Smart Mobility Blueprint for Illinois

R27-228Connected, automated, shared, and electric (CASE) technologies have invoked Mobility 4.0\u2014a connected, digitized, multimodal, and autonomous system of systems. This project established a flexible and adaptable blueprint that would streamline multidisciplinary and multistakeholder efforts as well as leverage available resources to prepare the Illinois Department of Transportation and other transportation agencies. Illinois has several strengths that make it an attractive location for CASE technology companies, including a talent pool from top-ranked universities, well-developed transportation infrastructure, government support, and a robust ecosystem of collaboration and innovation. Illinois also faces potential challenges (e.g., competition from other states and countries, limited access to funding, regulatory hurdles, and infrastructure readiness for new mobility technologies). Seven smart mobility pillars were identified in this study for Illinois\u2014namely, connected and automated (CA) freight, scaling intelligent transportation systems, farm automation, insurance, urban mobility, CA logistics, and alternative fuels. The balanced scorecard ranked the pillars as follows (from highest): alternative fuels, scaling intelligent transportation systems, CA freight, farm automation, CA logistics, insurance, and urban mobility. Tactical focus areas were also identified per pillar and were prioritized with suggested leads and stakeholders to champion the CASE directives and opportunities. Near-term actions for Illinois were also suggested that included establishing a central structure for Illinois\u2019 CASE program, enriching the knowledge base and experience, preparing transportation infrastructure, partnerships with external stakeholders, and expansion of laws, regulations, and policies that will help administer and grow CASE technology deployment and integration

Longitudinal Tracking Survey to Understand Changing Consumer Spending, Telework and Mobility Patterns Through the Pandemic

69A3552047139Recognizing that the COVID-19 pandemic provided a unique natural experiment in the use of Information and Communication Technologies, this report describes a 7-wave longitudinal tracking survey conducted by the Tier I Center on Telemobility to monitor the evolving consumer spending, telework, and activity participation behavior through the COVID-19 pandemic. The goal is to gain insights on expected post-pandemic virtual and physical mobility. The 7-wave longitudinal tracking survey was conducted between December 2020 and March 2022 through an online platform (Prolific) and resulted in data from 1877 unique respondents in the United States. Details are presented regarding the 12 different categories of questions asked in the survey, survey dissemination strategy and incentives provided to the respondents, and the response rates across various waves of the survey. Also presented are results of an exploratory analysis using the collected data on changing consumer spending; telework behavior and related attitudes and experiences; and the use for various types of online entertainment, delivery, and local transit pass related subscription services at various time points including pre-pandemic, last three years and post-pandemic. The report concludes with a summary of several studies using the collected data

Performance Evaluation of Choice Set Generation Algorithms for Modeling Truck Route Choice: Insights from Large Streams of Truck-GPS Data

This thesis evaluates truck route choice set generation algorithms and derives guidance on using the algorithms for effective generation of choice sets for modeling truck route choice. Specifically, route choice sets generated from a breadth first search link elimination (BFS-LE) algorithm are evaluated against observed truck routes derived from large streams of GPS traces of a sizeable truck fleet in the Tampa Bay region of Florida. A systematic evaluation approach is presented to arrive at an appropriate combination of spatial aggregation and minimum number of trips to be observed between each origin-destination (OD) location for evaluating algorithm-generated choice sets. The evaluation is based on both the ability to generate relevant routes that are typically considered by the travelers and the generation of irrelevant (or extraneous) routes that are seldom chosen. Based on this evaluation, the thesis offers guidance on effectively using the BFS-LE approach to maximize the generation of relevant routes. It is found that carefully chosen spatial aggregation can reduce the need to generate large number of routes for each trip. Further, estimation of route choice models and their subsequent application on validation datasets revealed that the benefits of spatial aggregation might be harnessed better if irrelevant routes are eliminated from the choice sets. Lastly, a comparison of route attributes of the relevant and irrelevant routes shed light on presence of systematic differences in route characteristics of the relevant and irrelevant routes

Comprehensive Exploratory Analysis of Truck Route Choice Diversity in Florida

This study presents a comprehensive exploratory analysis of truck route choice diversity in the state of Florida, for both long-haul and short-haul truck travel segments. It employs six metrics to measure three different dimensions of diversity in truck route choice between any given origin–destination (OD) pair. These dimensions are: (a) number of distinct routes used to travel between the OD pair, (b) the extent of overlap (or lack thereof) among the routes, and (c) the evenness (or dominance) in the usage of different unique routes. The diversity metrics were applied to a large database of 73,000 truck routes derived from 200 million GPS records. Descriptive analysis and statistical modeling of the diversity metrics offered insights into the determinants of various dimensions of truck route choice diversity between any OD pair. The results are useful for improving choice set generation algorithms for truck route choice modeling and in truck route policies and investments. An essential step toward enhancing highway freight mobility is to improve our understanding of freight-truck route choice behavior. Specifically, analysis of the routes that trucks use to travel between different origins and destinations can support the design of truck routing policies aimed at mitigating congestion, improving travel time reliability, and facilitating truck movement during network disruptions. However, research on truck route choice has been limited due to insufficient data on truck movements. The recent availability of global positioning systems (GPS) data has encouraged research on truck route choice modeling (1–3) and highway freight performance measures (4, 5). Yet little attention has been paid to exploring the diversity or variability of truck route choice between travel origins and destinations. An improved understanding of truck route diversity has significance in both freight modeling and planning. For modeling applications, understanding truck route choice diversity can help determine the number and structure (i.e., extent of overlap) of route alternatives to be used in route choice models and traffic assignment procedures (6). For planning applications, analyzing the diversity of truck route choices observed in the field can help inform truck routing decisions during regular and emergency situations. For example, identifying origin–destination (OD) pairs with high travel demand but low diversity in the routes used (e.g., a single route used) can help identify critical segments of the network and inform routine infrastructure maintenance scheduling as well as re-routing efforts during emergency recovery. Also, one can apply route diversity measures to evaluate the redundancy of (or lack of) truck routes in existing transportation infrastructure to justify long-term investment in truck corridors to increase network redundancy. This research presents a comprehensive exploratory analysis of truck route choice diversity in the State of Florida for both long-haul and short-haul travel segments. Specifically, the paper addresses two broad questions: How to measure the degrees of diversity in the routes trucks use to travel between an OD pair? and, What factors influence the diversity of truck route choice between an OD pair? To this end, six metrics are utilized to measure the following three different dimensions of diversity in route choice between a given OD pair: (a) number of different routes used between the OD pair, (b) extent of overlap (or lack thereof) among the routes, and (c) evenness (or dominance) of the use of different unique routes between that OD pair. These metrics are applied to quantify truck route choice diversity using a database of about 73,000 routes derived from more than 200 million truck-GPS records. Next, statistical models are estimated to explore the influence of various determinants on the three dimensions of route choice diversity between hundreds of OD pairs. The models provide insights into the influence of the characteristics of truck travel demand, OD location, and network structure on the diversity of truck route choice between an OD pair. Potentially, these insights can help travel modelers in improving choice set generation algorithms for modeling truck route choice and help planners in devising truck routing policies. The next section reviews past studies on variability in route choice behavior. The following section summarizes the truck-GPS data used for this study. The metrics used to quantify diversity in truck route choice are then elaborated. The next section presents the statistical modeling methodologies used in this study. Subsequently, empirical results are presented and discussed. The last section concludes the paper

In-person, pick up or delivery? Evolving patterns of household spending behavior through the early reopening phase of the COVID-19 pandemic

Consumer reactions to COVID-19 pandemic disruptions have been varied, including modifications in spending frequency, amount, product categories and delivery channels. This study analyzes spending data from a sample of 720 U.S. households during the start of deconfinement and early vaccine rollout to understand changes in spending and behavior one year into the pandemic. This paper finds that overall spending is similar to pre-pandemic levels, except for a 28% decline in prepared food spending. More educated and higher income households with children have shifted away from in-person spending, whereas politically conservative respondents are more likely to shop in-person and via pickup

For whom did telework not work during the Pandemic? understanding the factors impacting telework satisfaction in the US using a multiple indicator multiple cause (MIMIC) model

The COVID-19 pandemic required employees and businesses across the world to rapidly transition to work from home over extended periods, reaching what is likely the upper bound of telework in many sectors. Past studies have identified both advantages and disadvantages of teleworking. The pandemic experience offers a unique opportunity to examine employees' experiences and perceptions of telework given the broad participation duration and extent. While employer strategies will play a major role in defining the future forms and adoption of telework, employee preferences and constraints, such as access to appropriate technology to work from home or the home environment, are also going to be important factors. Using data from a U.S. representative sample of 318 working adults, this study uses a Multiple Indicator Multiple Cause Model (MIMIC) to understand employee satisfaction with telework. The presented model links telework satisfaction with experienced and perceived benefits and barriers related to telework, and hence provide a causal structure to our understanding of telework satisfaction. We also present an ordered probit model without latent variables that help us understand the systematic heterogeneity in telework satisfaction across various socio-demographic groups. The results suggest younger and older aged individuals experienced/perceived lower benefits and higher barriers to teleworking compared to middle aged individuals. The results also suggest a disproportionate impact on Hispanic or Latino and Black respondents as well as on those with children attending online school from home. Accordingly, this study highlights important factors impacting telework adoption that employers and policy makers should consider in planning future work arrangements and policies in a post-pandemic world

Longitudinal tracking survey to understand changing consumer spending, telework and mobility patterns through the pandemic

16. Abstract Recognizing that the COVID-19 pandemic provided a unique natural experiment in the use of Information and Communication Technologies, this report describes a 7-wave longitudinal tracking survey conducted by the Tier I Center on Telemobility to monitor the evolving consumer spending, telework, and activity participation behavior through the COVID-19 pandemic.  The goal is to gain insights on expected post-pandemic virtual and physical mobility. The 7-wave longitudinal tracking survey was conducted between December 2020 and March 2022 through an online platform (Prolific) and resulted in data from 1877 unique respondents in the United States. Details are presented regarding the 12 different categories of questions asked in the survey, survey dissemination strategy and incentives provided to the respondents, and the response rates across various waves of the survey. Also presented are results of an exploratory analysis using the collected data on changing consumer spending; telework behavior and related attitudes and experiences; and the use for various types of online entertainment, delivery, and local transit pass related subscription services at various time points including pre-pandemic, last three years and post-pandemic. The report concludes with a summary of several studies using the collected data.</p