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The State of Intelligent Transportation in 2021

The State of Intelligent Transportation in 2021

Smart car (HUD) and Autonomous self-driving mode vehicle on metro city road with graphic sensor signal.

By Dr. Georges Aoude

It’s reported that road accidents kill approximately 1.3 million people and injure tens of millions more every year. It is imperative to leverage the advancements in various technologies including artificial intelligence (AI) to address this hidden, global epidemic. The use of V2X (vehicle-to-everything) enables communication between vehicles, as well as between vehicles and roadside communication systems for road safety. In fact, within three to five years, this will be a factory feature on almost every vehicle. In addition, various sensor technologies including cameras powered by AI are enabling transportation agencies to understand roadways better than ever before with applications ranging from accurate traffic counts to predicting spots on roads that are most prone to crashes. It’s even predicted that the global intelligent transportation system (ITS) realm is expected to rise to an estimated value of over $63 billion by 2026.

Autonomous vehicles operating within communities as shuttles is one example of this technology currently being utilized to improve safety. For example, autonomous vehicles and roadside AI platforms “communicate” with each other to improve traffic flow and help protect both pedestrians and vehicle riders. Pedestrians and hazards are detected by traffic cameras, which is then processed by the AI “brain” in real-time to send alerts back to the vehicle. This means an autonomous vehicle would get notified of a pedestrian or potential road hazard before it even comes into view. 

Current And Future Utilization of AI Technology For Safer Roadways

Volkswagen announced in 2020 that it planned to install the V2X antennae in the newest generation of its Golf model. Ford also plans to deploy C-V2X technology in all new 2022 vehicles. In Dubai, the goal is to have 25 percent of its transportation autonomous by 2030. One issue that remains is that today’s road infrastructure is not ready to support autonomous vehicle deployments. There is a clear technology gap that needs to be filled to open the door for several opportunities for innovative solutions. However, a number of road agencies, such as the Departments of Transportation in Michigan (MDOT), Florida (FDOT), and Ohio (ODOT & DriveOhio), are working to make road infrastructure smarter to help save lives by deploying AI-enabled traffic systems. This technology also helps these agencies prioritize infrastructure investments and improve their road safety. 

Technology companies like Miovision, Waycare, Derq, and Lyt are all playing an integral role when it comes to AI being incorporated with road infrastructures. They’re leveraging technology to prevent traffic fatalities and sharing their platforms with various agencies to ensure open communication and information. Collaborating with transit authorities and law enforcement is just the beginning for what’s to come in regard to safer roads. Some of these analytics platforms are partnering with automotive companies and cities to provide their AI-powered systems to enable safer and smoother deployments of autonomous vehicles.

AI Technology and Analytics Expanding To Other Industries

With so many industries already incorporating AI technology into company practice, more industries are sure to follow suit as the technology and reporting continues to advance. The automotive insurance can leverage AI with video analytics to streamline claims management. Utilizing AI technology will supply insurance companies with more complete information for claims processing as well as save them time and money. 

There’s no question that the implementation of AI into various other industries is sure to come as those currently utilizing the technology continue to analyze data that had previously never been available. 

Dr. Georges Aoude is the co-founder and CEO of Derq, an MIT-spinoff and leading AI company for edge video analytics to make roads safer, enabling efficient movement of road users and autonomous vehicles (AVs) by adding intelligence to existing cameras to understand all movements and dangerous behaviors in the roads.