Applications of AI in Transport: Safe and Improved Road Network Operations

How is AI making transport safer and improving the road network operations



Artificial intelligence is a broad area of computer science that makes machines function like a human brain. It is used to address issues that are difficult to clarify using traditional computational techniques. This technology is already having a profound impact on the way we interact with the world around us. Like a powerful set of technologies that can help humans solve everyday problems, AI has significant applications in several fields. One such field is transport, where AI applications are already disrupting the way we move people and goods. From scanning traffic patterns to reduce road accidents and optimizing sailing routes to minimize emissions, AI is creating opportunities to make transport safer, more reliable, more efficient, and cleaner. There are multiple applications of AI in both advanced economies and emerging markets that exemplify the contributions these evolving technologies can make to economies.


Automated Accidents Detection 

In many cases, it is hard to fully understand the relationships between the characteristics of the transportation system; therefore, AI methods can be presented as a smart solution for such complex sustainability. Many researchers have demonstrated the advantages of AI in transport. An example of that includes transforming the traffic sensors on the road into a smart agent that detects accidents automatically and predicts future traffic conditions. Also, there are many AI methods used in transport such as ANNs. ANNs can be used for road planning, public transport, traffic incident detection, and predicting traffic conditions. It is classified into supervised and unsupervised learning methods. Supervised methods include Support Vector Machine (SVM), Probabilistic Neural Network (PNN), Radial Basis Network (RBN), K-Nearest Neighbors and Decision Tree, etc. while unsupervised NNs include greedy layer-wise and cluster analysis.

Though autonomous vehicles, or AVs, get much media attention, AI applications in transport go far beyond driverless vehicles and are already having an impact. On a much broader scale, AI can help solve a variety of problems in transport related to safety, reliability, and predictability, as well as efficiency and sustainability. 


Road Safety

Road safety for both drivers and pedestrians is a major public health issue. Road traffic-related deaths reached 1.35 million in 2016, up from 1.25 million in 2013.7 Most of those deaths occurred in low-income countries. While inadequate infrastructure, in particular, poor roads and vehicles without modern safety equipment play a role in the high death toll, human error is an important contributor. Human error like speeding, distraction, and drunk driving plays a part in more than 90 percent of accidents on roads. Tesla’s first attempt at an AV reduced accident rates by 40 percent when self-driving technologies were activated. While AVs may not be ready for mass deployment in emerging markets in the short term, some ambitious estimates project there will be 10 million AVs on the road by 2020, with 1 of 4 cars being driverless in 2030.


Traffic Management Operations

Many AI algorithms are well-suited to solving complex problems such as those posed by traffic operations, and they are being used around the world. One example is SurTrac from Rapid Flow Technologies, a Carnegie Mellon University spinoff, which provides solutions for intelligent traffic signal controls. It has coordinated traffic flows at a network of nine traffic signals in three major roads in Pittsburgh. Rapid Flow helped reduce travel times by over 25 percent on average and wait times declined by an average of 40 percent during the trial. It also reduced emissions by 20 percent.

Just like in Pittsburgh, many cities around the world are beginning to use AI to help them solve traffic flow problems. In Bengaluru, India, where traffic jams are common, Siemens Mobility built a monitoring system that uses AI through traffic cameras that detect vehicles and calculate the density of traffic on the road and then alter traffic lights based on real-time road congestion. Alibaba, China’s e-commerce giant, launched “City Brain” to minimize road congestion, utilizing data from traffic lights, CCTV cameras, and video recognition to make suggestions for traffic flow management. 

AI holds the promise of dramatically increasing productivity and efficiency in several sectors, including transport, and these changes are not in some distant future; they are happening now. AI is already helping to make transport safer, more reliable and efficient, and cleaner.

Some applications include drones for quick life-saving medical deliveries in Sub-Saharan Africa, smart traffic systems that reduce congestion and emissions in India, and driverless vehicles that shuttle cargo between those who make it and those who buy it in China.