines the processes across stakeholders, using an approach of collaborative serious gaming, which simultaneously enhances situation awareness and communication among stakeholders. Study F provides the implementation of a systemic approach and its visualization as a GIS-based risk dashboard, shedding light on interdependencies among critical infrastructures and cascading effects. Study G closes with an examination of the evaluation of the potential of infrastructure funds. For this purpose, the study conducts an online survey to determine investors’ willingness to pay for various fund mechanisms, integrating the option of private coverage. Despite the geographic focus of the case studies on Germany, valuable insights can be gained for infrastructure management that can also apply to other countries. In addition to the case study findings, general recommendations for infrastructure owners are derived. As a result, it can be stated that it is essential that maintenance strategies have to be more resilience-based than traditional strategies, which are mainly based on fixed time intervals for maintenance. Moreover, the application of both serious gaming and GIS visualization can help to enhance situation awareness and thus the resilience of infrastructure systems. An essential finding for which this dissertation provides methodological approaches is that considering the local area’s attractiveness for business locations should receive more attention regarding investment decisions. Thereby a focus should be set on the realistic threat of relocations as response to deteriorating infrastructure conditions. Eventually, public debates should strengthen the knowledge about infrastructure and its funding, while deficits in alongside mechanisms in infrastructure funding must be encountered. Consequently, this dissertation provides insights into the potential of infrastructure management. Mainly, it offers the potential to improve the resilience of the waterway transportation system and address stakeholders accordingly

Quantifying and Visualizing City Truck Route Network Efficiency Using a Virtual Testbed: Models for an Urban Freight and Parcel Delivery Virtual Testbed in NYC

69A3551747119This project explored routing app designs that can be of use to NYC DOT in informing truck drivers in NYC. This involved developing a prototype app and engaging in a hackathon in Fall 2022 to refine the visualization of the routing data. Second, we leveraged public data to construct a synthetic population of trucks that can be incorporated into a multiagent simulation that allows for dynamic passenger and commercial vehicle interactions. The synthetic truck population, which includes schedules of trip chains for each individual truck, will be incorporated into MATSim-NYC (He et al., 2021). Third, we proposed a new model for predicting zonal residential parcel delivery volumes and VMT that is applicable to large-scale scenarios and validate such a model using data from New York City (NYC)

Contributions to sustainable urban transport : decision support for alternative mobility and logistics concepts

Increasing transport activities in cities are a substantial driver for congestion and pollution, influencing urban populations’ health and quality of life. These effects are consequences of ongoing urbanization in combination with rising individual demand for mobility, goods, and services. With the goal of increased environmental sustainability in urban areas, city authorities and politics aim for reduced traffic and minimized transport emissions. To support more efficient and sustainable urban transport, this cumulative dissertation focuses on alternative transport concepts. For this purpose, scientific methods and models of the interdisciplinary information systems domain combined with elements of operations research, transportation, and logistics are developed and investigated in multiple research contributions. Different transport concepts are examined in terms of optimization and acceptance to provide decision support for relevant stakeholders. In more detail, the overarching topic of urban transport in this dissertation is divided into the complexes urban mobility (part A) in terms of passenger transport and urban logistics (part B) with a focus on the delivery of goods and services. Within part A, approaches to carsharing optimization are presented at various planning levels. Furthermore, the user acceptance of ridepooling is investigated. Part B outlines several optimization models for alternative urban parcel and e-grocery delivery concepts by proposing different network structures and transport vehicles. Conducted surveys on intentional use of urban logistics concepts give valuable hints to providers and decision makers. The introduced approaches with their corresponding results provide target-oriented support to facilitate decision making based on quantitative data. Due to the continuous growth of urban transport, the relevance of decision support in this regard, but also the understanding of the key drivers for people to use certain services will further increase in the future. By providing decision support for urban mobility as well as urban logistics concepts, this dissertation contributes to enhanced economic, social, and environmental sustainability in urban areas

Designing and Scheduling Cost-Efficient Tours by Using the Concept of Truck Platooning

Truck Platooning is a promising new technology to reduce the fuel consumption by around 15% via the exploitation of a preceding and digitally connected truck’s slipstream. However, the cost-efficient coordination of such platoons under consideration of mandatory EU driving time restrictions turns out to be a highly complex task. For this purpose, we provide a comprehensive literature review and formulate the exact EU-Truck Platooning Problem (EU-TPP) as an Integer Linear Program (ILP) which also features a hypothetical task-relieving effect for following drivers in a convoy. In order to increase the computational efficiency, we introduce an auxiliary constraint and two hierarchical planning-based matheuristic approaches: the Shortest Path Heuristic (SPH) and the Platoon Routing Heuristic (PRH). Besides a qualitative sensitivity analysis, we perform an extensive numerical study to investigate the impact of different critical influence factors on platooning, being of major political and economic interest. Our experiments with the EU-TPP suggest remarkable fuel cost savings of up to 10.83% without a 50% task relief, while its inclusion leads to additional personnel cost savings of up to even 31.86% at best with maximally 12 trucks to be coordinated in a recreated part of the European highway network. Moreover, we prove our matheuristics’ highly favorable character in terms of solution quality and processing time. Keywords: autonomous transport; Truck Platooning; driving time and rest periods; cost-efficient routing & scheduling; computational efficiency

Commodity-based Freight Activity on Inland Waterways through the Fusion of Public Datasets for Multimodal Transportation Planning

Within the U.S., the 18.6 billion tons of goods currently moved along the multimodal transportation system are expected to grow 51% by 2045. Most of those goods are transported by roadways. However, several benefits can be realized by shippers and consumers by shifting freight to more efficient modes, such as inland waterways, or adopting a multimodal scheme. To support such freight growth sustainably and efficiently, federal legislation calls for the development of plans, methods, and tools to identify and prioritize future multimodal transportation infrastructure needs. However, given the historical mode-specific approach to freight data collection, analysis, and modeling, challenges remain to adopt a fully multimodal approach that integrates underrepresented modes, such as waterways, into multimodal forecasting tools to identify and prioritize transportation infrastructure needs. Examples of such challenges are data heterogeneity, confidentiality, limitations in terms of spatial and temporal coverage, high cost associated with data collection, subjectivity in surveys responses, etc. To overcome these challenges, this work fuses data across a variety of novel transportation sources to close existing gaps in freight data needed to support multimodal long-range freight planning. In particular, the objective of this work is to develop methods to allow integration of inland waterway transportation into commodity-based freight forecasting models, by leveraging Automatic Identification System (AIS) data. The following approaches are presented in this dissertation: i) Maritime Automatic Identification System (AIS) data is mapped to a detailed inland navigable waterway network, allowing for an improved representation of waterway modes into multimodal freight travel demand models which currently suffer from unbalanced representation of waterways. Validation results show the model correctly identifies 84% stops at inland waterway ports and 83.5% of trips crossing locks. ii) AIS and truck Global Positioning System (GPS) data are fused to a multimodal network to identify the area of impact of a freight investment, providing a single methodology and data source to compare and contrast diverse transportation infrastructure investments. This method identifies parallel truck and vessel flows indicating potential for modal shift. iii) Truck GPS and maritime Lock Performance Monitoring System (LPMS) data are fused via a multi-commodity assignment model to characterize and quantify annual commodity throughput at port terminals on inland waterways, generating new data from public datasets, to support estimation of commodity-based freight fluidity performance measures. Results show that 84% of ports had less than a 20% difference between estimated and observed truck volumes. iv) AIS, LPMS, and truck GPS datasets are fused to disaggregate estimated annual commodity port throughput to vessel trips on inland waterways. Vessel trips characterized by port of origin, destination, path, timestamp, and commodity carried, are mapped to a detailed inland waterway network, allowing for a detailed commodity flow analysis, previously unavailable in the public domain. The novel, repeatable, data-driven methods and models proposed in this work are applied to the 43 freight port terminals located on the Arkansas River. These models help to evaluate network performance, identify and prioritize multimodal freight transportation infrastructure needs, and introduce a unique focus on modal shift towards inland waterway transportation

2nd Symposium on Management of Future motorway and urban Traffic Systems (MFTS 2018): Booklet of abstracts: Ispra, 11-12 June 2018

The Symposium focuses on future traffic management systems, covering the subjects of traffic control, estimation, and modelling of motorway and urban networks, with particular emphasis on the presence of advanced vehicle communication and automation technologies. As connectivity and automation are being progressively introduced in our transport and mobility systems, there is indeed a growing need to understand the implications and opportunities for an enhanced traffic management as well as to identify innovative ways and tools to optimise traffic efficiency. In particular the debate on centralised versus decentralised traffic management in the presence of connected and automated vehicles has started attracting the attention of the research community. In this context, the Symposium provides a remarkable opportunity to share novel ideas and discuss future research directions.JRC.C.4-Sustainable Transpor

Analysis of global channel costs for the pharmaceutical industry

Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2009.Includes bibliographical references (leaves 77-78).The pharmaceutical industry creates products which often have more than one supply chain channel, defined as a route through the supply chain network from sourcing to the end market. Each channel's specific cost characteristics are important to the pharmaceutical industry's ability to maintain positive profit margins while meeting high customer service requirements. Determining the optimal supply chain channel involves the analysis of fuel costs, logistics, taxes, wage differences, and many more. Additionally, variables such as time and risk significantly impact the total cost of a supply chain channel, but are extremely difficult to quantify. In this research, we identify the relevant channel costs and variables for the supply chain of a large pharmaceutical corporation. After identification, our study categorizes each cost based on level of measurability and causes of variability to develop a framework identifying the most relevant costs by four product types. We then analyze market forces that affect costs over a product's lifecycle. Finally, we develop an operational model for using the framework to compare costs across multiple supply chain channels and time horizons.by Eric C. Rimling and Wontae Thomas Seoh.M.Eng.in Logistic