There was widespread speculation that by 2019, major cities of the advanced world will witness wide-scale deployment of autonomous vehicles. Hence, investment picked up, accumulating as high as $80 billion by 2020. However, so far, such an expectation has ended in disappointment. But hope has not entirely evaporated. According to an article in The Economist, April 2023, autonomous vehicles are coming but slow. Perhaps, they are not caught in Death Valley.
It seems that autonomous vehicles have been caught in the Chasm, as articulated by Geoffrey Moore in his book—Crossing the Chasm. Why have they ended up in the chasm? What is its nature, and how to overcome it, if possible? Why cannot it keep steadily diffusing deeper in society like the way the Rogers theorized Innovation diffusion pattern? Do all other innovations with a radical potential of unleashing creative destruction face a similar fate? Besides, why did we witness a spike in expectations, investment, and media reporting about the imminent arrival of autonomous vehicles?
Rise of Autonomous Vehicles as Reinvention Wave
Autonomous vehicles refer to human-free driving or driverless cars. People also call them robocars, self-driving vehicles, driverless taxis, and cars that drive themselves. Autonomous vehicles got the initial importance due to the option of sharing cars with family members and friends. Initial experimentation started in the 1920s with buried magnetic strips as guidance. However, despite the demonstration, it could not pick up adequate momentum.
In the 1980s, the US military started investigating autonomous vehicle technology to make driverless armored vehicles, tanks, and infantry fighting vehicles. The objective of making moving war machines autonomous is to reduce the exposure of military personnel to enemy attack. The work done at the Robotics Institute of Carnegie Mellon University and other laboratories led to the creation of a reinvention wave of autonomous vehicle driving—by replacing human drivers from the loop with technology.
Subsequent progress led to the belief that autonomous vehicle technology could reach maturity for making civilian vehicles also self-driving. It was envisioned that autonomous vehicles would be able to address the natural limitation of human driving—like 700ms latency in responding to unpredictable situations. As a result, autonomous cars will reduce road accidents, increase highway throughput, and improve vehicle sharing or utilization. Hence, based on the likely economic gain and technology possibilities, expectations about the future of profiting from autonomous vehicles emerged. Consequentially, investment, media activities, Startups, mergers, acquisitions, spin-offs, and R&D portfolios spiked, followed by a plunge, forming a typical hype cycle.
Customer Purposes and Autonomous Driving Technology Core Maturity Affecting Diffusion
Experimental autonomous vehicles under human supervision have been plying the street for quite a while. Besides, the military turned many of their war vehicles into autonomies. However, why are they not being adopted by the majority? Why have not ordinary civilians been giving up their driving role to machines to enjoy all kinds of possible benefits?
Innovation diffusion refers to the adoption of innovation by different categories of customers. Unlike innovation as a static public good, technological innovations have an S-curve-like dynamic life cycle. Both the performance and cost of innovations keep changing along the life cycle. Furthermore, not all categories of target customers have the same purpose to meet in the same situation. Hence, the technological innovation diffusion pattern varies from the one presented by Mr. Rogers in the 1960s.
Like all other innovations, autonomous vehicles began the journey in a primitive, costly form. Due to unique requirements, the military found that primitive solution was far better than physically exposing soldiers to the battlefield. Hence, the military market started half-baked adopting autonomous vehicles to serve urban warfare. Those driverless military vehicles are not as efficient and safe as human-driven ones. But they are a far better alternative. Hence, like many other significant innovations like computers, digital cameras, and mobile phones, the military market emerged as an innovator segment for autonomous vehicles.
The rising popularity of e-commerce found autonomous mobile platforms in structured warehouses a suitable alternative to human-driven vehicles for moving products. Hence, e-commerce companies became early adopters of the civilian market.
However, autonomous vehicles should have further capability enhancement to make them suitable for serving purposes of subsequent customer segments such as elderly and parcel delivery. To penetrate other market segments like early majority, late majority, and laggards, autonomous vehicles must advance further.
Autonomous Vehicles Get Caught into Chasm
In 1991, Geoffrey Moore’s book Crossing the Chasm: Marketing and Selling High-tech Products to Mainstream Customers brought a new insight into the diffusion pattern of technological innovation. He presented a modified version of Rogers’ innovation diffusion theory by placing a gap or Chasm between the early adopters and the early majority of the target customer groups. It was justified it by referring to traits of customers like enthusiasts, visionaries, and pragmatists. He mentioned pragmatists value proven material benefits far more than the other two groups. Hence, they wait for data about the benefits of innovation from previous users.
Both Rogers and Geoffrey perceived innovation as a static thing. They looked upon social and personal traits to explain the time-dependent adoption of innovation by different groups of customers. Unfortunately, such attempts of theorizing innovation diffusion failed to consider varying requirements and economic value from usages and dynamic aspects of technology life cycle.
The underlying factors of the adoption of autonomous vehicles by the innovator segment, the military in this case, is not because the military market was far more receptive than civilians to new ideas. Instead, due to justifiable economic value distilled from meeting war field movement requirements, which are different from civilian mobility necessity, the military found half-backed autonomous vehicle innovation attractive; besides, as structured warehouse environment is suitable for early-stage autonomous vehicle operation, this market segment responded early.
Emergence of Chasm due to autonomous vehicle technology barrier
However, the military’s autonomous vehicle technology is not sufficiently strong enough to offer needed performance, such as collisions, by the civilian market. Similarly, despite the success of the safe operation in structured environments of warehouses, the autonomous vehicle technology core faces challenges in offering safe mobility in unstructured outdoor environments. Hence, civilian markets comprising cars, buses, and trucks failed to respond. Such a reality has created a gap in the adoption growth cycle, creating the Chasm phenomenon. Hence, it’s not due to social and personal traits for which autonomous vehicles have been caught in the chasm. The underlying factor is that autonomous vehicle technology needs to improve further to make such innovations economically better alternatives than prevailing ones.
Inflated Expectations led to Dipropionate Investment
Due to the success of autonomous vehicle technology in diffusing in the military market, expectations about the imminent diffusion in the civilian market spiked. As a result, technology firms, R&D institutions, startups, and automobile companies ramped up investment. Consequentially, the valuation of technologies rapidly inflated, resulting in acquisitions at astronomical prices. One notable example is Intel’s purchase of Mobileye, developing algorithms for autonomous vehicles, primarily for the Israeli military. Upon speculating unfolding high demand, Intel paid a staggering $15.2 billion to acquire this small technology firm. Like Intel, many established technology and automobile firms paid a hefty sum to acquire small firms with expertise in autonomous driving.
According to Brookings Institutions, from 2014 to 2020, investment in autonomous vehicle technology development and investment reached as high as $80 billion. Along with the acquisition, publications, patents, and startups also spiked. Besides, media reporting also contributed to inflating the hype. However, due to unforeseen hurdles, key autonomous vehicle technology performance indicators, like disengagement frequency, started prematurely oscillating. Consequentially, the peak of expectation plummeted to a trough of disillusionment. Irrational exuberance caused by early success and the high-performance barrier faced by technology resulted in a typical hype cycle. Furthermore, claiming autonomous driving as a Disruptive innovation was also premature as the creative destruction tipping point has been far beyond the peak of the hype cycle and early success of diffusion in the military market.
Economics and Externalities Dictate Autonomous Vehicle Innovation Diffusion
Ultimately, innovation diffusion is dictated by the economics of innovation, technology advancement, and externalities. Customers, whether military, pragmatists, or majority civilians, carefully perform financial benefits to be derived from adoption. It happens that technological advancement keeps turning economics in favor of adoption due to the success of increasing quality and reducing cost simultaneously. Besides, externalities like infrastructure, maintenance, support service, and compatibility also affect innovation diffusion.
The hype cycle is caused by a lack of knowledge about technology advancement complexity in meeting the detailed requirements of different segments of customers. Often, at the early stage, the half-baked solution meets the economics of military adoption or some other market segments facing unique situations. Such success inflates the expectation of penetrating a large, untapped civilian market. However, it does not necessarily mean that the same immature technology will keep driving the diffusion of innovation in subsequent market segments. Often, subsequent market segments demand far higher technology maturity. In some cases, such reality stalls the diffusion, causing the chasm. Hence, such a chasm is created due to hard barrier faced by further technological advancement need to serve the majority market segment.
Inappropriate innovation diffusion theory and technology uncertainties
Unfortunately, technology does not keep growing linearly. Often, upon showing initial success leading to diffusion in innovator market segments like the military, R&D effort faces difficulty overcoming technology development complexity. As a result, both the chasm and hype cycle show up. Hence, interpreting the technology innovation diffusion pattern as a social and cultural phenomenon, as Rogers and Geoffrey Moore did, appears inappropriate. It seems that innovation, the economics, varying requirements of different customer segments, and unfolding complexities of technology development at various life cycle stages are the primary determinants of autonomous vehicle diffusion. Due to this, a Chasm in the innovation diffusion may keep occurring instead of just happening once somewhere between two segments.