The idea and architecture behind Pacenote.ai

Rallying has always been a passion of mine and, short of competing which remains an out-of-budget pipe dream, I’m always engrossed in this multi-faceted motorsport discipline. Another significant passion of mine is all things technology which consumes a significant part of my life not least because it’s my career. It’s only natural then that I’m often thinking about how my interests and skills can impact my hobbies and I’ve a long held belief that rallying is an area of motorsport that has tremendous scope to foster new technologies such as Machine Learning and Artificial Intelligence.

Being lucky enough to speak to some rally crews confirmed this. I had always assumed preparing for a rally was a process shrouded with exciting and top secret technology but this isn’t the case. From my research, crew still endure a very manual, human intensive process when preparing for a rally. Even at the highest level, manufacturer crews in the World Rally Championship follow an age-old process when reccing stages and creating pace notes which will be used in the competition later.

But if it’s not broken then surely there is no need to fix it? I certainly agree with this sentiment but what if technology could enhance the current process? What if rally crews could utilise state-of-the-art technologies more easily in order to better prepare for events? Rallying is a sport where even the smallest of human error, such as an incorrect pacenote, can have dire consequences. Rallying also involves long events where time is a limiting factor for crews and their preparation. Crews only get to recce the stages a few days before they drive at competitive speeds meaning a very limited amount of hours in which notes can be analyses and checked.

Artificial Intelligence is a technology that can process large amounts of data in a short period of time and create output that can mimic human output with a high degree of accuracy. This means that AI can help solves the two main issues plaguing rally crews at the moment: 1. AI can reduce the amount of time it takes to prepare pace notes for events allowing crews more time to spend on other areas of preparation; and 2. AI can reduce the human error in pace notes giving crews more confidence that they wont suffer a rally-ending crash as a result of an incorrect pacenote.

This is the idea behind Pacenote.ai. Pacenote.ai is a software platform currently being developed to offer rally crews an easy-to-use, fast and accurate tool for rally preparation. Designed to be useful in many ways, it can be used to verify traditionally created pace notes, it can be used in combination with the creation of traditional pace notes or it can be used entirely on its own to generate pace notes.

New technologies are frequently adopted in motorsport. One only has to look at Formula 1 to see some of the latest technologies in use. Rallying has also been a hotbed of technology over its lifetime. However, with top-level rallying currently exiting a period of decline, and grassroots rallying always being budget conscious, in order for new technologies to be widely adopted, they need to be accessible including in terms of cost. Pacenote.ai is no different and aims to provide its technology in a cost effective way to rally crews.