Private Sector Application

Private Sector Application

Studebaker Mobility Investment Focus

Private Sector Application

Studebaker Mobility will invest in technology that relates specifically to the automotive industry, even though select technologies like 5G and cyber security have wider applications in other industries.

Studebaker Mobility’s focus is on investment in disruptive technologies that will change the future of the automotive industry.

The technology focus areas for Studebaker include the following:



The cluster of technologies being developed to turn vehicles into intelligent, sentient robots include systems on chips, GPS, analytic sensors, wireless communications, and deep learning.

The emerging world of connected, increasingly autonomous vehicles will demand huge volumes of sensors – vision sensors, pressure sensors, temperature sensors and more – to feed live data sets to both on-board computers (accessed locally within the vehicle) and cloud-based data centers (accessed remotely)

In driving environments, there is often no time to send data to the cloud and receive back details of the appropriate action to take. At Level 4 autonomy and beyond, the vehicle will have to carry its own data center on board that can sense, infer and act in real time given the critical importance of zero latency in real time road and traffic conditions. This on-board computer will also play a critical safety role in cordoning the vehicle off from external cyber-attack.

Semiconductors technology encompasses several sub-sections for investment consideration including processors, sensors, light detection and ranging (LiDAR), and silicon photonics technology.

Each new car carries an average of $500 worth of chips. This compares to a chip content of just $60 for the average smartphone. These chips come in all shapes and sizes – RF and baseband chips, sensors, microcontrollers and powerful CPUs to process vision interpretation data. By 2030, it is estimated that 80% of the value of a vehicle will reside in its software and content. Neural net-based machine learning will become a standard auto component. The ability of vehicles to learn and improve themselves every mile they travel is front and center of the evolving self-drive phenomenon.

The car now has to be a rich, connected, voice-activated, AI-enhanced infotainment hub on wheels. A range of cloud-based apps driven by conversational platforms from Amazon (Alexa), Apple (Siri), Alphabet (Google Assistant) and Microsoft (Cortana) are being pushed into the cockpit. Amongst the Tier-1 auto component suppliers, Bosch has unveiled Casey, its own automotive conversational platform while, amongst the car makers, Ford has introduced Sync, its version of a voice-powered driving assistant.

Select companies are working on as passenger drones and electrical vertical take-off and landing (eVTOL) aircrafts – flying taxis. Passenger carrying drones may come to market within the next three to five years.

An electric drivetrain is simple compared to an ICE drivetrain. It comprises only a handful of components, whilst ICE drivetrains involve hundreds of components. Plug-in hybrid vehicles involve a combination of the two – electric motors and ICEs – and surrounding systems. Drivetrains will require significant performance improvements to meet more stringent emissions regulations.

Key to the automotive industry are the auto parts suppliers and key among those are the Tier-1 suppliers who supply whole sub-systems to the car makers rather than just individual components. Auto suppliers are collaborating with OEMs and EV automakers to jointly develop and conduct field testing of new-age vehicles. Major Tier-1 suppliers are also collab collaborating with IT companies and startups specializing in new technologies to strengthen their in-house R&D capabilities.

There are no global standards for electric charging stations even though there are over 7 million installed chargers for electric vehicles worldwide. According to the Electric Vehicles Charging Association (EVCA) the total number of charging stations will increase to 46 million by 2025, with 10 million in the world’s biggest car market, China.


Widespread adoption of Level 4 and Level 5 autonomous vehicle technology will call for 5G broadband wireless networks. These 5G mobile networks will require access to sufficient radio spectrum and be supported by ubiquitous base stations, in-device antennas, and denser yet cleaner-cut multiple input and multiple output (MIMO) systems in order to serve millions of connected ‘things’ per square mile in major cities.

Amid euphoria about the scope and prospects for self-drive, there looms the ever-larger threat of cyber-attacks. These attacks can come in many forms: hacks that lock people out of their cars and demand ransomware; malware that plays on brakes and steering to cause fatal accidents; and sabotage of driving environments and GPS mapping. Securing vehicles against a myriad of cyber threats will be critical to public acceptance of fully autonomous vehicles, which offer a greater ‘attack surface’ exposed to sabotage than current Level 3 autonomy vehicles.

Auto brains need access to huge datasets to educate them. Some of these datasets include ‘live time’ streaming of sensor data from LiDAR, cameras and radar systems to enable safe navigation. Cloud and in-vehicle data analytics and machine learning based on big data are part and parcel of self-drive.