The Internet of (Delivering) Things
How a map can be the platform for real-time communication
Traffic is an easy thing to complain about. So is a late train. Commuting, running errands, visiting friends and places — so much of our day is spent moving from point A to B. Our cities are made up of constantly circulating things, likened by Jane Jacobs to an “intricate ballet” in her book The Death and Life of Great American Cities from 1963. When these dance routines fall out of rhythm, they result in more than complaining. Congestion creates costly and environmentally-taxing inefficiencies and even hazards. The problems leak into all components of transportation: streets, parking, mass transit, and even flexible transit options like micro-transit, bikes, and scooters. They’re also inter-dependent; relieving one usually results in exacerbating the other, at least temporarily.
Most of the solutions and conversations in the transportation space revolve around improving how people move in cities. It’s a relatable and exciting arena to bring technology to. In seeing the domino effect of transportation, the more near-term, fast-growing transportation problem to solve is improving how goods move.
The goods 📦
The urban goods delivery system accounts for a large and quickly increasing part of transport flows. So how’d we get here?
Delivery in cities used to be almost entirely made up of bulk commercial freight. This “last mile” of getting loads of goods into city centers was always problematic and expensive. But, as it was limited to commercial neighborhoods and shops, solutions like restricted hours and designated curbs helped keep the peace. In terms of residential deliveries, people in cities had things like milk and the newspaper delivered to their door, but that’s about it. Accessibility to shops and businesses was a big perk for choosing to live in a city, after all. In recent years, the introduction of e-commerce and heightened customer demands are reshaping urban freight altogether.
At its inception, e-commerce bloomed in suburban communities by providing access to goods that otherwise may have been long drives away or inaccessible altogether. Since suburbs were built near highways and with vehicles in mind, they successfully integrated fulfillment centers and a growing number of delivery trucks. As delivery times got shorter and shorter, city dwellers soon wanted in on this new level of convenience.
Today, when given the option between a 20-minute walk to a retail store or a two-day shipment to the apartment door, we’re increasingly picking the latter. We want it all. We still want to live in dense, walkable cities with grocery stores, restaurants, and retail shops nearby (which all require commercial freight delivery) and we want super-fast, on-demand delivery. The result is the suburban model of e-commerce on hyper-drive flooding our crowded, “walkable” urban streets with box trucks.
Square peg, round hole 🔨
How can the city streets accommodate for this new wave of delivery? Right now, they can’t, argues Christopher Leinberger, chair of the Center for Real Estate and Urban Analysis at George Washington University.
“Urban freight trips are basically fitting a square peg into a round hole. It’s more trucks and more routes jammed onto city streets, which is trying to address a challenge with obsolete thinking,” says Leinberger.
What makes these square peg misfit problems more urgent is that the number of daily deliveries is increasing and their load size, decreasing. Beyond Amazon’s Prime Now booming 2-hour delivery, think about the individual items being moved around the city by on-demand services and the gig economy. These single or few-item shipments require more moving parts on our already over-capacity roads. Municipalities are very aware of this growing problem and cities like New York and Seattle have set forward initatives in their own “Freight Master Plans.” New York has even put in place an Office of Freight Mobility.
The companies moving the goods know that the worsening congestion they’re contributing to hurts their bottom line and their ability to meet customer expectations. As a result, services that can manage to are increasingly migrating off the street and into new territory like bike lanes, sidewalks, and even the air by using new kinds of delivery vehicles. It seems the next era of urban freight problems and potential lies in the evolving nature of what will be moving goods in the future.
The next era requires coordination
Even if we sculpt the square peg to fit that round hole, we’re quickly finding new geometries we need solve for. Walking through Manhattan in 2018, you may see a biker with a Seamless order, a Postmates delivery person on-foot, a small box-truck trying to find the closest place to park, and a freighter looking for a Whole Foods loading dock all within one block. Looking a few years into the future, let’s imagine a different scene: a drone managed by private air-traffic control overhead scanning for its drop-off, sidewalk bots hunting for the right stoop and on-road electric delivery vans are all moving from origin to destination, working together in harmony. It’s a new “ballet” to be choreographed. Plus, in this tight-knit and more autonomous movement of goods, the last-50-feet becomes the *new* last-mile problem.
What’s needed to make the last-50-feet to arrival efficient and the coordination of these vehicles possible? They’ll need to be able to communicate the spatial information they collect in real-time. That way, the network of bots could all rely on shared knowledge of entrances, edges and unpredictable elements to efficiently route to their final destination.
Follow the ants 🐜
A mechanism for enabling teamwork between vehicles doesn’t necessarily require direct communication. Thinking of this mesh of devices as an ecosystem or a swarm, we can look to biology for inspiration. One solution for indirect coordination is to mimic the ingenious tactic ants use to tell the rest of the colony where to find food.
I’m sure you’ve seen ants in a organized single-file line, seeming to be telling each other where to go or following the leader of the operation. In reality, there is no leader and there’s no communication from ant-to-ant. There is, however, a shared environment and shared reliance of clues called “local pheromone trails”.
Here’s how those ants all got there: a few ants leave to look for food and all leave pheromone trails behind them as they go, like marking trees to find your way home after a hike. One ant bumps into a crumb, grabs a piece, and heads back home using her trail. On her way back, she leaves another layer to the trail behind her, strengthening the scent. One of the other ants blindly roaming around bumps into that strong trail and knows to follow it. After picking up some of the crumb, that ant also takes it back home. Now that trail is doubly reinforced, bringing more ants and more trails so long as there’s more food to bring back. These local pheromone trails function as a shared external memory for the ant colony.
This is called “stigmergy” and it applies to more than just ants. It’s essentially a network of things that can tell each other where something is by leaving a trace in the environment instead of directly communicating or planning. It results in a coherent structure that supports collaboration. No individual memory, intelligence, talking, or even awareness of each other required.
A map platform for digital pheromone trails
This form of swarm intelligence can be used to produce efficient navigation between vehicles, too. For example, the first delivery bot to make a route may slowly navigate its surroundings like an ant scouting for crumbs, relying entirely on its sensors, avoiding a fire hydrant, circumventing construction, finding an on-ramp. Eventually, the bot drops off the package at a particular door, gathering more information about how to be more successful next time. Once that breadth of spatial and routing knowledge is gathered, another vehicle moving through that space may have a much easier time navigating and finding that door. Just like a pheromone trail, the strength of this path would fade over time and increase with reinforcement.
What’s required to make that teamwork and ‘external memory’ possible? At Mapfit, we believe the answer is a high-definition map cloud that allows for inputting, plotting, and publishing live updates as they’re gathered. Essentially, creating a digital environment for trails to be left. We’re building the processes for maintaining this accurate and real-time representation of the world. So, if that bot scooting down a sidewalk detects a new understanding of its route, our platform will be able to intake this data, clean it up, and refresh the mapping stack to reflect the current information. That way the next passerby could use that update to efficiently navigate — in turn, sharing another fresh memory on the map with a whole ecosystem of things trying to get from point A to crumb.