In this in-depth conversation, Mark Preston discusses his career at the forefront of motorsport and mobility innovation. He talks about his engineering roles at Arrows and McLaren. He also discusses founding Super Aguri F1, winning titles in Formula E, and pioneering autonomous vehicle technology at Oxa. The discussion explores leadership, strategy, marginal gains, AI, and building high-performance teams.
Conversation Highlights
In a wide-ranging discussion, Mark reflects on a career defined by pushing the boundaries of engineering, leadership, and innovation. His journey spans from the racetrack to autonomous technology. He began as a simulation and stress engineer in Australia. Later, he moved to the UK to pursue his Formula 1 dream. He eventually worked with Arrows and McLaren. A turning point came when he shifted from pure engineering to business leadership. He founded Super Aguri F1. He later achieved championship success in Formula E with DS Automobiles and now Lola & Yamaha. Throughout, the constant has been a deep commitment to learning, experimentation, and building high-performing teams.
Motorsport is an unparalleled arena for decision-making under pressure. Mark highlights that performance is tested every two weeks. Even small wins, like optimising pit stops or improving team communication, compound into success. Drawing from experience at McLaren, he emphasises the importance of institutional memory. He stresses the need for scientific rigour and structured processes over black art intuition. He also discusses how strategic clarity is critical in racing. Iteration is also vital. Scenario planning helps build resilient, innovative organisations across sectors.
Beyond motorsport, Mark shares insights from his leadership at Oxa. He is applying engineering knowledge to autonomous vehicles in ports and logistics. His focus remains on practical, scalable use cases — leveraging off-highway environments and deep software integration. AI and machine learning reshape both racing and autonomy. Mark combines technical depth with organizational clarity in his approach. He continually strives to stay on the “bleeding edge” where no one has the answers — yet.
To keep up with my latest work in motorsport, autonomous vehicles, and innovation, connect with me on LinkedIn or explore more projects at www.MarkAndrewPreston.com.
Move the Ball: Mark Preston, Pushing the Boundaries in Motorsports and Beyond.
Mark Preston’s illustrious career in motorsports is a testament to his passion, innovation, and leadership. From his early beginnings in Australia, where he developed a love for cars while working on a farm, to his groundbreaking achievements in Formula 1 with Arrows Grand Prix and McLaren, Preston has consistently pushed the boundaries of engineering and technology.
His entrepreneurial spirit led to the rapid establishment of the Super Aguri Formula 1 team, built from scratch in just 100 days. Transitioning to Formula E, Preston played a pivotal role in its inception, leading Team Aguri and DS TECHEETAH to multiple championships. Now, as the Motorsport Director at Lola Cars, he continues to drive innovation with a focus on sustainability, underscored by a new partnership with Yamaha for Formula E.
Mark Preston’s journey is a remarkable blend of technical expertise and visionary leadership, making him a significant figure in the evolution of motorsports.
In 1999, during my tenure as Head of R&D at Arrows Grand Prix, I embarked on a journey to enhance the performance of our F1 cars. At that juncture, genetic algorithms emerged as the preferred tool, particularly in fast trading software. Despite operating on Silicon Graphics visual workstations, which were relatively powerful but nothing like what is available nowadays, we could conduct many runs. We employed these algorithms primarily to analyse tyre models and seek other optimisation strategies. Interestingly, the learning often highlighted inaccuracies within our models. For instance, a particular simulation model would consistently suggest a 100% front weight on the car, indicating an error in the model that may have caught out a few teams over the years with unrealistic targets! These were the early days of using computers with limited power and brute force algorithms.
When I moved to McLaren F1, I was astounded by the wealth of “embedded knowledge” the team possessed, a term used in MBA circles to mean that they’ve meticulously documented everything. To make this vast reservoir of knowledge more easily accessible to new engineers, I considered implementing an “on-prem” Google server. The idea was that little nuggets of wisdom only known to a few people could be shared across the company. The idea is that knowledge, when harnessed collaboratively, can be greater than the sum of its parts. Now, imagine if we could enhance the learning model of ChatGPT by incorporating this internal knowledge derived from over three decades of racing expertise into speeding up the dissemination of knowledge and ideas (the first version of this article was prepared in May 2023, MS Co-Pilot and Google’s Bard are solving precisely this at the moment).
Fast forward to the Super Aguri F1 team. Our radios were not at the level of the other teams, so we decided to experiment with increasing the quality of our communication with the drivers. We agreed that one solution was to move the pitwall engineering (prat perch) to the air-conditioned, quiet, controlled environment of the engineering truck behind the pits. This increased the communication quality and was a precursor to thinking more about the now standard “Mission Controls” back at base in F1 and FE, where engineers can work in a quieter controlled environment. This decoupling of tasks is a powerful concept. Obviously, “you can’t hammer a nail over the internet,” so specific tasks need to stay on the ground, at the track, but many jobs can be done remotely.
The result was the now famous run in between Anthony Davidson and a beaver while running 3rd at the Montreal Grand Prix in 2007. With engineers positioned in the truck behind the pit garages and Anthony having to dive into the pits at the last minute, the mechanics were left surprised as the TV talked about him coming into the pitlane! An example of the right intent, but not the right outcome!
Another solution to our communication problem was to think about texting. I saw the Technical Director of F1, Charlie Whiting, in Monaco on the morning of the F1 race to discuss solutions. Car communications are restricted to radio, but I argued that if our driver had had a hearing impairment, that would not be entirely fair, hence the need for text-based communications. Charlie agreed to look at a proposal. We never did implement the concept due to the requirement to redesign the steering wheel, but I have continued to think about communications and ideas that might solve problems.
Since I started looking at genetic algorithms in 1999, rapid advances in computing power, including GPUs and TPUs, enabled machine learning to evolve significantly. This computational growth allowed for training complex models on large datasets, leading to powerful AI like GPT-3 and GPT-4 and ushering in a new era of AI innovation. The astonishing rise of ChatGPT and large language models or LLMs is the latest thing and is changing by the week, if not the day at the moment (this article will be out of date by the time you read it potentially, first written May 2023!).
Could the LLM be trained on a smaller data set and more clearly communicate with a driver? My current understanding of these LLMs is that the better “prompt engineering” fed into the model, with the best context, the better the answers and the more concise the results. If you notice that when you type in a question to Bing now, it first makes the prompt more straightforward, then feeds it to the model. The more you narrow down the context, the better the answer. Here’s a simple example: Me on the prompt line: “Please write a concise radio communication for an F1 driver with bad radio quality to ask them to come into the pit lane for new tyres.”
A silly, small example, but it shows how it can be used. I have seen many times in the heat of battle where we engineers make mistakes. The more scenario planning and fast decision-making possible, the fewer mistakes. For example, ChatGPT could prepare radio communications and pop-up ideas for a race engineer based on preconceived knowledge from listening to “Mission Control” conversations or info coming from the TV!
These are only simple examples, and every day, I am sure you will all think of more. And by the time this article comes out, more API integrations, private learning model implementation and a host of tools have become available. I will watch with interest how this all begins to play out and would love to hear any ideas from engineers!
PS: this article was written with the aid of ChatGPT4
Wow, what a weekend! Amlin Aguri’s first win in the FIA’s first fully electric championship! It is an amazing feeling to get a result after all the work put in by the team over the last three years.
“Luck is when opportunity meets preparation.”
Plus it takes a lot of work to start a new team in a completely new championship – but it’s worth it when all the effort is rewarded! Many people have asked what we did to get to the front, what has changed, how did we do it?
The build up to the race win really started after all of our troubles in Punta del Este.
The series test, on the Sunday after the Punta race, was the first time that Antonio (Felix de Costa) and Salvador (Duran) really had a chance to test the car after Antonio had missed much of the pre-season testing and the first race in Beijing with BMW DTM duties. This, coupled with the fact that race weekends are so short which restricts running, means that when you haven’t got the car in the “zone” it is extremely difficult to do anything meaningful with regard to setup or finding solutions.
Our race pace has been quick from the beginning with Takuma setting the fastest lap in Beijing. So what we were looking for was time to get a proper qualifying setup and thereby increase our race pace accordingly. You must remember that if we hadn’t had an issue during the pit stop in Malaysia, then Antonio could have finished in the top five and potentially on the podium. The engineers worked over the break between Beijing and Putrajaya and then over Christmas before Punta to get our models and understanding of the car to a point that we could validate this understanding during the Punta test. The result was a fastest first sector on the final run of the day before a Red Flag which showed that we were going in the right direction for the next race in Buenos Aires.
Antonio arrived in BA with a quietly confident attitude focussed on making the best of our great Punta test and determined to have a great weekend: everyone arriving on a high and following through is a good indicator of the picture of the weekend.
So how did the weekend go? Well in Free Practice 1 the car was quick straight of the box. There was good work carried out during the session, getting everything done that was on the plan; another good step. Some cars were running maximum qualifying power; hence the large gap at the front of the pack but P9 was respectable, showing of potential to come.
Then in FP2, it was maximum at- tack, our final preparation before qualifying and we were immediately quick with our final position of P3 only 0.4s off the leader which showed that our ultimate potential for qualifying and race performance was within reach.
Qualifying is always a lottery. Antonio drew Q1 while Salvador was in Q3. The elusive Q4 without red or yellow flags is the name of the game with a rubbered-in track and potentially better track temperatures, but we made the most of the quicker car and got ourselves in the top 10. Antonio felt it was better to aim for a top 10 position and wait to see how things went in the race instead of necessarily going for pole and having a problem. Starting P7, 0.5s from pole position showed again that we were in the right place for the race.
The race was quite chaotic, but Antonio and Salvador drove sensibly, both overtaking a number of drivers and making the best of battles going on around them. As the race went on we had a great pit stop which resulted in gaining positions for Antonio and a safety car which caused some confusion with everyone waiting for the screens to update with the final order to be clear.
As we moved up the leader board it became more and more stressful for everyone in the garage as there was more to lose with each increment Antonio gained! By the time he was in a podium position, the tension was showing on everyone’s faces! And as each problem happened on track we were increasingly on the edge of our seats! Salvador was also making up places and looked like he would get into the points as well.
At that stage we could see that Antonio had plenty of battery life left over and
he was therefore in a great position to push all the way to the end of the race and catch Nick Heidfeld before the chequered flag. When the drive-through came for Nick we almost couldn’t believe it, we just had to hold our breath and bite our nails till the end of the race.
Some people might say that there was some luck involved, but you can bring up many old adages about finishing first that you must first finish, and that goes for every element of the car, our team work, the car setup, the drivers’ management of the car’s batteries, the control systems, our pit stop practice and also how the other teams run their cars. Every part of a team is important and we have proven in previous races that we too could have technical problems such as electronic control systems with Takuma at the first race and pit stop problems that cause issues.
Were we lucky?
Luck is when opportunity meets preparation,and we certainly had the pace to take the opportunities delivered to us over the weekend.
Whats next? Miami, where we should make some improvement on all aspects of the team operation, the car setup, our race strategy and some driver training. We have the pace and now it is a matter of building on success and doing a better job at each race and chipping away at the championship points to move ourselves up the grid. After all we love a challenge; otherwise we wouldn’t have entered such a unique and brand new championship!
Following my last column I have been very interested in the questions that we are being asked in our pre-race press conferences, especially at Buenos Aires where they are big fans of motorsport. One of the most common topics was, ‘how will the technology find its way into the world?’ The best example I could see was the bus rapid transit system they have in the city which is a great example of where electric drive, regenerative systems and wireless charging will find its way quickly into practical everyday applications.
You should remember that Uruguay generates 45% of their electricity from hydro
with a target of 90% in 2015 coming from renewables. The intermittent nature of some renewables will benefit from the “Energy Cloud” that will be created when more electric vehicles connect to the network and allow off line storage in the night for solar and during low wind conditions for wind.
Reprinted from Mark Preston’s column Racing to the Future in Motorsport Monday
Launch photos for Super Aguri Formula E team in Tokyo.
It is good to be back in the forefront of motorsports with the Super Aguri team again. We are very much looking forward to the challenges that Formula E is going to throw at us. Being at the forefront of motorsports technology and developing the technology of the future is exciting. We believe that there will be a disruptive change that comes in the automotive industry through all of the different technologies coming together to create Mobility as a Service. Smart phones, urbanisation, congestion and pollution are but some of the drivers.
