Safety, Mobility, and Cost Benefits of Closing One Direction of the Interstate in Rural Areas During Construction Work

With specific regard to interstates in the rural area, Indiana Department of Transportation (INDOT) has expressed a need for research that sheds light on this Maintenance of Traffic (MOT) issue so the agency [INDOT and the contractor] can make informed decisions regarding the crossover sections versus the closure in one direction with detour roads. A number of studies have investigated the advantages and disadvantages of various MOT strategies; however, there is no specific study that can help INDOT traffic engineers and design engineers make decisions by comparing direct and indirect benefits of crossovers and detours (full lane closures). This research examined the advantages and disadvantages of entirely closing one direction of traffic over traditional work zone techniques (such as partial lane closure through median crossover) from the perspectives of the agency, road users, and the community. In the case of full closure, the study (a) examined the alternative MOT strategies and best practices through an extensive literature review and survey of agencies (b) investigated risk, benefit, and costs associated with selected detour routes (c) validated the identified critical factors through case studies in Indiana and at other states, and (d) implemented best practices in an expected project to evaluate the safety, mobility, and cost benefits of closing one direction. Through the literature review and four case studies, eleven KPIs for MOT strategy developments were identified. This study prioritized these KPIs through the survey questionnaire. The top five KPIs are (1) safety, (2) mobility, (3) budget constraint, (4) project duration, (5) complexity of project sites. Based on these KPIs and other findings presented in Section 4.3.3, this study has proposed a comparison tool for predetermined MOT strategies in the form of a flow-chart. This tool is followed by the scores or weights associated with each KPI. These scores are normalized—i.e., the most important KPI which is safety, has the maximum weightage 1 and rest of the KPIs are weighed relatively. INDOT has a set of editable documents which are references for making MOT decisions. This proposed flow-chart tool will “walk” the INDOT team through the use of these spreadsheets corresponding to the identified KPIs through this study. It will be at the discretion of the INDOT team as to which KPIs are relevant to the situation at hand. Therefore, the flow-chart tool is flexible to incorporate the dynamic nature of MOT strategy selection

Enhanced Treatment Selection for Reflective Joint Cracking in Composite Pavements

This research developed a decision-making process that can be used by INDOT to enhance identification of the condition of the underlying concrete joints or cracks by looking at the surface distresses of the asphalt overlay in composite pavements. In order to achieve the research objective, several tasks were performed during the research including literature reviews, data collection, and data analysis. In conjunction with the developed decision-making process, this study also developed a databased to organize the collected data and a computer application to not only increase the accessibility of INDOT field engineers to the sample data but also to improve the analysis process by providing better visualization tools. The data collection was performed based on four steps of field evaluation procedure (visual inspection of asphalt overlay, FWD testing, Coring, and visual inspection of exposed concrete). The collected data was analyzed to show distribution of joint and mid-panel cracks, and correlation between asphalt crack severity and concrete crack severity. Four input factors from the analyzed data (visual inspection of asphalt overlay, D1, LTE, and Resilient Modulus) were selected to develop the decision-making tool. A handbook is also provided to help INDOT field engineers’ decision-making during their field activities. The handbook contains important information of pavements, photographs of cracks, and the exposed concrete condition of sample data points for the benefit of field engineers. Recommendations and limitations are also discussed in this report

A Strategic Assessment of Needs and Opportunities for the Wider Adoption of Electric Vehicles in Indiana

INDOT plans to invest nearly $100 million to build a statewide electric vehicle (EV) charging network as part of the National Electric Vehicle Infrastructure Formula Program. SPR-4509 Phase-I identified energy EV charging deserts in Indiana for long-distance trips. SPR-4509 Phase-II further examines the charging stations\u27 impact on EV long-distance trips in Indiana. Using an agent-based simulation model, the number of charges, vehicle miles traveled, energy used during the trip, and energy used during charging were estimated for nine different cases. High EV daily charging demand areas in Indiana were shown in ArcGIS based on multiple scenarios of different charging station construction phases and EV market penetration rates. The study findings can inform the state’s EV charging plan development

A Strategic Assessment of Needs and Opportunities for the Wider Adoption of Electric Vehicles in Indiana

The primary objective of this study was to assess the challenges and opportunities associated with the provision of appropriate infrastructure to support electric vehicle (EV) operations and electrification across Indiana. A secondary objective of this study was to develop a strategic plan for INDOT that outlines new business opportunities for developing EV charging stations. To achieve these objectives, the project team assessed current and emerging trends in EV operations, particularly EV charging infrastructure and EV demand forecasting. They also examined opportunities for the strategic deployment of EV charging stations by identifying EV infrastructure deficit areas; investigated the impact of EV adoption on highway revenue and the feasibility of new revenue structures; and evaluated strategic partnerships and business models. The agent-based simulation model developed for future long distance EV trip scenarios enables INDOT to identify EV energy deficient areas for current and future energy charging demand scenarios, and it can support Indiana’s strategic plans for EV charging infrastructure development. The results of the revenue impact analysis can inform INDOT’s revenue model. The estimations of the recovery EV fee, the VMT fee, and pay-as-you-charge fee that break-even the fuel tax revenue loss can be used by INDOT in pilot programs to capture users’ perspectives and estimate appropriate fee rates and structures. The insights obtained from the stakeholder interviews can be used to enhance preparedness for increasing EV adoption rates across vehicle classes and to strengthen the engagement of different entities in the provision of charging infrastructure

Public Participation Consortium Blockchain for Smart City Governance

Smart cities have become a trend with improved efficiency, resilience, and sustainability, providing citizens with high quality of life. With the increasing demand for a more participatory and bottom–up governance approach, citizens play an active role in the process of policy making, revolutionizing the management of smart cities. In the example of urban infrastructure maintenance, the public participation demand is more remarkable as the infrastructure condition is closely related to their daily life. Although blockchain has been widely explored to benefit data collection and processing in smart city governance, public engagement remains a challenge. In this article, we propose a novel public participation consortium blockchain system for infrastructure maintenance that is expected to encourage citizens to actively participate in the decision-making process and enable them to witness all administrative procedures in a real-time manner. To that aim, we introduced a hybrid blockchain architecture to involve a verifier group, which is randomly and dynamically selected from the public citizens, to verify the transaction. In particular, we devised a private-prior peer-prediction-based truthful verification mechanism to tackle the collusion attacks from public verifiers. Then, we specified a Stackelberg-game-based incentive mechanism for encouraging public participation. Finally, we conducted extensive simulations to reveal the properties and performances of our proposed blockchain system, which indicates its superiority over other variations

Energy-Efficient Device Selection in Federated Edge Learning

Due to the increasing demand from mobile devices for the real-time response of cloud computing services, federated edge learning (FEL) emerges as a new computing paradigm, which utilizes edge devices to achieve efficient machine learning while protecting their data privacy. Implementing efficient FEL suffers from the challenges of devices’ limited computing and communication resources, as well as unevenly distributed datasets, which inspires several existing research focusing on device selection to optimize time consumption and data diversity. However, these studies fail to consider the energy consumption of edge devices given their limited power supply, which can seriously affect the cost-efficiency of FEL with unexpected device dropouts. To fill this gap, we propose a device selection model capturing both energy consumption and data diversity optimization, under the constraints of time consumption and training data amount. Then we solve the optimization problem by reformulating the original model and designing a novel algorithm, named E2DS, to reduce the time complexity greatly. By comparing with two classical FEL schemes, we validate the superiority of our proposed device selection mechanism for FEL with extensive experimental results

Building a Private LoRaWAN Platform

LoRaWAN technology has been here for several years as one of LPWAN technologies. It consists of various components such as end nodes, a gateway, a network server, and an application server at the minimum. The servers have been exclusive products of commercial companies, and not many experimental or academic ones are available. Recently one such software has been developed. However, few fully functional academic ones have been reported. In this study, we implement a fully functional private independent LoRaWAN platform for the academic research of LPWAN Internet of Things (IoT) and demonstrate that our platform can support not only end-to-end LoRaWAN communication but also graphical user interface on an embedded and limited computing power system

A Strategic Assessment of Needs and Opportunities for the Wider Adoption of Electric Vehicles in Indiana [Phase 2]

SPR-4509 Phase IIThe primary objective of this study was to assess the challenges and opportunities associated with the provision of appropriate infrastructure to support electric vehicle (EV) operations and electrification across Indiana. A secondary objective of this study was to develop a strategic plan for the Indiana Department of Transportation (INDOT) that outlines new business opportunities for developing EV charging stations. To achieve these objectives, the project team assessed current and emerging trends in EV operations, particularly EV charging infrastructure and EV demand forecasting. They also examined opportunities for the strategic deployment of EV charging stations by identifying EV infrastructure deficit areas; investigated the impact of EV adoption on highway revenue and the feasibility of new revenue structures; and evaluated strategic partnerships and business models. The agent-based simulation model developed for future long distance EV trip scenarios enables INDOT to identify EV energy deficient areas for current and future energy charging demand scenarios, and it can support Indiana\u2019s strategic plans for EV charging infrastructure development. The results of the revenue impact analysis can inform INDOT\u2019s revenue model. The estimations of the recovery EV fee, the vehicle miles travelled (VMT) fee, and pay-as-you-charge fee that break-even the fuel tax revenue loss can be used by INDOT in pilot programs to capture users\u2019 perspectives and estimate appropriate fee rates and structures. The insights obtained from the stakeholder interviews can be used to enhance preparedness for increasing EV adoption rates across vehicle classes and to strengthen the engagement of different entities in the provision of charging infrastructure

Enhancing Critical Capacity of Infrastructure Supply Chain to Improve Resilience of Associated Communities and Infrastructure to Disaster

Infrastructure are becoming increasingly interconnected in the modern society. Failure of any type of infrastructure due to natural and/or man-made disasters may impact operational capacities of interdependent infrastructure within its supply chain and result in economic and social losses for the associated communities due to disruption in business continuity. Hence, the decision-makers for an infrastructure should consider the need to enhance not only the post-disaster operational capacities of the infrastructure but also that of its interdependent infrastructure. A large number of studies on post-disaster capacity developments for infrastructure systems and associated communities have been conducted for decades. However, a significantly less attention has been paid to (1) investigating disaster impact propagation due to interdependency of infrastructure networks including civil, civic, social, financial, educational, environmental, and cyber infrastructure, diverse stakeholders, and entities in multiple tiers of supply chain, (2) incorporating impacts of upstream infrastructure’s existing operational capabilities (i.e. business continuity) onto downstream infrastructure’ post-disaster capacity development plans, and (3) developing strategies and effective decision-making rules for infrastructure capacity development considering criticalities of its internal and external interdependencies with other infrastructure systems. This research presents a novel methodology for enhancing the resilience of interdependent communities and infrastructure through systematic and strategic ex-ante capacity development of the entities on its supply chain to maintain the business continuity in a post-disaster environment. To accomplish this objective, this study (1) investigated the nature of interdependencies for the different types of infrastructure based on historical case studies, (2) developed a platform for infrastructure supply chain that incorporates internal and external components of various infrastructure at different tiers, (3) developed a methodology to evaluate criticalities and interdependencies of the internal components and external entities in the infrastructure supply chain, and (4) developed an integrated decision support system to select best capacity development strategies by conforming the decision-makers’ customized risk appetite. With these developed platform, methodology, and decision support system, the decision-maker would be able to evaluate strategies that will enhance the resilience of the affected communities and infrastructure. This research, therefore, contributes to the body of knowledge and practice by (1) adding a new dimension to the concept of seven infrastructure layers by systematically analyzing criticalities and interdependencies of both upstream and downstream entities at different tiers, (2) advancing analysis methods of infrastructure interdependencies by constructing an infrastructure supply chain with respect to seven-layer classifications of infrastructure systems, (3) modeling disaster impact propagations by capturing the impact flows through different types of infrastructure at different tiers, and (4) developing a unified methodology to evaluate the post-disaster capacity needs of infrastructure supply chains by flexibly and proactively reflecting the decision-makers customized risk appetites with the different levels of details during the decision-making process

Rule-based scan-to-BIM mapping pipeline in the plumbing system

The number of scan-to-BIM projects that convert scanned data into Building Information Modeling (BIM) for facility management applications in the Mechanical, Electrical and Plumbing (MEP) fields has been increasing. This conversion features an application purpose-oriented process, so the Scan-to-BIM work parameters to be applied vary in each project. Inevitably, a modeler manually adjusts the BIM modeling parameters according to the application purpose, and repeats the Scan-to-BIM process until the desired result is achieved. This repetitive manual process has adverse consequences for project productivity and quality. If the Scan-to-BIM process can be formalized based on predefined rules, the repetitive process in various cases can be automated by re-adjusting only the parameters. In addition, the predefined rule-based Scan-to-BIM pipeline can be stored and reused as a library. This study proposes a rule-based Scan-to-BIM Mapping Pipeline to support application-oriented Scan-to-BIM process automation, variability and reusability. The application target of the proposed pipeline method is the plumbing system that occupies a large number of MEPs. The proposed method was implemented using an automatic generation algorithm, and its effectiveness was verified