About Safe Road Solutions
History
Safe Road Solutions Inc. (SRS) specializes in road safety data analytics, especially utilizing smartphone sensor technology and AI models to extract detailed road and user data, to support data-driven risk identification and proactive, systemic safety improvements. By leveraging smartphone sensor data and AI, transportation agencies can effectively prioritize infrastructure investments, implement targeted safety countermeasures, and reduce accident rates.
SRS provides advanced data analytics for curve safety assessments, curve countermeasures, and intersection to enhance overall road safety. For curve safety, SRS provides an innovative solution using smartphone and AI to effectively and efficiently extract curve geometry, Ball Bank Indicator, superelevation, and advisory speed on curves to identify potential risks.
For curve countermeasures, SRS focuses on automatically and accurately detecting and classifying curve signage, geospatially registering sign locations, and comparing existing signage to MUTCD-compliant sign design to identify deficiencies in the network.
For intersections, SRS focuses on near-miss analysis using images and AI, signal timing enhancement for vulnerable road users (e.g., pedestrian and biker), and innovative intersection design through driver behavior analysis using smartphone and eye tracking, including RCUT (Restricted Crossing U-Turn), roundabout, and DDI (Diverging Diamond Interchange). Senior safety is also quantitively analyzed using sensor data.
The technologies were originally developed by Dr. Tsai at the Georgia Institute of Technology (GT) through research projects sponsored by the NCHRP Innovation Deserving Exploratory Analysis (IDEA) program. A spin-off company from GT, SRS retains an exclusive license to implement the technologies. The previous version of the technologies had been implemented on 18,000 centerline miles of roadways in Georgia. SRS is currently working on curve safety for a SS4A project in Georgia and a feasibility study in Alabama.
Founder
Dr. Tsai, the founder of Safe Road Solutions, is a distinguished faculty member at Georgia Tech and a well-recognized leader in applying intelligent, sensor-based, and spatially-enabled systems for advancing roadway safety condition assessment methods. For the past 18 years, Dr. Tsai has served as Pl and led a multidisciplinary team in developing and validating systems and methods for curve finder, sign detection and recognition, curve sign design planning through multiple competitively selected research projects sponsored by the National Academy of Science (NAS) NCHRP Innovation Deserving Exploratory Analysis {IDEA) program, the U.S.DOT Commercial Remote Sensing and Spatial Information Technologies (CRS&SI) program, and the Georgia Department of Transportation (GDOT). The research outcome has been developed and patterned through Georgia Tech. Dr. Tsai has a strong history of success in implementing complex, large-scale IT-base systems at GDOT. He was appointed as Associate Editor of the ASCE Journal of Computing in Civil Engineering. He had served in the Expert Task Group (ETG) of the U.S. National Strategic Highway Research Program (SHRP 2) for more than 5 years.
Our Integrated Solutions
By combining a data collection app with a curve finder, we support a safe road experience by allowing data to be collected at a lower cost and more frequently.
Products
Data Collection App
Data Collection App
Data Collection App
Our app involves calibration, data collection of real-time advisory speeds, and discrepancy detection.
Curve Finder
Data Collection App
Data Collection App
The curve finder combines sign detection and recommended signage.
Clients
City of Milton
Auburn University
Auburn University
We are performing effective safety condition assessments on Hopewell Road and Freemanville Road for the City of Milton, Georgia. This project is part of the larger initiative Safe Streets For All, which is funded by the U.S. Department of Transportation as one of 385 SS4A grants awarded throughout the country.
Auburn University
Auburn University
Auburn University
Because existing programs to improve the safety of horizontal curves are costly in terms of both time and resources, the Alabama Department of Transportation (ALDOT) is exploring a new Mobile-based Curve Safety Evaluation Tool (MCSET) (developed in the NCHRP IDEA Project 214 (1) and GDOT project (RP 20-22 (2)) as a cost-effective alternative method to assist the curve safety evaluation. The purpose of this pilot study is to critically assess the practicality of the MCSET method for performing curve safety evaluations on ALDOT’s roads and provide recommendations on its potential applications, including determining adequate advisory speed and MUTCD-compliance curve sign design.