Project: #364 Autonomous Food Delivery Impacts on Traffic and Sustainability Progress Report - Reporting Period Ending: Sept. 30, 2022 Principal Investigator: Destenie Nock Status: Completed Start Date: July 1, 2021 End Date: June 30, 2022 Research Type: Applied Grant Type: Research Grant Program: FAST Act - Mobility National (2016 - 2022) Grant Cycle: 2021 Mobility UTC Progress Report (Last Updated: Sept. 27, 2022, 1:22 p.m.) % Project Completed to Date: 100 % Grant Award Expended: 100 % Match Expended & Document: 0 USDOT Requirements Accomplishments Major goals of the project include the following: • Produce a traffic modelling tool for understanding how grocery delivery market penetration will impact congestion and environmental sustainability • Environmental sustainability and equity trade-off assessment. We will perform an analysis of how grocery delivery impacts air pollution and congestion in low income areas. • Develop a relationship with grocery and autonomous vehicle companies to promote interdisciplinary transportation planning. Over the past few months we have improved the grocery demand model and calibrated it against real traffic counts. Our demand model simulates grocery delivery in a built environment. It estimates number of trips and vehicle miles traveled (VMT) under different grocery batching scenarios and market penetration rates. The batching scenarios refer to a grocery store combining different household deliveries into a single grouping. The market penetration rate is the proportion of grocery shoppers that switch from in-store shopping to online delivery orders. Over the past few months several improvements, analysis, and changes have been made to improve the demand model. These include the following: 1. We improved the model by only performing delivery trips based on the distance the grocery store is to the home. This is the closest grocery to home system which assumes that deliveries are being made to the closest traffic analysis zone (TAZ) which has a grocery store. 2. We have been able to better simulate grocery demand because of new tour-level information. A tour refers to the chain of trips that a person makes. With this level of information, we can determine where people’s homes are, and can route delivery tours to actual demand locations. 3. We can generate representative demand scenarios that serve as inputs to commercial transportation analysis software. The outputs from the demand model are in the form of Origin-Destination (OD) matrices, that result from a specified batch size and market penetration rate. 4. The framework we created has increased understanding and awareness of the grocery delivery challenge in the transportation sector. During COVID there has been an increase in the amount of people sourcing their groceries online. There was large uncertainty regarding how this shift to online delivery would impact emissions. We have shown how grouping multiple customer's deliveries (i.e., batching), delivering from original versus closest grocery stores, and market penetration could impact the emissions and congestion in an area. In addition to developing the demand model, we have fitted it into a Monte Carlo simulation to observe trends and uncertainty in our delivery system after several iterations. With this, we can choose OD matrices near the median and the extreme, and them use them as input to transportation analysis software. This will allow us to have a bound on congestion impacts for a certain batch size and penetration rate. Papers: We have submitted our final report, and submitted the paper for publication in a peer-reviewed journal. We have also submitted the research to the Transportation Research Board Conference. Collaborations: As a part of this project we have met with representatives from Giant Eagle (grocery store), EasyMile (autonomous food delivery company), and the Pugent Sound Regional Council (transportation planner). Professional Development: The PhD student has had the opportunity to present his work at the IISE conference, and has mentored an undergraduate student during this project. While the PhD student was mentoring the summer research student, the advisors (Harper and Nock) met with the graduate student each week to discuss leadership and communication skills. Then twice a month the advisors would meet with the PhD student and undergraduate student to help steer the project. This has improved the PhD student's communication skills, and now the student is advising two undergrads. Impacts The effectiveness of the transportation system will be improved by understanding how food delivery impacts congestion, and air pollution emissions. We have presented our findings at multiple conferences, which we believe will aid in adoption of new practices in transportation planning. Our publication and final research report has increased the scientific body of knowledge on the ways grocery delivery will impact emissions and congestion within a region. The framework we created has increased understanding and awareness of the grocery delivery challenge in the transportation sector. During COVID there has been an increase in the amount of people sourcing their groceries online. There was large uncertainty regarding how this shift to online delivery would impact emissions. We have shown how grouping multiple customer's deliveries (i.e., batching), delivering from original versus closest grocery stores, and market penetration could impact the emissions and congestion in an area. Other We have accomplished the following during the reporting period: 1. We developed food delivery demand model(s) and use systems transportation modeling approaches to quantify how autonomous food delivery could affect peak hour traffic operations, and determine delivery alternatives that are most sustainable. 2. We have integrated the demand model into the static traffic assignment model, which is being used to identify how food delivery demand impact the overall congestion within a city. 3. We are developing relationships with relevant stakeholders including Giant Eagle (local grocery store), Puget Sound Regional Council (transportation authority), and autonomous vehicle companies. 4. We have completed the analysis for a metropolitan region, and identified key factors in grocery delivery systems which impact emissions and congestion. This framework can be used to evaluate deployment plans for grocery delivery services. Outcomes New Partners Puget Sound Regional Council (transportation authority) Issues During the Spring 2021 Semester our first PhD student Anthony Reid decided to leave the program with an MS degree due to a combination of personal reasons and the COVID pandemic. This has been resolved by hiring a second PhD student (Mateo) who is now leading the analysis on the project. We have 100% of our matching scheduled to be charged, but we have had challenges with getting a charging string from the accelerator. The cost share hasn't been set-up yet; we're working with the Accelerator to get the task linked so we can charge to it but that hasn't happened yet. We are planning to do AY Salary for this but since the Accelerator hasn't set it up we can't charge there yet.