Our all-member meetings are a fantastic opportunity to reawaken our sense of purpose. No matter how busy they are, no matter the complexity of the challenges they face during their daily work, our members make time to stop, consider our rapidly-changing world, and think about what we can do to make a positive impact on the future.

Since our last all-member meeting, things have definitely changed. Organizations have dusted themselves off after the main impacts of COVID, and generative AI tools have taken to collective consciousness by storm. Any scroll through a news site will reveal an almost bewildering array of new circumstances.

To help focus our discussions, we began our recent meeting with an analysis of the edge computing market. Tim Hatt, head of research and consulting at GSMA Intelligence, walked us through the current adoption of the technologies that affect edge infrastructure realization, with a focus on how to achieve ROI.

From there, we dove into two of the most important topics that we face as a society: how to achieve sustainability and how we work with AI. Most importantly, we discussed how we, as the AECC, can meet the demands of the marketplace in ways that ultimately benefit our society.

The Future of Sustainable Mobility

To take advantage of the collective expertise and intelligence of the group, we used a digital whiteboard tool — Miro — to engage in a brainstorming session. We kicked off the session with a vote on which sub-topics to delve into. The membership chose:

1. Energy-efficient green mobility systems
2. Improving the vehicle lifetime
3. Electrification of vehicles

From there, the members used digital “sticky notes” to add talking points to the boards for each topic, while Lei Zhong of Toyota and Mikael Klein of Ericsson led the group through discussions of key points. The boards will be kept, added to, and brought into working groups for development. Here are just a couple of the sustainability-related ideas that we covered.

Making Optimizations That Become Significant at Scale

Because transportation consumes so much energy, any improvements will add up to better sustainability. Appropriate use of big data and AI will be vital in measuring vehicle use, understanding patterns, and enabling all kinds of improvements. These improvements could focus on individual vehicles, cloud networking infrastructure, and even track parts through the supply chain.

In terms of helping drivers, alerts for maintenance (which enable better fuel efficiency) could be based on real vehicle data instead of on a generic predetermined schedule. Other systems could be used to help drivers improve their behavior, including teaching them that driving faster (which uses more fuel) doesn’t help them when there are red lights everywhere. Tracking a vehicle’s carbon footprint accurately could also help drivers make better decisions about vehicle use.

Helping Drivers Optimize Battery Recharging Times

For electric vehicle drivers, the need to recharge the battery is an ongoing challenge. This need is also a big concern for drivers who might otherwise consider switching from fossil fuel to electric power.

Connected vehicle systems could help both groups by showing that timing a recharge doesn’t have to be a big worry. A system could take into account the power level of the battery, the driver’s location, the location of possible recharging stations, how busy they are, how fast they can recharge the battery, and even what amenities are available while the driver waits.

AI Has Made It to the Masses — Now What

Roger Berg of DENSO led the group through a discussion of the new generative AI applications and kept things lively with his great sense of humor.

These are a few of the points that emerged:

• It’s easy to imagine exciting use cases for AI, up to and including voice-activated driving assistants, like AI could help realize our goals of smart cars and smart cities.
• Making the most effective use of AI means understanding its strengths and limitations — even if these are changing over time. Currently, AI isn’t great at generating new insights, but it is great at parsing large amounts of data to find patterns and anomalies. The immediate applications of these capabilities lie in security and finding things like available parking spaces.
• There are a number of ways we can use data and AI while still preserving privacy. For example, data could be connected to a vehicle, while the owner of the vehicle remains anonymous. The challenge will be to find an approach that works in different regions of the globe, which have different attitudes to data privacy.
• There are all kinds of interesting applications for the combination of edge computing and AI. For example, if one vehicle detected an obstacle the information could be quickly communicated to the other vehicles in the area.
• One challenge with AI is that training a model is expensive and can introduce problems if the dataset is too narrow or biased in some way. Federated learning, in which models have trained on multiple independent datasets, will become more important to overcome this. In terms of connected cars, federated learning would mean models are trained on many cars and hundreds of thousands of rides. With this type of training, a model wouldn’t just be learning from your driving habits, but from the habits of many others as they work through a variety of scenarios. The same model, once mature, could be added to every car that comes off the manufacturing line.
• Ownership of data is one question that will need to be worked through. It will have important ramifications for insurance and legal issues if there is an accident. Authentication of data will also be critical — as we’ve seen from the variety of deepfake examples, there needs to be a way to prove that data is real.

The role of the AECC should be to continue to lead the way by showing how these tools can be used well. For that reason, we’ll be continuing to engage in our proof of concept program.

Become a Part of the Conversation

The AECC is driving the future of the connected vehicle industry. Our members are developing the network architectures and computing infrastructure required to enable big data and connected vehicle services on a global scale.

If your organization is a vehicle manufacturer, MNO, data and analytics company, cloud provider, parts manufacturer, or in a related industry, you need to be a part of these conversations.

To learn more about AECC membership, visit our membership page or get in touch. And don’t forget to follow the AECC on LinkedIn and Twitter for our latest updates.