Development and Demonstration of Merge-Assist System Using Connected Vehicle Technology
- M. Imran Hayee, Professor, Dir. of Grad Studies, UMD-Electrical Engineering
One potential area to improve driver safety and traffic mobility involves the merge points of two roadways, such as on a typical freeway entrance ramp. Due to poor visibility- because of weather or complex road infrastructure- on many such entrance ramps, it may become difficult for the driver in the merging lane or on the merging entrance ramp to clearly see the vehicles traveling on the main freeway, making it difficult to merge. A fundamental requirement to facilitate many adaptive driver-assistance systems (ADAS) functions, including a merge-assist system, is to accurately acquire vehicle-position information. Accurate position information can be obtained using either sensor-based systems (camera-based, RADAR, LiDAR) or global navigation satellite systems (GPS, DGPS, RTK). For these systems to work well for practical road and weather conditions, advanced techniques and algorithms, which also make the system complex and expensive to implement, are needed. This research project is developing a merge-assist system by acquiring the relative position of vehicles using standard GPS receivers and dedicated short-range communications (DSRC)-based V2V communication. The DSRC-equipped vehicles traveling on the main freeway and on the entrance ramp periodically communicates position information with each other. Using that information, the relative trajectories- the relative lane and position of all DSRC-equipped vehicles traveling on the main freeway- is calculated and recorded in real-time in the vehicle traveling on the entrance ramp. Finally, a merge-time cushion also is calculated potentially to assist the driver of the ramp vehicle to safely merge onto the freeway.
- OST-R summary report for this project (PDF)
- May 2015 Roadway Safety Showcase presentation (579 KB PDF)
- Start date: 06/2014
- Project Status: Active
- Research Area: Transportation Safety and Traffic Flow