Smart Transit Solutions & AI Use Cases to Ease The Traffic Madness

 

Nowadays, accidents, traffic congestion, lack of parking spaces, and poor road conditions are the four villains that frequently create traffic congestion and haunt cities worldwide.

But can Artificial Intelligence in transportation help fight them and make commuting more comfortable, convenient, and safe? 

 

Because construction of roads, bridges, and underpasses and the building of alternative modes for public transport systems are becoming insufficient to lessen traffic blocks and manage them.

Moreover, it’s getting more difficult to handle each passing day. Consequently, it becomes crucial to introduce a modern & intelligent system for resolving these issues.

 

Numerous practical solutions introduced by the world’s largest transportation companies indicate that it is possible. And we don’t have to wait for fully self-driving cars to benefit from AI.

 

The changes are taking place right in front of our eyes. So, without further delay, let’s move to the subject and learn more about the practical application of AI to smartly tackle these chronic headaches of all the nations around the globe.

 

Increasing Roadblocks, Pollution, and Traffic Congestions

 

In 1900, the United States — the only country that manufactured automobiles at the time – had 4192 vehicles. The number of automobiles on the road is projected to be over 600 million, and with current manufacturing rates, this figure is expected to quadruple in the next 30 years.

 

The issues are the same all over the globe. So, Our cities are congested and polluting, and getting in a car during rush hour is almost impossible in many locations. Not to mention the true endurance test that drivers face.

 

So, we must explore solutions that lower the number of automobiles in cities. Also, we must equip urban infrastructure and adapt cars with tools that effectively offset the negative effects of technological globalization.

Hence, the Internet of Things and artificial intelligence are assisting in developing a new class of intelligent transportation systems (ITS) for vehicle rail, marine, and airplane transportation.

 

The Advantages of Using AI in Transportation

 

According to Market Data Forecast, the worldwide transportation AI market will be worth around $3.87 billion by 2027 and growing exponentially at a CAGR of 15.8% between 2021 and 202.7 

 

It’s no big surprise that more and more firms are adopting these solutions. And the advantages of integrating AI technology in transportation are genuinely far-reaching, and its future seems promising. 

 

The key benefits of using AI in transportation include:

 

  • Increasing transportation safety;
  • Discovering upcoming market trends;
  • Lessening traffic blocks;
  • Minimizing greenhouse gas emissions, air, and sound pollution;
  • Enhanced transportation design and management;
  • better urban space management and recapturing specific urban areas for residents; analysis of transportation needs and pedestrian behavior

 

Now, let’s move on to a few major use cases of AI in transportation which helps to reduce traffic jams, increase road safety and help businesses worldwide thrive faster.

 

Major Use Cases of AI for Transit Solutions

 

1.)  Advanced Driver-assist Technologies

Artificial intelligence is already present. For example, many car manufacturers have long begun incorporating semi-autonomous driving features into their vehicles.

Such as advanced driver-assistance systems (ADAS) to assist with parking procedures, maintain vehicle control in adverse weather conditions, and avoid collisions.

 

Given the shocking number of people killed in road accidents each year (an estimated 1.35 million, as per World Health Organization estimates), it’s easy to see why security awareness and maximizing safety is a top priority when implementing AI in this field.

 

 

2.)  Personal Assistance

A different, more chatty approach to providing AI-powered support to drivers includes using the same voice-based gadgets we’ve grown accustomed to in our homes.

Natural language processing is used in these tools to comprehend user requests and conduct several functions, such as making a call, switching radio stations, or delivering information on vehicle problems.

 

However, the possibilities opened up by artificial intelligence in transportation extend well beyond that since the transition from aid to autonomous driving may be a matter of time.

 

3.)  Automatic Number – Plate Recognition

ANPR systems are a significant sub-branch of computer vision-based traffic management applications, although they focus on individual cars rather than the overall flow of vehicles.

 

HD cameras set on street poles, infrared sensors to provide 24/7 monitoring, and image processing software to recognize vehicle registration plates via OCR are examples of such solutions (optical character recognition).

 

As a result, they are valuable in quantifier management and security activities, such as:

  • Analysis of travel duration to improve road planning
  • Vehicles that violate traffic laws will be identified by law enforcement.
  • Toll management will collect toll payments from road users electronically.

 

4.)  Smart Parking

There are few things more awful than traffic and speeding tickets. One of them is the never-ending search for a parking spot in a congested lot in the city center.

Fortunately, artificial intelligence can help us and make this “difficult quest” a little easier with the help of cameras and computer vision, which can be used in indoor and outdoor metropolitan environments.

 

These methods can be incredibly beneficial in a variety of ways and scenarios:

 

  • Vehicle counting to estimate queue time accurately
  • Unauthorized parking can be detected via license plate matching.
  • Time tracking to make ticket billing and payment easier
  • Parking lot security cameras are used to detect suspicious activity.
  • Parking availability indicators are linked with free slot detection.

 

 

5.)  Monitoring of road conditions

In the United States, potholes cause three billion dollars in automobile damage yearly. Intelligent algorithms can warn vehicles of potential road hazards and monitor the state of the road surface, alerting authorities in advance of dangerous places that will need to be repaired soon.

 

This is made possible by connecting the camera to ADAS, which uses machine learning to capture real-time information from the road surface as it moves.

 

The motorist can thus be notified not just of roadway damage but also of wet surfaces, ice, potholes, or harmful road debris. This enhances traveler safety, prevents accidents, and saves drivers and the city money.

 

 

6.)  Automatic Detection of Traffic Incidents

Video surveillance has been used on the roads for a long time. Still, it wasn’t until AI solutions supplemented the system that it became feasible to detect traffic accidents more efficiently, respond faster, and deliver information to traffic users in real-time.

 

We can identify several forms of accidents by connecting cameras within its system, employing computer vision technology, and outfitting vehicles with intelligent sensors.

Intelligent algorithms save lives, avert serious accidents, and warn drivers of potentially dangerous circumstances by offering safer routes.

 

 

The following are the most often observed traffic incidents:

  • pedestrians or animals crossing the street;
  • vehicles traveling too quickly or slowly;
  • vehicles obstructing the passage
  • Debris detection on the road;
  • detecting vehicles traveling in the opposite direction

 

7.)  Driver Surveillance

Finally, a broad range of artificial intelligence technologies operate directly in the car’s interior and affect the drivers. Three of them deserve more attention:

 

  • Driver tiredness monitoring – by recognizing the driver’s face and measuring the position of the head, the system can detect the driver’s drowsiness and emotions, preventing an accident.
  • The system sends a warning when the driver becomes distracted, such as when they reach for their cell phone, drift out of their lane, or turn around in the back seat to talk to fellow passengers.
  • When the driver is not reacting/responding and does not control the vehicle, the automobile initially attempts to wake the driver by braking and tugging safety belts. If that fails, the car pulls over and calls an emergency.

 

AI in transportation: The Road towards Future

 

Some major changes in urban transportation are expected to occur soon. Travelers will be given transportation alternatives for their journeys that do not necessitate vehicle ownership but instead rely on renting and sharing with the rest of the community (i.e. shared mobility).

However, the increasing usage of vehicles in cities may result in greater traffic congestion, higher energy consumption, harmful emissions, visual effects, and land use expenditure.

 

Furthermore, empty vehicles running on highways to avoid parking or conduct driver-free deliveries may generate a higher volume of journeys in addition to the availability of more vehicles.

 

In conclusion, it is necessary to carefully assess the broad spectrum of potential impacts of artificial intelligence applications and the endless usage of AI Services on transport systems against the changes they will bring to mobility, considering the impact on land use, social inclusion, and more.

So, embracing AI will definitely show the pathways to unlock great enigmas known to mankind.

 

Vishnu Narayan

Vishnu Narayan is a content writer, working at ThinkPalm Technologies, a software & mobile app development services company focusing on technologies like BigData, IoT, and AI. He is a passionate writer, a tech enthusiast, and an avid reader who tries to tour the globe with a heart that longs to see more sunsets than Netflix!

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