We’re delighted to share that our project proposal “Towards greener last-mile operations: Supporting cargo-bike logistics through optimised routing of multi-modal urban delivery fleets” for the Climate Change AI innovation grant was successful!
We will work as a supporting industry partner with an incredible team of academic researchers, namely Dr. Maria Astefanoaei (ITU), Dr. Akash Srivastava (MIT-IBM) and Dr. Kai Xu (University of Edinburgh). We look forward to working alongside pioneering cycle-logistics partners, and bring academic research and industry together!
We’re especially pleased as this was a very competitive programme, with less than 7% of submitted proposals being accepted.
A list of the different funded projects can be found here.
In 2019, the organisation Climate Change AI (CCAI) published a 100-page research paper entitled Tackling Climate Change with Machine Learning, co-authored by some of the leading AI researchers in the world.
The innovation grant programme is the first of its kind, focusing on supporting research at the intersection of machine learning and climate change.
“We need a wider variety of tools and approaches to accelerate on-the-ground action, like existing work in renewables integration and sustainable agriculture,” Priya Donti, co-chair of Climate Change AI, says. “At Climate Change AI, we seek to catalyse and accelerate this work by supporting members of the AI and climate action communities to deploy machine learning where it can make an impact.”
Cycle-logistics as a sustainable solution to urban transport has not been a focus of the machine learning community, where very often solutions such as autonomous vehicles, delivery drones and robots get most attention and funding, despite their uncertain feasibility and impact.
Transport experts estimate that cycle-logistics could competitively substitute 25-50% of urban freight [1,2,3]. Today the figure is closer to 0.1%, but is gaining increasing attention from the logistics industry, and is being pioneered by a number of smaller logistics operators.
Cargo-bikes are a multi-solution on the path to sustainable and humane cities.
They directly cut pollution, decongest cities, emit a tenth of the CO2 emitted by an electric van, and take much less space on the roads, all this while moving significantly faster in dense urban areas.
A significant uptick in cycle logistics would also make cycling as a means of regular transport much safer and thus encourage people moving away from cars through 1) removing vans from the roads, 2) commercial incentives for cycling infrastructure and 3) a phenomenon known as ”safety in numbers” (the more people cycle, the safer it is, thus the more people cycle).
In cities, 50% of car trips are shorter than a 20min cycle.
To learn more about the project, you can find our proposal abstract below:
Light goods vehicles (LGV) used extensively in the last mile of delivery are one of the leading polluters in cities. Recently, cargo bike logistics has been put forward as a competitive, zero-emission candidate for replacing LGVs in urban areas, with experts estimating 25-50% of van deliveries being replaceable by cargo bikes. Due to their faster speeds, shorter parking times and more efficient routes across cities, they can out-compete traditional van logistics when operated effectively.
Despite this competitive advantages in dense urban areas, their widespread adoption by logistics operator is limited. This is primarily due to the lack of inexpensive ways of accurately evaluating their impact on the cost of business.
To this end, we aim to develop data-driven tools to allow for high-fidelity simulation of hybrid (vans+cargo-bikes) fleet-operation under real-world settings. Our simulator will enable key stakeholders to run feasibility studies towards optimising and diversifying their fleet composition in a cost-effective manner.
During the project, we will collaborate with innovative cargo-bike logistics businesses, and we look forward to saying more in the near future.
If you’re interested in related problems, either from an academic or an industry perspective, please shoot us a message - we’d love to chat!