Modern technology and logistics infrastructure have made sending a package anywhere in the world easier than ever imagined. The most visible part of logistics – the last mile – is as important as ever, and yet it continues to be complicated.
In major cities, commonplace obstacles like road closures, construction, heavy traffic, and even parking restrictions make the last mile remarkably time- and energy-consuming. For example, London recently announced the expansion of its ultra-low emission zone, making the deployment of last-mile delivery vehicles even more complicated for logistics companies. On the other hand, in more remote areas, the infrastructure (or lack thereof) as well as a low volume of deliveries often render the logistics excessively inefficient.
E-commerce continues to boom and spread to previously untapped markets, with some conservative estimates noting that total annual e-commerce spending could eclipse $2.7 trillion. Meanwhile, environmental reports become more alarming, and the need for smarter logistics has become more urgent than ever. Carbon dioxide emissions from freight transportation account for 30% of all transportation-related carbon emission from fuel combustion. But eco-friendly last-mile delivery solutions could help to make the logistics industry greener and reduce its carbon footprint. There are innovations powered by Artificial Intelligence (AI) in the areas of route optimization, robotics, and anticipatory shipping that can make real and quantifiable improvements on sustainability in last-mile delivery — while making the process smoother and more cost-effective.
Using AI to Lessen the Environmental Impact of Last-Mile Delivery
Among its many negative consequences, last-mile delivery is a major culprit when it comes to urban air pollution. Delivery vehicles in London, for example, used by companies like Amazon, Royal Mail, DHL, and others have been found to emit 23 times the level of toxins allowed by U.K. law. One can easily see how massive fleets of delivery vehicles, even if divided by neighborhood, can create traffic jams in the busy streets of major cities, simply to meet the demand of delivery recipients. Furthermore, the sheer volume of goods being delivered, if not managed intelligently, can play a significant role in air quality problems and produce unsustainable levels of carbon emissions. However, potential solutions to this problem can be found with the help of AI.
AI is often associated with futuristic dystopias where machines rule over humans. The reality is, in its present form, AI can be described as computer algorithms that can make decisions far more complex than traditional software is capable of handling. There’s no question that it has the power to automate and drive exponentially greater efficiency in a range of applications, including last-mile delivery.
Presently, introducing modern data-driven technologies to logistics has its limitations, by and large for the fact that such data is often messy and incomplete. However, by using Machine Learning and Predictive Analytics, logistics companies can cleanse and enrich the incomplete data. It enables them to manage their business in a more intelligent way, therefore, reaching much higher levels of operational efficiency and improving the bottom line.
One more potential AI-powered use
A great example of such technology was implemented by the Singaporean delivery company SingPost, which has unveiled a new AI-powered logistics platform called Last Mile Platform (or LaMP). SingPost developed LaMP with the help of software planning company LogiNext. LaMP consolidates a number of last-mile delivery services like couriers, brick-and-mortar collection points, and parcel lockers into a single platform – and it’s able to do this regardless of the technology the various courier companies use. In addition to that, LaMP uses AI to automate plot-optimized courier routes based on a number of factors, including package destinations, real-time traffic data, and weather conditions.
There’s also the possibility to optimize deliveries using the shipment data: the type of product or material that’s being delivered, the dimensions of the package, and perhaps even patterns to the timing in which the products are being ordered and requested for delivery. Such data can be collected, cataloged, and visualized to create more efficient last-minute delivery mechanisms, helping to optimize the number of overall trips and creating sustainability in the long term.
For instance, Amazon famously relies on AI to run its ambitious and impressive Prime service, which guarantees two-hour deliveries. One of the innovative approaches that the company uses to fulfill their promise is anticipatory shipping which predicts when, where and which items will be purchased by customers based on the history of buying habits in a particular area. In other words, when Amazon client orders a popular product, it will be sent from a nearby hub in a much shorter timeframe due to its ensured availability there.
However, Amazon’s AI usage goes beyond predicting what goods customers will buy and when. The e-commerce giant also leverages AI to accurately predict how many delivery drivers will be needed at a given time, to determine the number of shipments and the most efficient way to store them in a delivery vehicle. For two-hour deliveries, every moment is precious, and attention to these details – and better yet, addressing them with AI – makes the last mile more sensible and sustainable for Amazon.
Another important area of the last mile which is affected by AI is robotics. There are already a number of notable front-runners in this sector, such as Boxbot, Starship, and Marble that are using small robots to bring a greater level of sustainability to the last-mile delivery process.
Another great example of such a solution is Postmates, a delivery provider for groceries, food, and drinks. The company has recently rolled out a smart delivery robot, called Serve, which was developed in response to the problem of “moving a one-kilo burrito with a two-ton car,” according to Ali Kashani, the company’s VP of robotics. Not only does this innovative approach reduce the carbon footprint of food deliveries (as Serve can carry up to 23 kilograms worth of goods as far as 40 kilometers on a single charge), but the robot is pedestrian-friendly, equipped with a turn signal and specific instructions to yield.
Furthermore, Nuro, a grocery delivery company that just raised nearly $1 billion, sought out to solve the same problem, but with a more heavyweight approach. The company’s battery-powered delivery vehicles can travel up to 40 kilometers per hour with enough space to fit several bags of groceries – but not quite enough room to fit a human driver. Nuro has recently partnered with the grocery chain Kroger to begin making deliveries in the Scottsdale, Arizona-area.
Beyond Sustainability in Last-Mile Delivery
For far too long, last-mile delivery has been dependent on analog systems and delivery vehicles that create a massive carbon footprint. In a time of constant alarming circumstances such as polar vortex, ice-melting, and the worldwide climate change caused by irresponsible carbon footprint, AI-powered solutions – paired with the use of electric vehicles and other carbon-neutral measures – have the power to make last-mile delivery more environmental-friendly, allow us all to breathe more easily and save our planet for the future generations.
There are benefits to adopting smart last-mile delivery solutions that go beyond sustainability as well. Route optimization, fuel savings, and other benefits of innovations in the last mile offer a number of financial benefits for delivery companies. Meanwhile, the delivery recipient has a far greater ability to see the progress of the journey for the packages being delivered to them. This instills a higher degree of trust, which matters when customers have an array of options for sending and receiving an important parcel.