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1. Commute Booster: A Mobile Application for First/Last Mile and Middle Mile Navigation Support for People With Blindness and Low Vision

   https://doi.org/10.1109/JTEHM.2023.3293450  

   Feng, Junchi ; Beheshti, Mahya ; Philipson, Mira ; Ramsaywack, Yuvraj ; Porfiri, Maurizio ; Rizzo, John-Ross ( January 2023 , IEEE Journal of Translational Engineering in Health and Medicine)
2. A-VRPD: Automating Drone-Based Last-Mile Delivery Using Self-Driving Cars

   https://doi.org/10.1109/TITS.2023.3266460  

   Imran, Navid Mohammad ; Mishra, Sabyasachee ; Won, Myounggyu ( September 2023 , IEEE Transactions on Intelligent Transportation Systems)

   Drone-based last-mile delivery is an emerging technology that uses drones loaded onto a truck to deliver parcels to customers. In this paper, we introduce a fully automated system for drone-based last-mile delivery through incorporation of autonomous vehicles (AVs). A novel problem called the autonomous vehicle routing problem with drones (A-VRPD) is defined. A-VRPD is to select AVs from a pool of available AVs based on crowd sourcing, assign selected AVs to customer groups, and schedule routes for selected AVs to optimize the total operational cost. We formulate A-VRPD as a Mixed Integer Linear Program (MILP) and propose an optimization framework to solve the problem. A greedy algorithm is also developed to significantly improve the running time for large-scale delivery scenarios. Extensive simulations were conducted taking into account real-world operational costs for different types of AVs, traveled distances calculated considering the real-time traffic conditions using Google Map API, and varying load capacities of AVs. We evaluated the performance in comparison with two different state-of-the-art solutions: an algorithm designed to address the traditional vehicle routing problem with drones (VRP-D), which involves human-operated trucks working in tandem with drones to deliver parcels, and an algorithm for the two echelon vehicle routing problem (2E-VRP), wherein parcels are first transported to satellite locations and subsequently delivered from those satellites to the customers. The results indicate a substantial increase in profits for both the delivery company and vehicle owners compared with the state-of-the-art algorithms. 

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3. An Application of ASP in Nuclear Engineering: Explaining the Three Mile Island Nuclear Accident Scenario

   https://doi.org/10.1017/S1471068420000241  

   HANNA, BOTROS N. ; TRIEU, LY LY ; SON, TRAN C. ; DINH, NAM T. ( November 2020 , Theory and Practice of Logic Programming)

   null (Ed.)

   Abstract The paper describes an ongoing effort in developing a declarative system for supporting operators in the Nuclear Power Plant (NPP) control room. The focus is on two modules: diagnosis and explanation of events that happened in NPPs. We describe an Answer Set Programming (ASP) representation of an NPP, which consists of declarations of state variables, components, their connections, and rules encoding the plant behavior. We then show how the ASP program can be used to explain the series of events that occurred in the Three Mile Island, Unit 2 (TMI-2) NPP accident, the most severe accident in the USA nuclear power plant operating history. We also describe an explanation module aimed at addressing answers to questions such as “why an event occurs?” or “what should be done?” given the collected data. 

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4. Spatial welfare effects of shared taxi operating policies for first mile airport access

   https://doi.org/10.1016/j.ijtst.2017.07.001  

   Ma, Ziyi ; Urbanek, Matthew ; Pardo, Maria Alejandra ; Chow, Joseph Y.J. ; Lai, Xuebo ( December 2017 , International Journal of Transportation Science and Technology)
5. Understanding the Last Mile Transportation Concept Impacting Underserved Global Communities to Save Lives During COVID-19 Pandemic

   https://doi.org/10.3389/ffutr.2021.732331  

   Jones, Erick C. ; Azeem, Gohar ; Jones, Erick C. ; Jefferson, Felicia ; Henry, Marcia ; Abolmaali, Shannon ; Sparks, Janice ( September 2021 , Frontiers in Future Transportation)

   The underserved population could be at risk during the times of crisis, unless there is strong involvement from government agencies such as local and state Health departments and federal Center for Disease Control (CDC). The COVID-19 pandemic was a crisis of different proportion, creating a different type of burden on government agencies. Vulnerable communities including the elderly populations and communities of color have been especially hard hit by this pandemic. This forced these agencies to change their strategies and supply chains to support all populations receiving therapeutics. The National Science Foundation [National Science Foundation (NSF) Award Abstract # 2028612] funded RAID Labs to help federal agencies with strategies. This paper is based on a NSF funded grant to work on investigating supply chain strategies that would minimize the impact on underserved populations during pandemic. This NSF funded study identified the phenomena of last mile importance. The last mile transportation concept was critical in saving lives during the pandemic for underserved populations. The supply chain model then maximizes social goods by sending drugs or vaccines to the communities that need it the most regardless of ability to pay. The outcome of this study helped us prioritize the communities that need the vaccines the most. This informs our supply chain model to shift resources to these areas showing the value in real time prioritization of the COVID-19 supply chain. This paper provides information can be used in our healthcare supply chain model to ensure timely delivery of vaccines and supplies to COVID-19 patients that are the most vulnerable and hence the overall impact of COVID-19 can be minimized. The use of electrical vehicles for last mile transportation can help in significantly fighting the climate change. 

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