Connected cars have been around for about two decades. GM first launched its OnStar in-vehicle communications service in 1996. Although the vast majority of the 1.4 billion cars on the world’s roads still lack embedded cellular connectivity, there is growing demand from drivers for wireless safety and security features, and streamed entertainment and information services. Today, many people simply use their smartphones inside their cars to help them navigate, find local amenities and listen to music.
The falling cost of cellular connectivity and equipment is now making it increasingly cost-effective to equip vehicles with their own cellular modules and antenna to support emergency calls, navigation, vehicle diagnostics and pay-as-you-drive insurance. OnStar, which offers emergency, security, navigation, connections and vehicle manager services across GM’s various vehicle brands, says it now has more than 11 million customers in North America, Europe, China and South America. Moreover, as semi-autonomous cars begin to emerge from the labs, there is growing demand from vehicle manufacturers and technology companies for data on how people drive and the roads they are using. The recent STL Partners report, AI: How telcos can profit from deep learning, describes how companies can use real-world data to teach computers to perform everyday tasks, such as driving a car down a highway.
This report will explore the connected and autonomous vehicle market from telcos’ perspective, focusing on the role they can play in this sector and the business models they should adopt to make the most of the opportunity.
As STL Partners described in the report, The IoT ecosystem and four leading operators’ strategies, telcos are looking to provide more than just connectivity as they strive to monetise the Internet of Things. They are increasingly bundling connectivity with value-added services, such as security, authentication, billing, systems integration and data analytics. However, in the connected vehicle market, specialist technology companies, systems integrators and Internet players are also looking to provide many of the services being targeted by telcos.
Moreover, it is not yet clear to what extent the vehicles of the future will rely on cellular connectivity, rather than short-range wireless systems. Therefore, this report spends some time discussing different connectivity technologies that will enable connected and autonomous vehicles, before estimating the incremental revenues telcos may be able to earn and making some high-level recommendations on how to maximise this opportunity.
- Executive Summary
- The role of cellular connectivity
- High level recommendations
- The evolution of connected cars
- How to connect cars to cellular networks
- What are the opportunities for telcos?
- How much cellular connectivity do vehicles need?
- The size of the opportunity
- How much can telcos charge for in-vehicle connectivity?
- How will vehicles use cellular connectivity?
- Telco connected car case studies
- Vodafone – far-sighted strategy
- AT&T – building an enabling ecosystem
- Orange – exploring new possibilities with network slicing
- SoftBank – developing self-driving buses
- Conclusions and Recommendations
- High level recommendations
- STL Partners and Telco 2.0: Change the Game
- Figure 1: Incremental annual revenue estimates by service
- Figure 2: Autonomous vehicles will change how we use cars
- Figure 3: Vehicles can harness connectivity in many different ways
- Figure 4: V2X may require large numbers of simultaneous connections
- Figure 5: Annual sales of connected vehicles are rising rapidly
- Figure 6: Mobile connectivity in cars will grow quickly
- Figure 7: Estimates of what telcos can charge for connected car services
- Figure 8: Potential use cases for in-vehicle cellular connectivity
- Figure 9: Connectivity complexity profile criteria
- Figure 10: Infotainment connectivity complexity profile
- Figure 11: In-vehicle infotainment services estimates
- Figure 12: Real-time information connectivity complexity profile
- Figure 13: Real-time information services estimates
- Figure 14: The connectivity complexity profile for deep learning data
- Figure 15: Collecting deep learning data services estimates
- Figure 16: Insurance and rental services’ connectivity complexity profile
- Figure 17: Pay-as-you-drive insurance and rental services estimates
- Figure 18: Automated emergency calls’ connectivity complexity profile
- Figure 19: Automated emergency calls estimates
- Figure 20: Remote monitoring and control connectivity complexity profile
- Figure 21: Remote monitoring and control of vehicle services estimates
- Figure 22: Fleet management connectivity complexity profile
- Figure 23: Fleet management services estimates
- Figure 24: Vehicle diagnostics connectivity complexity profile
- Figure 25: Vehicle diagnostics and maintenance services estimates
- Figure 26: Inter-vehicle coordination connectivity complexity profile
- Figure 27: Inter-vehicle coordination revenue estimates
- Figure 28: Traffic management connectivity complexity profile
- Figure 29: Traffic management revenue estimates
- Figure 30: Vodafone Automotive is aiming to be global
- Figure 31: Forecasts for incremental annual revenue increase by service