Today, automotive trends go beyond horsepower and top speeds to the connected and edge technologies that could make self-driving cars possible.
Connected cars are growing in adoption and autonomous vehicles could be around the corner. To keep up with automotive technology, new data infrastructure is critical for vehicles to store and process information from radar, LIDAR, sensors, control units, and other vehicle electronics to help make real-time driving decisions. So, instead of asking about horsepower, a curious consumer might ask, “How much technology does it have?”
Investing in Next-Generation Mobility
As the transportation industry transforms, the vehicle data changes with it. It demands different approaches to collect, manage, and utilize it to its full potential. “Even corporations that have dealt with large volumes of data, new mobility is bringing to them new variety, velocity, and quality of data,” argues Evangelos Simoudis, Founder and Managing Director of Synapse Partners.
His venture capital firm has a sole focus on early-stage companies using enterprise software applications that combine Big Data and AI. Their growing portfolio already includes startups involved in:
- Teaching self-driving vehicles how to read and react to pedestrian behavior
- Simulating solutions for autonomous vehicles at scale
- Combining data analytics, driver safety, and self-driving software
We sat down with Evangelos to talk about data-driven automotive trends that are shaping the vehicles and infrastructure of tomorrow.
#1. Cybersecurity Solutions for Connected Vehicles
In many ways, a connected car is a large-scale version of an IoT-enabled device. Consider this: it has embedded electronics, hardware, and devices connected to the Internet. Better connections could mean new services and new solutions, which in turn could make driving safer and more enjoyable. But, it could also be exposed to attacks from hackers. Such a data breach could pose an immediate threat to drivers and passengers, especially if a hacker were to gain control of a moving vehicle.
“We have cybersecurity for the engine. We have cybersecurity in the autonomous stack or ADAS-level. We have cybersecurity in the cabin – sensors capturing data that enable personalization of vehicles. Finally, we have cybersecurity of passengers’ data,” Evangelos Simoudis explains.
Just about every service that a connected car can provide has a unique set of cybersecurity needs. It would be difficult to find a one-size-fits-all security solution. Instead, big data analytics and machine learning are helping create cybersecurity coverage across the driver ecosystem: OEMs, Tier 1 organizations, ride-sharing, rental, fleets, and more. The result could be protection from vehicle fraud, misuse, and policy violations.
#2. V2X Communication in the 5G Era
The era of 5G is almost upon us. Whether through big 5G conferences or trial runs, major telecommunications companies are laying the groundwork for fifth-generation wireless networks. Before deploying, though, there are a few considerations to be addressed. 5G is poised to create new demands in data storage, access, and transfer. Data storage must be clearly defined from end points at the edge and in the cloud to help meet both user and application needs.
Communication is also a key to help creating a safer generation of smarter vehicles. This is especially important in autonomous drive development, where vehicles are constantly communicating with other vehicles and the broader road infrastructure. V2X communication plays a role in preventing accidents on the road, improving the flow of traffic and exchanging information with road-side, connected devices.
As Evangelos notes, there is also the matter of cybersecurity in V2X communications:
“The AI that help monitor V2X communication in connected vehicles require cybersecurity updates to ensure they are tamper-proof,” he states.
SD cards and embedded flash drives can help protect messages from being intercepted by potential hackers. These devices can store communication security keys, operation system software, and message log data – all important components of keeping vehicle communications safe.
#3. Developing Fully Autonomous Vehicles
The automotive industry is making strides to reach the pinnacle of self-driving vehicles, Level 5 autonomy. This involves full-time performance of an automated driving system with driving tasks on a variety of road environments – free of human intervention. Reaching this level of advanced knowledge will include using machine learning on vehicle data generated by radar, sensors, cameras, control units, and other devices. In addition, real-time edge storage can help overcome latency and connectivity issues tied to using the cloud for vehicle services.
In developing autonomous and connected vehicles, physical fleets can only drive so many miles for so many hours. This makes it challenging to collect the amount of data necessary to know how a self-driving car might drive in a variety of road conditions. Instead, one of the most powerful automotive trends is to start using data to create virtual fleets of autonomous vehicles. Even a fleet of 100 simulated vehicles could generate as much as 200 – 500 petabytes of raw data. It’s a massive amount of data, and manufacturers might be wise to rethink their infrastructure for unstructured data that requires extreme data durability with fast and easy retrieval.
#4. Onboard Computing Could Protect Passengers and Drivers
In 2018, there were an estimated 718 accidents per hour, in just the United States. But, what if data could help prevent accidents? Enter: edge processing. By building a platform for onboard computing, vehicles could learn to process and react to changing road conditions in real-time. For example, lane departure warnings use edge processing to collect and analyze sensor data. This gives drivers and passengers real-time alerts, while avoiding the latency associated with the cloud. Big data is also making possible vehicle safety features, such as:
- Automatic brakes
- Automatic distance control
- Backup cameras
- Collision warning
- Lane departure warnings
- Parking assist
Onboard computing is far from being widely adopted by OEMs. In fact, a few years ago, only 5 percent of cars had advanced driver-assistance systems. One issue is the higher costs of developing and installing compute resources onto vehicles. Another potential challenge is the process of over-the-air software updates. These updates must be downloaded, checked for integrity, sent to the vehicle’s systems for updates, and backed up.
#5. Beyond Moving from Point A to B
Next-generation vehicles and associated services are getting a lot of attention, but the passenger experience is still developing. One of the next steps is to integrate mobility with convenient services. Historically, OEMs have lacked the data and resources to seamlessly tie in-vehicle services with the driving experience.
In recent years, though, newer vehicles have embraced a new wave of technology. Small displays have been replaced with large touch screen monitors – Internet-connected, Bluetooth-enabled, and loaded with data-intensive mobile applications. Even car navigation systems, which drivers might have chosen to use mobile mapping services, is starting to see adoption through 3D maps.
Could there be other opportunities to monetize mobility? Artificial intelligence might offer an answer. With AI-based reasoning, new ways to use mobile shopping, video streaming, and other tools could keep passengers engaged and incentivized during their time on the road.
“Imagine: I want to go on a skiing weekend to Lake Tahoe,” Simoudis illustrates as an example. “I want to think of it as a complete experience. I don’t want to think of just the transportation from Point A to Point B. Mobility companies will have the opportunity to offer those kinds of services, given where the industry believes it’s going.”
More on the Future of Automotive Trends and Technology
- Did you know that edge processing could save your life on the road? Our research report dives into the details.
- What will it take to build self-driving cars? Edge computing, for starters, but so much more. Read our blog post about automotive trends at the edge.
- In the future, the fuel for automotive transportation probably won’t be oil. It’ll more likely be data. Find out why from Western Digital’s automotive data solutions.
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