Artificial Intelligence drives plans for safer roads

#A new project from the FHWA (Federal Highway Administration) aims to transform highways with artificial intelligence. Areas where the technology is expected to be useful in the future include improved safety, environmental mapping, bridge capacity insights and smart parking.

The Exploratory Advanced Research (EAR) program is currently soliciting proposals with a deadline of December 5. At that time, it will award the contract or enter into a cooperation agreement. The proposal is seeking research projects that “will bring about transformational and truly revolutionary advances in highway engineering and intermodal transportation in the United States.”

Additionally, the call for proposals stated that “the project will support scientific investigation and research that promotes current knowledge and state-of-the-art technology in the science and technology used in the planning, design, construction, operation, maintenance and management of the nation’s highways” .Strategically, this research will promote and accelerate the development of revolutionary approaches, methods and breakthroughs needed to drive innovation and significantly improve the efficiency of road transportation."

Artificial Intelligence for Highway Traffic

According to FWHA, early research is necessary to support emerging advances in artificial intelligence to help solve complex problems in road transportation. As a result, the FHWA EAR project is now seeking to demonstrate the potential of untested advances in artificial intelligence to solve critical national problems in highway transportation.

FHWA found that examples of AI applications that have the potential to address critical road transportation issues and challenges include:

Safety and Mobility

Vulnerable Road Users - Utilization Artificial intelligence analyzes data or develops solutions targeting the safety of vulnerable road users, particularly on under-researched topics such as safety outside urban settings or in traditionally underserved communities.

Pedestrian, Cyclist and Micromobility Detection – Use machine vision and other AI technologies to analyze the movement of pedestrians, cyclists and micromobility devices on roads and intersections, for all Improved signal performance in these modes for travelers, including those using assistive devices such as wheelchairs.

Pedestrian Wayfinding – Use artificial intelligence to highly automate the dynamic mapping of pedestrian environments, including sidewalks, crosswalks, paths, transportation centers and other public and private spaces.

Bridge Collisions – Use artificial intelligence, including video analysis, to improve understanding of the root causes of collisions of vehicles, especially larger vehicles, with bridges and other highway structures.

Smart Truck Parking - Uses artificial intelligence, including video analytics, to predict and predict the availability of rest stop truck parking spaces with high accuracy. Highly accurate predictions of truck parking spots will make it easier for drivers to find parking spaces, improving safety.

Infrastructure Modernization

Physics-guided AI solutions for predicting asset performance - Typically, AI systems are based on statistical inference, so they may provide information that defies real-life physics constraint results. Integrating physics into artificial intelligence may help bridge the gap between collecting data and effectively using it for decision-making.

Interpreting Sensor Data – It is difficult for asset owners to analyze all the data coming from infrastructure status sensors. This project could explore how artificial intelligence can be used to improve the reliability and automation of converting raw sensor data into actionable information for asset owners.

Cross-cutting areas

Significantly improve processing data or integrating different data by reducing or eliminating the need for manual data pre-processing, or by having experts interpret the complex data of highway transportation Data capabilities.

Combining edge computing with roadside hardware to improve data security and privacy, increase the speed of analysis, and reduce the resources required to move, store, and analyze data in highway transportation .

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