Increased accident fatalities and the rising concern for vehicle safety and security have accentuated the need for the development of semi-autonomous and autonomous vehicles, according to the latest research from MarketsandMarkets Research Pvt. Ltd. (MnM). Srinath Manda, Associate Director of Automotive and Transportation at MnM answered a few questions from Autonomous Vehicle Technology (AVT).


AVT: Autonomous vehicles are expected by MnM to be commercialized by the 2022-2023 timeframe, however the adoption is expected to face many hurdles. Explain what you mean by “commercialized,” regarding mobility services and shared cars/rides versus private-car ownership, and what are some of the major hurdles to be faced?

Manda: MnM’s assumption/expectation is that autonomous vehicles will be introduced to the general market by 2023. Therefore, the market estimation for autonomous vehicles would start from 2023 and reflect to stages of mass production and adoption by 2030.

  • The high cost of self-driving cars is considered to be a big reason for their high penetration into shared mobility, at least at the initial timeframe.
  • A study by Intel cited that self-driving vehicles are expected to free more than 250 million hours of consumers’ commuting time per year in the most congested cities in the world. That is a lot of time that could be filled with streaming video, news, and other content delivered to a captured audience. By 2050, it is also predicted that use of mobility as a service will be a market worth $3 trillion in revenue.
  • Convenience and cost savings are two major reasons for adaptation of shared vehicles over private car ownership. Autonomous vehicles would become the natural commuter choice as the consumer becomes increasingly uninvolved from the driving experience and vehicle ownership.

Safety and security concerns are the biggest hurdle for the growth of autonomous vehicles. There is a rising concern that autonomous vehicles can be hacked and controlled by hackers, which may pose a life threat to the passengers and also to the people who are within the proximity of the car.


AVT: MnM estimates that North America will hold the largest semi-autonomous vehicle market share, by volume, of about 44% in 2022, followed by Europe at 31%. Why will North America be leading, compared to other major markets?

Manda: The North American market is being dominated by OEMs such as Ford, GM, and a few others. The rapidly expanding ecosystem includes Tesla with its EV (electric vehicle) technology; Toyota with its product offerings and strategic partnership with Uber; Mobileye, which has recently been acquired by Intel, showing the importance of its product offerings; and Google, which is pioneering advances in autonomous and in-vehicle technology.

Increasing road fatalities, increasingly stringent passenger safety and security norms, and increasing connectivity in vehicles are expected to boost the market growth of semi-autonomous and autonomous vehicles in North America.

North America is considered the most favorable region in terms of autonomous vehicle testing. The favorable government policies along with the high revenue support has further driven the market for autonomous vehicle in the region. As of November 2017, California? Department of Motor Vehicles has issued autonomous vehicle testing permits to more than 40 companies. Major OEMs around the globe—such as Chinese players such as Baidu Inc. and SAIC Motors, which do not even have a major presence in the U.S., are coming to the region for testing of their autonomous cars. It has been estimated that after getting the autonomous cars developed in North America, these companies will start testing their vehicles in their respective regions.


AVT: How are the MnM identified factors of the demand for minimal driving errors, reduced insurance premiums, efficient operating costs, and rising concerns of safety and security expected to drive market growth in the coming years?


Minimal driving errors: Autonomous or intelligent driving is divided into these parameters: 1) route planning, 2) path planning, 3) maneuver choice, and 4) trajectory planning. While transporting passengers or goods from a given origin to a given destination, motion-planning methods incorporate searching for a path to follow, avoiding obstacles, and generating the best trajectory that ensures safety, comfort, and efficiency. This would reduce driving error and will subsequently increase the adoption rate of autonomous vehicles.

Reduced insurance premiums: In the future, the insurance of vehicles will be usage-based, where the total driving miles will be considered in the calculation of the insurance premium. Since all the data of an autonomous vehicle (such as the miles traveled) would be hosted in the cloud, and these data would also be used to calculate insurance premiums, the costs on such fronts will be reduced. Thus by reducing insurance premium, adoption of autonomous vehicles is expected to rise.

Efficient operating costs: To ensure efficient operating costs, OEMs are focused on developing advanced technologies such as ECU consolidation or moving towards domain fusion, which would further reduce the number of ECU applications in a vehicle. This would result in higher adoption of autonomous vehicles. Furthermore, OEMs are inclined towards developing electric vehicles and reducing components and weight in vehicles, which are also expected to result in efficient or reduced operating costs and increase in market size for autonomous vehicles.

Rising concerns of safety and security: Cars today are equipped with a large number of advanced ECUs (in some cases, more than 100 units) and more than 100 million lines of code. It has raised concerns for auto manufacturers as they source ECUs from different suppliers, which results into no single supplier having full control of, or even familiarity with, all of a vehicle’s source code. This is a concern of safety and security. OEMs are focused on developing in-house software and control cloud data, which would minimize such risks. This will drive the market for autonomous vehicles.