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AV matchmaking: Finding the right technology to fit your autonomous vehicle project

July 23, 2021

Traditional tech acquisition models won’t work for AVs, but here’s an approach that will

Evaluating autonomous vehicles (AV)—or really any new and emerging transportation technology—can be overwhelming. There’s so much to consider. From use cases to vendors to connections with existing infrastructure, it’s no wonder agencies and companies across the world have released hundreds of Requests for Information (RFIs) over the last five years, hoping to gain some clarity and direction to help them move forward. It may not be quite the same as choosing a life partner, but it is a decision that will be with you for a very long time!

The old ways of gathering information to make procurement decisions worked fine for decades. But the AV industry is extremely dynamic and would-be system owners need a process that can keep up. The GenerationAV team keeps a close eye on industry players, mergers, and launches. And we’re currently looking at 36 AV trucking and delivery companies, and 107 passenger AV companies—that’s a lot to keep track of! Compare that to the transit bus landscape, which is comprised of 36 total manufacturers (four of which produced 68% of all transit buses in 2013 according to Mineta Transportation Institute), and it’s clear that the AV industry is far more difficult to navigate.

Information that will help guide procurement includes vehicle specifications and capabilities, current deployment information, safety and policy reviews, real-time public sentiment analysis, and especially, insight from subject matter experts. This is critical knowledge for acquiring the right AV, and then operating and maintaining AV service. By taking a different approach from the traditional RFI process and user surveys, we can get to a level of transparency that helps accelerate AV deployment.

Evaluating your unique needs

One of the most common missteps we’ve seen during this time is jumping right into vehicle evaluation before understanding what challenge or problem is being addressed. People want to know vehicle capabilities, availability, specifications, and prices. All of that is really important, but is it the most important first step?

It’s not, because to truly find the right fit, you need to understand what your needs are and identify the challenge you’re addressing. Are you trying to add first-mile/last-mile connections? Extend service hours and improve service flexibility? Improve transit accessibility for citizens with mobility issues?

Only once you truly understand your needs can you develop a vision, which is a critical step in developing a right-fit solution.

Setting your vision (with the community)

Your vision will be influenced by several factors: Your AV readiness and strategic goals, federal and local policy, and stakeholder and community needs. There are many reasons to start with creating a vision, such as enabling long-term planning, building a stronger business case, and supporting the voice of the community. Take the opportunity to talk with your stakeholders and community members. Let their needs form the basis of your project requirements. Expose them to potential solutions by setting up technology demonstrations, workshops, working groups, and more. There are plenty of creative ways to engage, connect, and set goals.

Once your vision is set, you can then develop and test a concept to confirm its feasibility and compatibility with your vision. With a project champion and strong stakeholder support, you can further develop your conceptual use-case by conducting site and route assessments to plan for AV integration with existing infrastructure and systems. Other activities that will set your project up for success include interviewing potential users and documenting feedback; estimating capital and operations budgets to seek funding; ensuring you can meet regulatory and policy requirements; and, of course, a safety assessment. 

By taking a different approach from the traditional RFI process and user surveys, we can get to a level of transparency that helps accelerate AV deployment.

Safety is fundamental. No autonomous vehicle of any shape, size, or function, should ever be deployed without conducting a thorough and holistic safety assessment. This includes evaluating the Operational Design Domain (ODD)—essentially the environment in which the AV is operating—to document the requirements and specifications that a vehicle vendor or operator must meet.

Evaluating the ODD was exactly where we started when a business improvement district and transit agency recently asked us to provide a tech evaluation for their project concept—a passenger AV service that extends the reach of high-capacity transit. We looked at the physical environment to help define the type of technology that could be successful operating there. This led us to recommend a multi-platform solution: One vehicle type for their high-capacity use-case and another for their on-demand use-case. In the end, we were able to recommend a set of solutions that met their most important needs and allowed them to move onto their fundraising stage.

This practice of creating your vision and assessing concept feasibility and safety is the most efficient way to begin evaluating AV technology and finding the right fit. There’s still a lot to do to find that ideal match, but it’s like online dating—if you don’t set up your profile honestly based on what you’re looking for, you’re going to be disappointed. 

Build your AV acquisition approach (with the help of a matchmaker)

As mentioned earlier, acquiring an AV is vastly different from acquiring a traditional transit vehicle, largely because of the quickly evolving technology landscape and the significant number of options available. The most common misstep we’ve seen is to start the acquisition process by soliciting information from potential vendors. An organization will spend time and money to develop an RFI or RFQ, publish it, and wait patiently for responses of varying quality. Responses in this case often end up being a fairly generic marketing report that mostly contains publicly available information. The organization would then spend time evaluating these responses, following up with questions and interviews to get one step closer to publishing an RFP.

The worst part about this time-consuming process is that there is no verification built-in, and no objective third-party ensuring the information is reliable and accurate. The information can also be limited in scope and won’t contain critical data points like deployment details and public sentiment. The latter can be especially hard to assess without aggregation and analysis tools. And not much of the information is easy to compare, requiring ad hoc interpretation and settling for apples to oranges comparisons in some cases.

To help address this challenge, we’ve developed a single platform supported by industry expertise that provides agencies and companies with the information they’re looking for more efficiently and with a level of trust that didn’t exist before. Having that level of detailed information upfront makes the acquisition journey more cost and time efficient and produces better results.

Recently, our team was able to help a confidential mining client skip the entire RFI process. The industry analytics platform we created provided all necessary details and product specifications to thoroughly assess AV equipment options for a complete capital and operating expenditure analysis. The client went from project concept through feasibility and is now set up for procurement. Again, without going through a time-consuming RFI process.

We’ve established that evaluating and planning for the adoption of emerging technologies is difficult. But when it comes to automated vehicles, it doesn’t have to be. Following a systematic and efficient process can provide the clarity required to make AV planning, procurement, and deployment decisions. Couple that with a true apples to apples comparison when it comes to technology selection, and your matchmaking tools are ready.

In the end it’s a pretty simple equation: Better data supported by a good process produces better outcomes.

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