The major threats to the automotive industry have generally come from within. The automotive industry has enjoyed decades of steady growth, immune to outside disruptions like the ones seen in the entertainment industry with Netflix and the hotel industry with Airbnb. However, tightening regulations and changing consumer trends fueled by major advancements in emerging technology is changing all that.
In the automotive industry, customer perception of value has shifted from the car hardware and brand name to safety, efficiency, driving comfort and environment-friendliness. Artificial intelligence, machine learning, cloud and smart connectivity along with existing radar, lidar, cameras and sensors have produced several advanced driver assistance systems (ADAS) that are being implemented extensively, thereby disrupting the industry today.
Among the ADAS features are adaptive cruise control, blind spot detection, parking assistance, lane departure warning and autonomous emergency braking. SAE International classifies them as level 1 (driver assistance) and level 2 (partial automation) where the human driver monitors the driving environment and intervenes when required. The ADAS market is now an established multibillion-dollar industry with rapidly evolving methodologies and best practices. While ADAS has contributed significantly to improving transportation safety, emissions and efficiency, it is only the first step towards a larger goal - Fully autonomous vehicles.
The potential for fully autonomous vehicles to usher in a new era of transportation has seen unprecedented investment from automotive OEMs in recent years. Despite bold claims from these automakers, level 4 (high automation) and level 5 (full automation) automobiles could be several years away. Governments and Automotive companies will have to work together on three fronts to further accelerate the development of autonomous vehicles.
The first challenge automotive companies encounter is legal and regulatory. While testing of autonomous vehicles (AVs) is allowed on roads, a code of practice or standards that the testers are expected to follow is still unclear in most countries. This causes an issue of determining liability in the case of accidents involving transition of vehicle control from driver to human. Frameworks regarding data sharing in V2V and V2X communication are largely under development.
The second and most significant challenge is technological. Despite the advancement and proliferation of smart sensors, there have been reported cases of sensor snags. This situation is a complete no-go when an AV is driving itself at speeds above 60 mph. Moreover, three kinds of systems – radar, camera and lidar are required. Sensor fusion yet again is not fail proof. Another challenge is the volatile nature of driving environment. AVs need highly complex algorithms to predict the behavior of human pedestrians, human cyclists and human-driven vehicles. Weather conditions like snow and fog only add to the misery.
The third challenge is economic. Developing advanced driver assistance systems that can be manufactured and deployed at large scale with cost-effective, maintainable hardware is quite complicated. Insurance pricing becomes dynamic. What will be the new pricing methods for insurance and how do you determine compensation when liability is unclear? Another issue is the vast amounts of data generated by AVs which opens new monetization opportunities. How do you determine who owns the data in these situations?
There are many questions to be answered and obstacles to be crossed. If we are to see these 4-wheeled robots on the road any time soon, it is quite clear that automotive OEMs must engage in partnerships and collaborative ecosystems to speed up their go-to market. This opens the door for established technology companies which are already software inclined and have more deployable human capital towards software development. Traditionally, automotive companies have focused on minimization of risk due to rigid supply chains, product development practices and tough sectoral norms. Technology firms on the other hand, use agile operating models that allows experimentation. This is only augmented by the fact that they enjoy higher financial agility and robust operating margins that increase the opportunity to explore innovative solutions.
In addition to autonomous driving, trends such as connectivity, electrification and mobility are transforming the global automotive market’s massive size and value-creation potential. As a result, the already complex automotive ecosystem is primed to become more intricate and one thing is inevitable – software will drive the driverless future and partnerships between automotive OEMs and technology firms will be at the forefront.