Background

Car accidents continue to be a leading cause of death year-over-year. In an effort to make roads safer, vehicles are coming equipped with intelligent features that detect dangerous situations, alert the driver, and even make driving decisions before collisions occur. The advancements in transportation have been significant, yet there is still great need for the development of more complex protection features.

Opportunity

Artificial intelligence (AI) and machine learning (ML) has had a big impact in automotive with the development of autonomous vehicles. Though this topic has generated a lot of buzz, it will be some time before self-driving cars dominate our roads. Vehicles are, however, becoming increasingly intelligent as data from sensors, cameras, radar, voice commands, and other communication systems are shared and analyzed in real-time. With AI/ML technologies, vehicles can go beyond responding to objects in their path to accurately predicting the actions these obstacles may take. As cognitive vehicles become more reliable, so does the safety of our roads.

Impact

Implementing a fast, accurate, reproducible, and cost-effective driver assist framework is the power needed to build safer vehicles and hold a competitive edge in the industry. See how Anaconda Enterprise can improve data science workflows in transportation by contacting us.