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  • Maximilian Mayer

Machine learning and the next level in reshaping mobility

Updated: Feb 24

Acknowledging the brains behind the wheels of a mobile revolution



When it comes to artificial intelligence, we all seem to have got more and more comfortable with the idea of not only coexisting, but also benefiting from it. Counter arguments appear to be fading somewhere into the background of the multiple important contributions that truly revolutionized the world. And one of the most thrilling ongoing revolutions is happening in the mobility industry.


Throughout history, we have witnessed a number of no less than extraordinary contributions to improving mobility, such as Switzerland building the Gotthard Tunnel, the longest and deepest rail tunnel in the world. Aside from the display of magnificent engineering, milestones like this one show the importance of an innovative way of envisioning and approaching the mobility sector. Therefore it’s unsurprising that AI is currently behind the wheels when it comes to driving us to the next evolutionary phase for transport and mobility. Even in a world crippled by a pandemic, cities grow more connected and the possibilities for artificial intelligence to improve energy efficiency, liveability and mobility grow exponentially. This allows a better self-organization and an organic evolution, in a data driven way.


When machine learning becomes the teacher


Since it’s highly unlikely that the current circumstances haven’t already affected everyone one way or another, there’s no wonder why transportation and logistics (T&L) companies have last year reached their lowest ever confidence level concerning their revenue growth. Yet, more and more T&L companies are turning to new, cloud-based machine learning services that can help them become more efficient and drive a better experience for their customers. We’re experiencing times when the mobility industries are gaining more complexity and profitability grows exponentially with a technology-driven efficiency. AI and machine learning have been teaching us how to expand our horizons and proved to be a very important instrument in the process of adapting to the new normal. And it’s going to continue being an essential element for the bright future of the industry, by providing it with new innovations as a response to not only its biggest problems, but also its biggest plans.


The unique current circumstances only add up to the list of reasons why the way people and goods move will have to undergo dramatic change. Businesses seem to have understood this vital necessity and started focusing more on using technologies like machine learning, artificial intelligence and data analytics to identify, predict, and solve present and future mobility challenges. One of the major goals for companies and for cities as well is transitioning to autonomous mobility, in order to ensure a more efficient, sustainable and environment-friendly model.


Artificial Intelligence leading the mobility (r)evolution


As we very well know, AI already contributes in many various ways to the field of mobility. Automation and assistance systems are already widely implemented, while operations, planning and asset management have experienced a whole new level thanks to it. But the focus is now on making mobility efficient, user-friendly and profitable, on top of everything.



But how?


We’re more than delighted to jump the bandwagon and actively contribute to the revolution. Ubiq's AI-driven services do this by ensuring effective fleet rebalancing, charging and policy compliance. In other words, it makes sure that vehicles are in the right place, at the right time, to meet demand. AI can predict the best times to charge the electric vehicle. Moreover, smart grid management enables drivers to reduce costs and increases the efficiency and stability of the entire grid.


And we’re by far not the only ones. The ride-hailing company Grab turned to machine learning tools to access real-time data computation and data streams that support 1.5 million ride bookings and to boost its real-time on-demand matching and supply algorithms. This was one of the important moves that pushed Grab towards a success that culminated with the company defeating Uber to become the biggest ride-hailing company in Southeast Asia.


Another example of AI and machine learning, this time positively impacting the T&L industry, is Lyft’s use of an AI-powered time series analytics solution. This particular technology automatically surfaces anomalies signaling larger problems, and detects incidents needing inspection. As a result, Lyft no longer needed to invest in large in-house data science or manually inspect dashboards, which naturally led to quite significant cost reductions.


When it comes to driverless vehicles, it’s safe to say that they have been surrounded by a cloud of public skepticism from the very first moment. In spite of this tough spot, the majority of self-driving vehicle companies are still moving forward. They strongly believe that - with the assistance of AI and machine learning - they will turn this mentality around, gaining mass confidence and even become mainstream, while even considering the current pandemic circumstances. And there’s no secret why the companies would rely on machine learning and AI. Deep learning is the brains behind the processing and giving context to all the information that comes from the sensors. And since data comes from multiple complex sources, such as LiDAR, it’s more than useful to ensure a solid and comprehensive processing of it all.


Learnings from machine learning


Out of all the significant investments in the mobility sector, the majority focus on artificial intelligence. Furthermore, new mobility systems and players are planning to leave their own mark on the market: Tesla is continuously working to bring improvements to its autopilot system, Google is developing self-driving cars and Uber is experimenting with robotaxis.


What we need to consider is the effects of rapid movements and constant changes in the mobility industry due to machine learning and AI. While nothing less than an extraordinary evolution and contribution to the market in particular and life around the world in general, this major influence is highly dependent on its dynamic rhythm and following and adapting the next new trend. Companies are therefore pushed to keep up with this ongoing groundbreaking revolution in order to achieve evolution. And herein lies the beauty of mobility, an industry unanimously nominated to push boundaries and continuously set new and improved standards.

Ubiq enables operators to effectively position fleets to serve strategic goals. For more information, contact sales@ubiq.ai