{"id":48059,"date":"2024-04-30T11:35:18","date_gmt":"2024-04-30T15:35:18","guid":{"rendered":"https:\/\/engineering.jhu.edu\/ams\/?post_type=news&p=48059"},"modified":"2025-09-17T13:40:41","modified_gmt":"2025-09-17T17:40:41","slug":"the-turning-point-for-better-traffic-light-cycles","status":"publish","type":"news","link":"https:\/\/engineering.jhu.edu\/ams\/news\/the-turning-point-for-better-traffic-light-cycles\/","title":{"rendered":"The turning point for better traffic light cycles"},"content":{"rendered":"

Ryan Jasper, a junior in the Department of Applied Mathematics and Statistics<\/a>, has created a modeling technique that could help traffic engineers better adjust the timing and operations of left-turn signals at intersections, potentially improving traffic flow for vehicles trying to turn.<\/p>\n

Unlike typical traffic engineering models based on assumptions about the frequency of cars arriving at the intersection in the opposite lane, Ryan Jasper\u2019s model relies on different information: how long it takes for each car to make a complete left turn. This allows his model to understand the flow of traffic coming from the opposite direction without having to collect actual data on it.\u00a0 Jasper will describe his approach at the Whiting School of Engineering\u2019s annual Design Day on May 1.<\/p>\n

\u201cWhat makes our approach unconventional is that rather than making assumptions about the distribution of times it takes for cars to clear an intersection, we incorporated a random parameter linked to the preceding car\u2019s time,\u201d said Jasper, who was advised on the project by Fred Torcaso, a senior lecturer in the Department of Applied Mathematics and Statistics.<\/p>\n

\u201cThis approach challenged conventional wisdom but yielded insights that could revolutionize traffic analysis.\u201d<\/p>\n

The student\u2019s analysis found something unexpected: When only a few cars were waiting to turn left, the wait times for each car to make the turn varied wildly. But as more cars entered the queue, wait times for each to make the turn evened out to a consistent distribution.<\/p>\n

\u201cBy understanding and optimizing left-turn wait times, not only can individual commuters experience smoother, more efficient journeys, but the collective efficiency of entire traffic networks can be greatly enhanced, offering tangible benefit,\u201d said Jasper.<\/p>\n","protected":false},"template":"","class_list":["post-48059","news","type-news","status-publish","hentry","news_categories-applied-mathematics","news_categories-research","news_categories-student-experience"],"acf":[],"yoast_head":"\nThe turning point for better traffic light cycles | Department of Applied Mathematics and Statistics<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/engineering.jhu.edu\/ams\/news\/the-turning-point-for-better-traffic-light-cycles\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" 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