Machine Learning to Improve Deliveries

Machine Learning to Improve Deliveries



A new fleet data collection programme from DPD will help reduce risks for drivers.

The new pilot programme in partnership with Wayve will analyse computer vision and machine learning.



What is the aim of the study?


The study will examine how these technologies could apply to existing delivery fleets. This study aims to improve the safety of urban drivers during their operations. 50 DPD Vans in greater London had data collection devices installed. This will allow Wayve to collect the data from the drivers during their normal day to day operations. The device includes cameras with a 360-degree view of the vehicle. The data is then transmitted through 4G.




Alex Kendall, Wayve CEO said:

“Real-world driving data is fundamental to building the core capabilities of Wayve’s technology and we have built industry-leading expertise in the collection and utilisation of fleet-scale data. Working with DPD is an incredible opportunity to speed up the collection of petabyte-scale datasets.”

DPD drivers covered almost 96% of the UK’s road network in 2018. Drivers travelled over 156 million miles every month. This makes them the perfect guinea pigs in this case study.
Wayve had been developing AI-driven autonomous mobility technology over the past four years. This development has seen serval road tests across UK cities. The developments in projects like these help large-scale operators increase their fleet safety.


Risk manager at DPD UK, Andrew Morgan said:

“We are excited to collaborate with Wayve as we continue to explore the use of cutting-edge technologies to support our insurance and risk teams. Through this pilot, we aim to learn how advanced vision-based technologies can be applied to enhance the safety of our fleet for drivers, and other road users.”


How can we help?

Our Telematic solutions make the safety of your fleet and other drivers a top priority. Using cutting edge technology you can track your fleet in real-time.



Machine Learning to Improve Deliveries