Aarjav Trivedi, CEO, and founder, Ridecell, recently joined Grayson Brulte on The Road To Autonomy Podcast to discuss how digitalization and automation of fleets lead to increased revenue and profitability for logistics and mobility companies.
In the last of our 3rd- part series, Aarjav discusses what the future of fleet management looks like and autonomous business models.
GB: In your 2017 Auro Acquisition press release, you say that ‘the Auro acquisition and the launch of our autonomous operations platforms represent the next phase of our strategy to provide a complete autonomous solution for Ridecell customers.’ What is the complete autonomy solution?
AT: Today, each vehicle, whether it’s a Penske truck or an Uber car, comes with a free human being inside. They go out and pump fuel or charge the vehicle, and if someone spills popcorn all over the floor, they clean it.
So, the moment you take the person out, while it’s great that the vehicle is driving itself, someone’s got to decide on what to do if someone spills popcorn all over the autonomous car? How’s that going to work? Well, it’s going to be a camera that sees that something is wrong. But the system or some algorithm needs to decide, ‘do I need to send it 15 miles away for deep cleaning?’ or ‘can I probably just send it to the neighborhood carwash?’
And that level of automation is key. What we mean by autonomous operations is the ability to make all of the operational decisions around your fleet, both driven and autonomous, without involving a human being. And to be able to do it for a fleet of autonomous vehicles. This is what we have been working on for the past several years. And, and I think, the time is now where most fleets that are high utilization cannot scale further without this.
GB: What new trends are you going to stay ahead of?
AT: The explosion of survey data. Data coming out of the vehicle is not being used right now. And I think one of the new trends that I see is how the world will need to take advantage of this. Autonomous is absolutely where we should be aiming, but even just to be able to say, ‘how can I help this person drive this vehicle more safely?’
One of the challenges in improving the algorithms is there’s so much sensor data. So whether it’s data from telematics about tires and tail lights or data from ADAS systems and LIDAR about how someone is driving, all of this data ends up on a hard disk or in a data center. A human being needs to go through it with a great amount of time and trouble to make sense of it.
And one of the things that I think will happen is extending our data automation platform to these sensors, where we can identify these scenarios and enable them to be actionable automatically. So you don’t have to go through hours and hours of LIDAR and video data to find interesting scenarios. What is happening now is we finally have the ability as an ecosystem. And now, thanks to COVID-19, we can use all this data and create value out of it for ourselves in the world. And I think several trends are going to stem from this, this evolution.
GB: What is your take on the future of autonomous business models? Do you think that we’ve achieved a profitable model yet? Are these companies still going to have to find their path to profitability?
AT: No, I think it’s going to be a grind. I do believe the economies of scale are beginning to work. But what it has done is made it possible now to create much cheaper LIDAR potentially. You’re going to see costs come down right now, in a meaningful way for many of these components. Also, in adapting some of these components like LIDAR for non-L4 and L5 use cases, we have created more economies of scale. So, I do see consistent progress. I appreciate the low-key, keep your head down and make progress on the approach that the companies are taking now, with Waymo leading the way. I think that is the path forward. Use cases around logistics have several things going for them; revenue per vehicle is much higher. In some sense, particularly driving on the freeway, the problem is much easier. Specialized use cases like Gatik have an edge. I also think L5 is a long way ahead, and L4 has a hard path ahead of us.
GB: Is the key for companies like to scale fleet optimization?
AT: I think it’s broader than that. The key is to integrate the ecosystem. One of the key learnings for us was that it takes so many partners and entities–Tier 1 suppliers, OEMs, telematics providers, cleaning vendors, CRM platforms, insurance providers, etc.–to make a trip profitable. It is shocking that the digital connections between these systems have not existed. So the broader meaning of fleet optimization is ecosystem optimization. The core problem is not to let the data live in silos, so decisions are made inefficiently. You have to be able to connect the data from multiple sources. The magic of a profitable trip is taking data from 17 different places, automating decisions based on that data, and then sending orchestration decisions back to the 17 different places.
I’m excited because what I see now, that I didn’t see a couple of years ago, is this alignment, a sense of urgency in all parts of the ecosystem.
We have this unique opportunity in the world right now, where a crisis has created the alignment that we need to create fleets and mobility businesses that are not only profitable, but they are also sustainable. If we can align the ecosystems and the decisions, we will end up with a far better world for our children. We are helping the world move better, and not only is it more comfortable, but it’s also sustainable.
If you missed the rest of this conversation with Aarjav and Grayson, check out parts one and two.
To learn more about how we can help automate your fleet management, contact us today.
Author: Diptii Tiiku, Senior Director of Marketing, Ridecell