What Is The Future Of Artificial Intelligence AI In Transportation?

What Is The Future Of Artificial Intelligence AI In Transportation?

We’ve seen the transportation industry undergo a series of changes and turning points in the last several decades. We’re now at a pivotal point where breakthroughs are being achieved in the form of Artificial Intelligence, whether that’s via self-driving cars, road condition monitoring, or traffic flow analysis.  

Smart urban planning has become a priority for municipalities and authorities worldwide, with transportation businesses also looking to AI as a tool for addressing common transport-related problems as well as cutting costs. Monitoring vehicle dwell times, parking violations, and traffic density trends will also help with the management of smart cities.  

The global market forecast for AI in transportation is expected to reach $3.5 Billion by 2026. Investing in Artificial intelligence can help agencies in leveraging advanced technologies such as computer vision and machine learning in order to shape a future of transportation where passenger safety is a priority, accidents are reduced and there is less congestion on roads.  

Let’s take a look at some significant developments in the transport sector that with the help of AI are already in operation or are expected to become a reality soon.

Traffic Flow Analysis

Most cities face the same problems when it comes to traffic and congestion. With the effects of urbanization and the rise of private vehicle use, the number of cars on the road is unfortunately only increasing. This is not only affecting the environment by contributing further to global warming but also costing both time and money, adding more stress to the daily lives of citizens. AI is set to solve the issue of traffic congestion by utilizing data collected from sensors and cameras embedded in roads where large volumes of traffic are typically present. The data, which is sent to a cloud, serves as a pivotal point for analyzing patterns of traffic, giving municipalities valuable insights about its current state, allowing them to effectively make predictions and improve the flow of traffic. This is typically made possible through big data analytics and an AI-powered system.  

Other valuable insights and benefits from this data processing include reducing the number of accidents on the road as well as predicting and avoiding possible disruptions such as road blockages. Travelers will be provided with important information regarding the current state or any ongoing events on roads as well as be notified about the best route to their destination, helping them achieve a more seamless journey, with less hassle and inconvenience.

Automatic Traffic Incident Detection

Detecting traffic accidents is amongst the most well-researched subjects of ITPs (Intelligent Transportation Systems) and AI transportation. CCTV cameras and detectors placed along various road networks, provide the foundations for automated, uninterrupted monitoring. Powered by computer vision, these detectors offer constant data flow that assists TMCs with their traffic operations.  

Operators at control centers can then respond when alerted to an anomaly in traffic conditions such as an accident, and they can respond as soon as possible to any potential disturbance that the AI-driven systems have detected.

Parking and Traffic Regulation Enforcement

AI is set to also have a positive impact on parking and traffic regulation enforcement. Through a wide range of IoT sensors and cameras used to collect data, it will be possible to detect the occupancy status of parking spots, immediately informing drivers and helping them find parking for their vehicles, conveniently and effortlessly, avoiding further congestion in cities.  

Camera-based AI systems will additionally inform authorities about potential vehicles that are violating traffic laws. For example, an AI system can detect the current speed of the vehicles passing on the road and can generate potential alerts to patrolling officers if any of the vehicles happen to be overspeeding. Officers will be able to identify vehicles by their number plates, car model, and type and color, charging them for any active traffic violation that they commit. 

Although these systems have already been deployed by various countries, the adoption of AI-enabled traffic monitoring systems is still an ongoing process for others yet it’s something that is expected to progress shortly due to the many benefits such as reducing traffic violations, improving safety on the road, and reducing congestion.

Automated License Plate Recognition

Automated license plate recognition (ALPR) involves the use of computer vision-based camera systems which are attached to street poles, highways, and overpasses, capturing information regarding license plates, location, as well as the date and time of a potential violation. Once an image has been captured by a camera, the data is then fed and transferred onto a central server. 

These highly advanced features of AI-based systems could prove extremely useful to authorities when it comes to detecting and preventing crime on the road. Automated license plate recognition can incorporate the use of new camera systems which are designed specifically for this purpose, or it could alternatively use existing CCTV, along with road-rule enforcement cameras. This will help the police with the corroboration of evidence regarding whether or not a given vehicle was at the scene of a crime as well as establishing or disproving a person’s alibi.  

Аutomated license plate recognition can also be applied in other transport-related fields such as the recognition of travel patterns, particularly high monitoring, parking management, and toll management. It is expected that this will further prevent cars from being used in illegal activities as well as aid car dealership companies in keeping track of their fleets and assets.

Autonomous Vehicles

Self-driving cars are perhaps one of the most exciting and highly anticipated future applications of AI in transportation and they seem to be getting closer to becoming a reality. 

Autonomous vehicles are essentially cars that will ”drive themselves’’ through the application of AI technology which will merge a wide range of sensors, such as LiDAR, and RADAR, as well as cameras to comprehend the surroundings and make decisions based upon the information when navigating and planning routes. The IoT-based sensors will be able to generate a tremendous amount of data, which will transfer valuable insights and information that along with AI algorithms will help with various computer vision techniques, machine learning, and object character recognition.  

Apart from self-driving cars, autonomous taxis, and self-driving trucks have also been making serious headlines in the transportation industry. Both have made their debut in countries such as Japan and the US. In Tokyo, autonomous taxis are already being used for public transportation, although for now it is done by the presence of a driver on standby, just in case there is an emergency.  

In the US, autonomous trucks have been deployed by several big companies for the transportation of goods which has brought the nation multiple benefits including one of great importance – reducing the environmental impact of freight transport and optimizing deliveries and movement of goods which decreases congestion on roads and helps with monetary loss.  

A report published by McKinsey shows that driverless cars and trucks can reduce administrative and maintenance costs by 45%. The use of AI-powered autonomous vehicles has not become a norm for now, but it is expected to develop soon.

Delay Predictions

The benefits of AI in the transportation sector are expected to stretch far beyond just vehicles on land and traffic management. It’s estimated that AI-based technology will revolutionize the aviation sector by solving conventional problems such as flight delays. By leveraging and merging computer vision with data lake technology, aviation companies can put a greater emphasis on improving customers’ journey experience by reducing wait time and offering better quality service, at an improved, expedited pace. 

This alone is set to make a significant impact on the aviation industry as it will not only enhance the reputation of airlines but it will also cut financial loss as well as improve customers’ overall experience as delays are often the primary cause for dissatisfaction amongst people who fly.   

With the assistance of AI, aviation companies will also be able to monitor real-time data regarding potential delays and inform passengers before the flight so that they can plan their schedules accordingly. Through the processing of weather information in real-time, records, data, and patterns, AI will be able to effectively analyze and predict potential disruptions that might cause flight cancellations or delays.

Road Condition Monitoring

Road damage is a significant issue in the USA, with estimates suggesting that it costs drivers more than $3.0 Billion per year. When used in transportation, computer vision in AI can detect road defects successfully, as well as assess the surrounding infrastructure by looking for changes in the asphalt and concrete. The algorithms which use vision for identification will be able to spot potholes as well as establish the precise amount of road damage so that the relevant authorities can swiftly take action and improve road maintenance. 

The purpose of Automated Pavement Distress (PD) detection is to improve road maintenance allocation efficiency, while at the same time increasing road safety, saving time, and money, and limiting road accidents.

Driver Monitoring

One of the biggest breakthrough achievements of AI in transportation comes down to monitoring, analytics, as well as estimation and prevention, in particular when regarding accidents on the road. While many people would assume that is not such a big issue and that human error now and then is normal, the reality is that each year, there are around 56,000 road accidents due to sleepiness and fatigue in the USA alone, resulting in over 1,500 deaths.  

By adding computer vision to car cabins, safer driver monitoring will be possible as this technology will use face detection to predict a change in a person’s emotional state and make an estimate of the driver’s pose to look out for signs of drowsiness.  

These types of advanced driver assistance systems will ensure the safety of the driver, the passenger, as well as other people on the road. They can promptly alert drivers whenever their abilities to drive are impaired due to fatigue so that they can take the appropriate measures and pull over to rest. Additional alerts will signal and alert for signs of distraction, adding an extra layer of safety. 

Drone Taxis

Another innovative and exciting prospect of AI in transportation is its application in drone taxis. It is estimated that AI-based drone taxis will be able to facilitate intracity transportation to reduce the strain on existing urban infrastructure. This could provide a valuable solution to municipalities that are already under tremendous pressure as they struggle to meet the demands of growing populations when it comes to smart urban planning.   

Helicopters operating without a pilot for example offer a valuable solution that is set to combat carbon emissions, eliminate traffic congestion as well as reduce the need for expensive infrastructure construction plans. Drone taxis will ultimately help people reach their destinations quicker, and more seamlessly, minimizing their commute time. 

An example of this type of technology already becoming a reality occurred in China where a recent demonstration of autonomous aerial vehicles was made possible for 17 people as they experienced smart air mobility for the first time. It’s predicted that these types of taxis will be designed to fly remotely piloted or autonomously, avoid obstacles, and take off, fly, and land with incredible precision every time.  

Some delivery companies have already employed the use of drones for delivery services and with great success. AI can offer assistance with GPS navigation, delivery drops, detecting obstacles and avoiding them, as well as emergency and contingency management. This timely and precise management of drone deliveries will tremendously help companies scale up their delivery operations. 

We’re excited to see what’s around the corner as advances in technology bring newer, more exciting possibilities for innovations in the sector. Many experts in the field agree that smart cities, along with Artificial intelligence hold the potential for building a better future for all by boosting worldwide operational efficiency, improving sustainability, and making roads, highways, and intersections safer for all.