Merge Assist System Using GPS and DSRC Based Vehicle-to-Vehicle Communication

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Merge Assist System Using GPS and DSRC Based Vehicle-to-Vehicle Communication

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2019-01

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Abstract

One potential area to improve driver safety and traffic mobility is around merge points of two roadways e.g., at 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 on the merging/entrance ramp to clearly see the vehicles travelling on the main freeway, making it difficult to merge. A fundamental requirement to facilitate many ADAS functions including a merge assist system is to accurately acquire vehicle positioning 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 are needed which make the system complex and expensive to implement. In this report, the author proposes a merge assist system by acquiring the relative positioning of vehicles using standard GPS receivers and DSRC based V2V communication. The DSRC equipped vehicles travelling on the main freeway and on the entrance-ramp will periodically communicate their positioning information with each other. Using that information, the relative trajectories, relative lane and position of all DSRC equipped vehicles travelling on the main freeway, will be calculated and recorded in real time in the vehicle travelling on the entrance ramp. Finally, a merge time cushion will also be calculated which could potentially be used to assist the driver of the ramp vehicle to safely merge into the freeway.

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University of Minnesota M.S.E.E. thesis. January 2019. Major: Electrical Engineering. Advisor: Imran Hayee. 1 computer file (PDF); viii, 33pages.

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Hussain, Shah. (2019). Merge Assist System Using GPS and DSRC Based Vehicle-to-Vehicle Communication. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/202088.

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