We are seeing a growing body of research into last-mile logistics for delivery of products in cities. The growing congestion of cities and the explosion in e-commerce home delivery have challenged traditional last-mile logistics strategies that have focused on point-of-sale delivery. “In the city, shipments are typically much smaller and more fragmented than in regional transport,” says Matthias Winkenbach, a research scientist at MIT’s Center for Transportation and Logistics, and director of Megacities Logistics Lab in MIT News.
Smaller and more fragmented transport
There is greater uncertainty and complexity caused by increasingly dense and congested cities. Home delivery routes of e-commerce shipments typically consist of 50 to 150 stops per day. By comparison, beverage distributors to commercial clients have routes of 10 to 15 deliveries. The process of looking for parking spaces is a key drivers of inefficiency and congestion.
Consumer e-commerce also boosts the chance of delivery failure, which adds to complexity and cost. Matthias Winkenbach: “You often need to schedule deliveries for customer specific time windows, and there’s a greater risk the customer will not be home. Planners need to accept the new reality of internet shopping because it’s only likely to keep growing. People are getting used to the convenience of ordering products online and receiving them the next day or even the same day.”
Urban distribution networks
In recent decades, logistics centers have moved from the cities to the exurbs, due in part to lower real estate costs. With increasing shipments in urban areas, however, there are now more multi-tier distribution systems, in which hubs are augmented with smaller logistic centers and fulfillment operations in the city. Companies are experimenting with on-demand fleet services including crowdsourced delivery providers.
Big data and urban analytics
Planners are often insulated from the complex realities of the delivery process, which leads to erroneous assumptions. “Companies have a lot of data to sift through, but it tends to be simple data like transactions, delivery records, and customer information, primarily stored in-house,” Matthias Winckenbach says. “By combining it properly, you can generate a lot of insight into how demand is structured, how your customers behave, and how you can adapt your delivery systems to better serve customer needs. Planners often assume that drivers can park the vehicle in front of the customer’s house, but this is often not the case”.
The drivers know where they can potentially park, which might be three blocks away, but that real-world information rarely makes it into the planning process. Most fleets now have GPS tracking, and the resolution and accuracy are improving. Movement data is extremely useful for extracting local driver knowledge. By connecting movement data with transactional data, you can know where the vehicle parked and which customers were served from that stop. This enables route planners to come up with more realistic plans that drivers can actually adhere to.
Smart lockers, infrastructure, and autonomous vehicles
“The customer usually likes smart lockers because they can walk a short distance to receive their package whenever it’s convenient,” says Winkenbach. “Logistics service providers like them because they consolidate demand, letting them drop a lot of shipments at one stop. This reduces the risk of failed delivery to almost zero while increasing efficiency and lowering cost. Companies are working on smart street lighting with sensors that detect where free parking spaces open up. If you made that data available to service providers, it would streamline deliveries and reduce double parking.”
Autonomous vehicles have been proposed for last-mile delivery in cities with high labor costs. Yet, the conveniences imagined for self-driving taxi services do not translate to package delivery. With autonomous taxis, the routes can be coordinated to pick up new passengers near the drop-off point, so the vehicle rarely drives empty.
The Megacities Logistics Lab is helping companies answer questions like how many satellite facilities are needed, where they should be located, and what their function should be to optimize delivery systems.
Read the full interview on MIT Lab.