There are a lot of different technologies being implemented in the automotive industry these days. These technologies include hardware and software innovations like smart car applications and autonomous vehicle systems.
Software development services can be used to drive these changes and get products faster out the door for the latest vehicles to take advantage. Think Tesla’s electric vehicles with their internal systems of navigation, Apple’s integration of apps and services into vehicles called Apple CarPlay or Google’s Android Auto.
Today’s vehicles are also being equipped with various fail-safe measures such as assisted parking and software monitoring that is driven by the hard work of software developers. Such innovations are making cars more autonomous and safer to drive than ever before.
Software development is key to integrate vehicle systems with apps, other software like GPS navigation, as well as keep the internal systems and the main computer systems running.
Machine Learning in Vehicle System Design
Future vehicle design will allow vehicles to track your eyes, gestures as well as habits to use this data as insight. This insight will be used to change driving conditions like preferred temperature on the fly, suggested news sources and improved navigation to work or other frequently visited destinations.
Some say that the future of vehicle design may be more based on code than actual fuel. All of these innovations and real-time insight will be made possible in an ever greater capacity by machine learning and AI. As the algorithm learns from drivers’ driving habits, it will give them a more personalized experience.
Smart car hardware requires a top-notch code to make it sync and power on the internal systems. Vehicle software continues to be refined internally and software developers are needed for this task.
Future monitoring systems will offer continuous feedback and the ability to predict mechanical or other failures way in advance. These systems will also monitor your fuel or battery levels, estimates to rest stops, weather conditions and traffic congestion conditions in an ever more dynamic fashion.
Other advancements in machine learning are also paving the way for advancements in vehicle machine learning systems. This is because vehicles of the future will have greater voice implementations through systems like Siri rather than rely on drivers taking their eyes off the road to interact with a user interface. As natural language processing improves within AI systems, so will vehicle AI systems as a whole.
The Internet of Things and Smart Car Design
Sensors continue to be refined as well with software backing up their tracking abilities. These sensors are part of the new Internet of Things (IoT) concept where they give live feedback to drivers en route. An example of how they work is the aforementioned parking assistance, but the vehicles of the future will be fully automated with a driver’s wish.
Apple’s CarPlay is an example of how the Internet of Things is being implemented into vehicles of today and shows potential for future smart car design. It connects a vehicle to Apple’s ecosystem, via a tablet or a similar screen, of apps and services. A user can have news read to them via Siri, for example, or have an eBook read to them during a long commute.
Autonomous Vehicles and Software Development
Software development within the auto industry is more than just systems in place to make drivers more comfortable and travels safer. Autonomous vehicles of today, like the Google Car, use software and hardware to scan and analyze the terrain in order to improve mapping or other software.
However, this is just a first step to fully automated vehicles being able to use and analyze sensor data for changing driving conditions on the fly. We are still a few years away from fully automated vehicles on roads and software developers right now are working on solutions along with various engineers to make this a reality sooner than later.
There are still hurdles that need to be overcome before driverless cars start appearing on roads en masse. The big problem of fully autonomous vehicles are unpredictable road conditions such as a human driver making a mistake and the autonomous system responding to the mistake effectively in real-time. Another example is a curb that may or may not be marked or a yellow line pointing a vehicle to a dead-end that only humans can see with their own eyes but a computer has to analyze through data.
Software developers and engineers are currently putting their minds together to work these problems out. The future is bright for autonomous vehicle technology and a great field for software development investment.
Mass Differentiation Amongst Driver UX
Automation, vehicle assistance systems and personalization through software are just the tip of the iceberg when it comes to software systems within vehicles. Driving system software will define the driver and differentiate their UX as much as purchasing a new vehicle would.
Code that is reusable will be tweaked for each vehicle and driver along with their preferences ahead of time. Drivers will be able to customize virtually everything within their vehicles in a car lot as they purchase their car of choice. Automakers will also start to implement much more customization for clients to choose from based on different premiums and features they want.
Vehicles are becoming smarter and more software-defined than ever before. Code is replacing fuel as the driving force of the future. The industry is ripe for talent and offers opportunities. Machine learning, data gathering and automation are becoming standard practices. This trend will continue with autonomous vehicles and software-defined commuting becoming the norm and current software design is paving the way.
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