Computer vision applications in transportation are becoming more widespread and trending. With the help of AI vision technology, supply chain, and transportation facilities are improving their efficiency and advancing their supply chain and logistics management systems.
Computer vision solutions have digitized the way transportation activities operate. This technology handles the entire transportation flow, from the movement of goods to the logistics process. Additionally, it supports human operation in transportation through AI-visual capabilities, reducing human error and enhancing safety.
Apart from this, computer vision in transportation is also useful for tracking real-time traffic and logistics movements using image detection and object detection technology. It enables automatic number plate recognition (ANPR) and real-time movement tracking, helping logistics management make critical decisions with accurate time estimates, further improving supply chain operations.
What is Computer Vision in Transportation?
Computer vision in transportation is shaping the future of the sector by reducing accident risks and improving cost-effective logistics management. AI-powered image and object detection track traffic patterns like human vision—but with greater speed and accuracy.
According to the World Health Organization (WHO), over 1.35 million people worldwide die in road accidents each year. To mitigate such accidents, industries like healthcare, retail, security, manufacturing, and agriculture are leveraging computer vision solutions effectively.
How Computer Vision is Transforming the Transportation Industry
The global logistics system has faced disruptions due to various global challenges, increasing concerns regarding effective transportation facilities. In response, companies like Uber, Seven Drive, and Deliveroo are leading the way by utilizing computer vision applications in transportation. AI-vision technology enhances transportation by facilitating real-time activities, improving passenger safety, reducing traffic congestion, lowering carbon emissions, and minimizing accident risks.
Several computer vision technologies are revolutionizing transportation, including:
Image segmentation
Object detection
Facial recognition
Edge detection
Pattern detection
Image classification
Feature matching
These technologies play a crucial role in detecting and classifying objects (e.g., road signs and traffic lights), creating 3D maps, estimating motion, and enabling autonomous vehicles.
According to a market research report by MarketsandMarkets, "The global market for AI in transportation was valued at $1.2 to $1.4 billion in 2017 and is expected to grow to $3.5 billion by 2023, at a compound annual growth rate (CAGR) of 12-14.5%."
Applications of Computer Vision in Transportation
Corporations, industrialists, manufacturers, and governments are the biggest users of computer vision technology in transportation. It is particularly useful for governments to manage traffic flow and enhance transportation facilities, contributing to economic growth. Additionally, corporations are developing AI-driven solutions to improve their logistics and transportation efficiency.
