The rapid onset of the COVID-19 pandemic in March 2020 marked a challenging time for the US and its freight industry. Manufacturing slowed, consumer purchasing patterns changed, and for many, shopping moved online. The freight industry suffered a sharp decline in shipments, followed by a surprisingly quick rebound. The industry had to adapt quickly to meet fast-changing demand and supply patterns upended by global supply chain disruptions. This paper uses U.S. intermodal activity data, supported by in-depth interviews with leaders of railroads, intermodal carriers, equipment manufacturers, car leasing companies, shippers, and e-commerce players to characterize and assess how the rail industry met the challenge of this demand whiplash and other performance impediments. What emerges is a rich picture of the multi-actor intermodal supply chain, the impacts of COVID-19 on it, the performance of the logistics system in general, and railroads in particular during the pandemic. Industry interviews revealed that a handful of choke points, many of which were outside the rail industry, complicated supply chain responses to COVID-19. The paper shows how the rail industry was an essential component of pandemic resilience, demonstrating a high level of adaptability to meet consumer and business demands. Through the use of depth interviews it reveals the complexity of the intermodal supply chain, and it accurately foretells the subsequent disruptions that continued to plague that supply chain long after the initial impacts of the pandemic.

This paper investigates the potential of autonomous minibuses which take on-demand directional routes for pick-up and drop-off in a grid network of wider area with low density, followed by fixed routes in areas with greater demand. Mathematical formulation for generalized costs demonstrates its benefits, with indicators proposed to select existing bus routes for conversion with the options of zonal express and parallel routes. Simulations on modeled scenarios and case studies with bus routes in Chicago show reductions in both passenger costs and generalized costs compared with existing fixed-route bus services between suburban areas and the central business district.

This paper investigates managed lane toll setting and its effect under mixed traffic of connected automated vehicles (CAVs), high-occupancy vehicles (HOVs), and human-driven vehicles (HDVs), with the goal of avoiding flow breakdown and minimizing total social cost. A mesoscopic finite difference traffic simulation model considers the flow–density relationship at different CAV market penetration rates, lane-changing behaviors, and multiple entries/exits, interacting with a reactive toll setting mechanism. The results of Monte Carlo simulation suggest an optimal policy of untolled HOV/CAV use with tolled HDVs in particular scenarios of limited CAV market penetration. Small and targeted tolling avoids flow breakdown in managed lanes while prioritizing HOVs and other vehicles with high values of time. Extensions of the formulation and sensitivity analysis quantify the benefits of converting high-occupancy HDVs to CAVs. The optimal tolling regime combines traffic science notions of flow stability and the economics of resource allocation.

This paper analyzes and compares patterns of U.S. domestic rail freight volumes during and after the disruptions caused by the 2007–2009 Great Recession and the COVID-19 pandemic in 2020. Trends in rail and intermodal (IM) shipment data are examined in conjunction with economic indicators, focusing on the extent of drop and recovery of freight volumes of various commodities and IM shipments, and the lead/lag time with respect to economic drivers. Impacts of the Great Recession and the rebound from it were slow to develop, whereas COVID-19 produced both profound disruptions in the freight market and rapid rebound, with important variations across commodity types. Demand for energy-related commodities (coal, petroleum, and fracking sand) dropped during the pandemic whereas demand for other commodities (grain products and lumber, and IM freight) rebounded rapidly and in some cases grew. Overall, rail freight experienced a rapid rebound following the precipitous drop in traffic in March and April, 2020, achieving a near-full recovery in 5 months. As the recovery proceeded through 2020, IM flow, containers moving by rail for their longest overland trips, rebounded strongly, some exceeding 2019 levels. In contrast, rail flows during the Great Recession changed slowly with the onset and recovery extending over multiple years. Pandemic response reflected the impacts of quick shutdowns and a rapid shift in consumer purchasing patterns. Results for the pandemic illustrate the resilience of the U.S. rail freight industry and the multifaceted role it plays in the overall logistics system. Amid a challenging logistic environment, freight rail kept goods moving when other methods of transport were constrained.