How can AI contribute to Smart Mobility?


Nowadays, there are numerous investments in the automotive industry, particularly in Artificial Intelligence (AI) and optimizing the mobility landscape. Smart mobility can drive the economic growth of cities, generate cost-effective solutions, and open new markets for businesses.

Due to the increase in pollution, rise in fatalities, and wasted time in traffic jams, the need for a better and more efficient transportation sector has grown across the modern world. Smart mobility comprises different concepts such as bike commuting, ride-sharing, and driverless vehicles to improve traffic conditions.

At the same time, the integration of AI in smart cities has a positive impact on the environment. Used within smart cities, AI makes it possible to manage waste and maintenance and predict pollution risks, energy consumption, and the effects on the environment.

Cities are constantly innovating with the help of Artificial Intelligence, which already has a wide application in smart cities. Smart mobility is an innovative idea aiming to maximize and optimize transportation resource usage in a more secure and well-organized way to ensure zero emission, decrease the number of accidents and provide no ownership of vehicles.

As growing trends, AI and smart mobility are expected to advance significantly. According to a 2018 report from Frost & Sullivan, sharing cars is predicted to reach 36 million by 2025. Another study reported that there were only 0.35 million shared vehicles globally in 2006, but this number rose to 7 million by the end of 2015, and it could reach 36 million by 2025.

Smart car-sharing station traffic and toll management

People regularly face traffic congestion issues. Using smart car-sharing stations may comprise an important link in smart mobility. Sharing vehicles will lead to less traffic and fewer cars, so car-sharing can reduce congestion by cutting down the number of vehicles.

Thanks to AI, smart parking systems are starting to offer solutions for urban mobility. This system improves car parks accessibility and obtains real-time data about parking availability. For instance, Geneva boasts a very efficient smart parking system, lowering the number of vehicles searching for a parking place by 30%.

License plate recognition technology is broadly used for vehicle management operations, such as parking control, access control, toll collection, traffic monitoring, etc. With license plate detection, which recognizes vehicle number plates in an image or video, it is possible to automatically record a vehicle’s entry and exit, oversee the number of times vehicles appear, how long they stay, detect cars that have outstayed hours, etc.

Automated number plate recognition is a highly accurate system that manages traffic efficiently. It can be used to detect traffic rules violations, such as high-speed driving, stolen vehicles, illegal parking, and other traffic offenses. AI-powered license plate recognition may be integrated to manage toll operations automatically. The system records and controls the entry and exit of vehicles at toll gates. Besides, it can be used for electronic toll collection, automatically allowing drivers to pay for tolls. This technology enables effective toll booth management, reducing operational time and increasing productivity. Traffic and toll management is another space where AI can offer huge benefits.

Ensuring safety

Smart mobility is changing the mobility ecosystem in urban environments with technologies like shared motorcycle/bike, dedicated lanes, and improved transportation systems in response. With the help of AI, it can gain significant benefits, influencing the citizens’ quality of life and safety.

One of the main reasons for fatal accidents is that drivers or passengers do not wear helmets. AI-based helmet detection technology can identify people driving without helmets to ensure their safety and decrease the risks of accidents. For example, in the case of motorcycle/bike-sharing services, the system may be applied to improve the safety management of riders with helmet-wearing detection.

Saving the environment

Using AI and machine learning makes it possible to analyze the current pollutants, assess the risks associated with global warming, and predict pollution levels. These data help authorities to make well-informed decisions contributing to a safer and cleaner environment.

AI-enabled cameras can detect and recognize the type of trash thrown on the streets for categorization and make the waste collection more effective. AI-enabled sensors on the bins enable automatic alerts when the bins are about to be filled and reduce operational costs by eliminating unnecessary pickups and providing schedules for the optimization of waste management.

Additionally, the power generating grid and smart water management are leading factors that help produce energy with less pollution. They can also assist with getting clean drinking water and keeping our environment clean.

Driverless vehicles

As smart mobility solutions become more advanced, the trend towards driverless vehicles can slowly gain mass confidence and make its way into the transportation sector. According to self-driving vehicle market adoption statistics, the global self-driving vehicles industry is expanding by 16% every year.

As most car accidents are caused by human error, the crucial benefit of driverless vehicles would be safe. It could improve public transportation services and decrease vehicle ownership because personal cars won’t be necessary anymore. So, AI-enabled driverless vehicles can offer great potential to improve efficiency on roads, reduce traffic accidents, increase productivity and become mainstream for consumers.

Final thoughts

As smart cities grow, the need for AI-based systems becomes more apparent, bringing multiple benefits, such as more efficient energy, water, and waste management, reduced pollution, noise, and traffic congestion. It helps in reducing road accidents and fatalities, lower manufacturing costs, and increases service levels.

So, keeping in mind all the above mentioned we can conclude the following:

  • In smart cities, AI can help with new smart applications, such as management of energy and water supply, solutions for new services for inhabitants and businesses
  • AI can be used to improve urban mobility, reduce traffic congestion and air pollution, increase safety and improve transportation systems overall
  • Using AI and machine learning allows authorities and cities to make smarter data-driven decisions that are best for the environment within pollution control and energy consumption
  • AI-based solutions like helmet detection technology can ensure drivers’ safety

About the author:

Rem Darbinyan is the CEO and founder at SmartClick. He is a serial entrepreneur, angel investor, seasoned advisor, author, and keynote speaker with an investment portfolio of over 40 startups. Read more articles about AI on SmartClick blog.