Due to increasing traffic, air and noise pollution, and reduced access to urban areas, the need for new, greener and more sustainable mobility solutions is essential.
Machine learning, artificial intelligence, and the use of big data all cater to a modern mobility approach. Artificial intelligence creates opportunities to transition to an environmental-friendly, individualised mobility that is autonomous whenever possible and highly adaptable to the environments.
The development of the automotive industry is constant, and the use of artificial intelligence helps to focus on innovation and product development. Self-driving technology is significant and new mobility systems and new market players constantly appear on the market. Self-driving cars, robot-taxis and autopilot systems are also under development by established brands such as Tesla, Über and Google.
Artificial Intelligence also gained popularity in vehicle manufacturing and with the use of optimised assembly, fast and safe processes, the detection of faulty items and defects are made much easier. Production processes became more predictable and reliable.
The role of Mobility in the Development of Transportation
Accessible, sustainable, and smart technology becomes the new norm for building the future of transportation. Smart Mobility supports the growth of economies worldwide but also helps logistic supply chains, improves labour market opportunities, and opens new markets. With the use of Smart Mobility, an improved and more reactive transportations system can be created via e-scooters, shared bikes and shared cars and buses. Drone technology is applied more and more frequently to support fast and efficient deliveries and connected Autonomous Vehicles are seen as a new transportation option.
Six ways Artificial Intelligence helps to create Smart Mobility
1. Smart Cities
Artificial intelligence helps de-urbanise cities and enable people to use autonomous vehicles to commute faster and cheaper. During the travel time, they can stay productive to improve their life quality and use the time for work when it was not possible before.
2. Mobility-as-a-System (MaaS)
MaaS allows users to optimise their transportation journey by planning and managing their means of transportation online. With the use of smartphones, they can book and pay for their trips quickly and safely. Thorough tracking systems, the rides are coordinated to enable efficient ride-passenger matching, and through monitored rides, standards and safety regulations adhere more than any time before. Ridesharing helps travellers share autonomous cars on optimised routes, reduce travel expenses, commute time, and be part of a social experience that often supports their mental well being.
3. Smart Grid Management
Smart grid management facilitates thoughtful planning, cost reduction, and a reliable and stable grid. Coordinating the grid of an autonomous fleet helps to optimise both sides' requirements by improved charging times and acknowledging individual requirements. A smart grid helps to save money and optimise vehicles needed on the roads.
4. Self-Driving Vehicles
While driverless vehicles aren't mainstream yet, the future of transportation is undoubtedly focused on self-driving vehicles. Currently, public travelling options are tested and piloted and some of the transportation brands are already using these vehicles in real traffic.
The focus on self-driving vehicles is to create a safer and more reliable way of transportation by utilising computer vision, deep learning systems, and big data. Artificial intelligence can collect data from various sources on the road, such as cameras, radar, traffic prediction data, and sensors. Planning routes, according to data, also helps a faster and less congested arrangement.
5. Monitoring Driver Performance
Through artificial intelligence, drivers are continuously monitored to ensure peak performance and safety. Enabling systems to track driver behaviour, alertness, attention to the road, and posture helps monitor when drivers are tired, or not engaged with the car or the road. Technical features such as adjustable seats, mirror settings and automatic airbags also support an improved environment for safety and attention.
6. Traffic Predictions and Congestion Management
With artificial intelligence, big data, and analytics, traffic patterns and congestions can be anticipated through the network of cameras and sensors on the roads. Using AI, new, shorter and less congested routes can be planned, while road safety and reliability is constantly promoted.
Conclusion
While artificial intelligence brings a myriad of opportunities to the transportation market, it is essential to acknowledge that we need to balance machine and humanity. While artificial intelligence can create a safer, more economical, greener and more reliable transportation network, we need to ensure that companies don’t stop employing people, but rather find a way to create an improved and safe environment for all.