Dalla Chiara, Giacomo and Anne Goodchild. Giving Curb Visibility to Delivery Drivers. Intersections + Identities: State of Transportation Planning 2022, 134-143.
Fundamental diagrams describe the relationship between speed, flow, and density for some roadway (or set of roadway) configuration(s). These diagrams typically do not reflect, however, information on how speed-flow relationships change as a function of exogenous variables such as curb configuration, weather or other exogenous, contextual information. In this paper we present a machine learning methodology that respects known engineering constraints and physical laws of roadway flux–those that are captured in fundamental diagrams– and show how this can be used to introduce contextual information into the generation of these diagrams. The modeling task is formulated as a probe vehicle trajectory reconstruction problem with Neural Ordinary Differential Equations (Neural ODEs). With the presented methodology, we extend the fundamental diagram to non-idealized roadway segments with potentially obstructed traffic data. For simulated data, we generalize this relationship by introducing contextual information at the learning stage, i.e. vehicle composition, driver behavior, curb zoning configuration, etc, and show how the speed-flow relationship changes as a function of these exogenous factors independent of roadway design.
Competition throughout the urban freight supply chain is steadily growing. Companies need to devise innovative methods for the transportation of goods from raw materials all the way to the final consumer. From concept to practice, it can be challenging to identify affordable solutions. This article highlights recent research conducted by the University of Washington’s Urban Freight Lab and its partners to explore new methods to reduce transportation costs, improve the customer experience, reduce carbon footprint, and reduce urban congestion after goods leave the shipping docks.
Looking to go offshore, or improve your current offshore operations? A demand-driven supply chain strategy may be the answer. Here’s how to build one.
“I’d like the filet mignon—please make that well done, but juicy!” As anyone who’s ever waited tables knows, sometimes the requests you get are just unrealistic. But is this particular customer’s order any less realistic than the CEO announcing: “I’d like to move all production to China, but without increasing inventory or affecting service levels!”
Fortunately, we as operations managers have more tools at our disposal to respond to the CEO’s request that the waiter has to that diner. This column addresses those options. We assume that you have weighed the impact on your total cost to serve and ability to meet your customer demands, and have determined that off-shore sourcing and/or manufacturing is your best option. Our goal here is to help you improve that performance, especially as the speed of market change continually increases, and customer demands intensify. Simply put, we believe that the key to success in the global arena lies in two critical activities: (1) improving the demand signal and (2) decreasing the response time.
In an age of expanding online commerce, is home delivery greener than sending full truckloads of goods to stores and then customers driving to them? A detailed regional study finds compelling answers.
Readers who were teenagers in the 1980s may remember driving to a Sam Goody store to buy music. You probably also remember your disappointment when sometimes the tape or CD wasn’t in stock when you arrived. Perhaps you returned to your car and headed for Tower Records to try your luck there.
Your kids would probably find this story inconceivable today. The advent of the internet has profoundly altered consumer expectations. Immediate gratification is getting closer by the day; you can now obtain your favorite song in seconds, and order and receive physical goods in as little as a few hours in some urban areas.
Today’s ninth-grader expects to find any product she wants in seconds and order it right away on her smartphone. What’s more, she expects that the order will be accurate, complete, well-packed, and easy to return if desired.