3 min

New Technology, New Challenges: Navigating the CAV Landscape

Connected and automated vehicles (CAVs) are moving toward the mainstream. According to research firm McKinsey, the CAV market could be worth $150-$225 billion by 2030, and double that by 2035 as future AI tech evolves to meet consumer demand.


21 Nov, 2023

But new technology comes with new challenges vehicle manufacturers must overcome to make industry inroads. Here's a look at some of the biggest benefits offered by CAVs, some of their top challenges, and how companies can navigate the changing vehicle landscape more effectively.

On the Road Again? Three Benefits of CAVs

The adoption of CAVs at scale offers four benefits for drivers and manufacturers alike.


Vehicles are rapidly becoming intelligent machines capable of connecting with digital infrastructure, other cars on the road, and even pedestrians to help reduce the risk of accidents, improve safety, and enhance overall efficiency.

Automated Driving

Automation looks to reduce human error and improve traffic flow. Ranked on a six-level scale, with Level 0 being no automaton and Level 5 being fully automated, manufacturers have begun to roll out automated vehicles thanks to the emergence of standards such as the UN R157 ALKS regulation. For example, OEMs such as Tesla now produce L2+ vehicles, while shuttle manufacturers such as NAVYA have deployed L4 CAVs.

Artificial Intelligence (AI)

AI is about pattern recognition. These tools may be used for the detection of available cargo space in trucks, to suggest driver resting periods, or to take partial control of the vehicle if drivers are distracted. There are also companies that are using AI to help drivers identify bad habits and make changes to improve their safety or for the final inspections of tires to detect small deviations which are often extremely difficult to see with the human eye.

As noted by research from Stanford University, however, while AI algorithms are improving, significant work remains before they're ready to take more than cursory control of vehicles.

Challenges in Connected Vehicle Adoption

CAVs also come with potential challenges.

First is ensuring connected vehicle technology is robust enough to handle all weather conditions and is capable of either maintaining network connections under sub-optimal circumstances or using on-board systems to remain operational during network outages. There's also a growing need to ensure standardization across common CAV components to enable interoperability.

Next on the list is regulation. This becomes a key concern as vehicle autonomy increases. What happens if the vehicle is involved in a crash? Are the owners liable? The creator of the AI solution? The vehicle manufacturer?

There's also a need for ethical handling of vehicle data. While this data is critical to ensure continued operation, it poses potential liability risks if compromised.

Finally, companies need to consider business challenges such as ethical and economic implications. From an ethical standpoint, this means accounting for the environmental impact of vehicle creation and operation. From an economic perspective, companies must conduct complete cost-benefit analyses to ensure profitability.

Pillars of Progress: Finding the Balance

Four pillars are essential in the widespread adoption of CAVs. The first three are the same as the challenges listed above: If companies can address technology, regulatory, and business concerns, they can pave the way for increased vehicle uptake.

In practice, this requires balance, which is informed by the final pillar: User need. No matter how safe, secure, and cost-effective CAVs are, they won't see broad adoption until they address user needs.

The biggest need? Safety. According to McKinsey data, 64% of drivers surveyed said increased safety would boost their confidence in CAVs. Consider navigation. While HD maps and environmental models provide the foundation for effective navigation, manufacturers must go a step further with the implementation of AI and AR solutions capable of combining map accuracy with real-time route planning and AI object identification.

When it comes to CAV adoption, it's about when, not if. Given the increasing interest in CAVs, companies that can deliver safe and reliable AI-driven vehicles will gain a significant market advantage.

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