{"667259":{"#nid":"667259","#data":{"type":"event","title":"PhD Defense by SomDut Roy","body":[{"value":"\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003EPh.D. Thesis Defense Announcement\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EEmergency Vehicle Preemption Strategies using Machine Learning to Optimize Traffic Operations\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003EBy\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003ESomdut Roy\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003EAdvisor(s):\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EDr. Angshuman Guin (CEE) \u0026amp; Dr. Michael Hunter (CEE)\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003ECommittee Members:\u003C\/span\u003E\u003C\/strong\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cspan\u003EDr. Michael Rodgers (CEE), Dr. Randall Guensler (CEE), Dr. Richard Vuduc (CSE), Dr. Abhilasha Saroj (Oak Ridge National Laboratory)\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003EDate \u0026amp; Time: \u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003Cspan\u003E\u003Cspan\u003EApril 21, 2023 at 11:30 am\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u003Cspan\u003E\u003Cspan\u003E\u003Cstrong\u003E\u003Cspan\u003E\u003Cspan\u003ELocation: \u003C\/span\u003E\u003C\/span\u003E\u003C\/strong\u003E\u003Cspan\u003E\u003Cspan\u003E(Hybrid) SEB 122 and Zoom: \u003Ca href=\u0022https:\/\/gatech.zoom.us\/j\/991863429\u0022\u003Ehttps:\/\/gatech.zoom.us\/j\/991863429\u003C\/a\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/span\u003E\u003C\/p\u003E\r\n\r\n\u003Cp\u003E\u0026nbsp;\u003C\/p\u003E\r\n\r\n\u003Cp\u003EEmergency-Response-Vehicles (ERVs) operate with the purpose of saving lives and mitigating\u003Cbr \/\u003E\r\nproperty damage. Emergency-response Vehicle Preemption (EVP) is implemented to provide the\u003Cbr \/\u003E\r\nright-of-way to ERVs by displaying the green indications along the ERV route. Two EVP\u003Cbr \/\u003E\r\nstrategies were developed as part of this effort. First, a strategy was developed, defined as\u003Cbr \/\u003E\r\n\u201cDynamic-Preemption\u201d (DP), that utilizes Connected-Vehicle (CV) technology to detect, in real\u003Cbr \/\u003E\r\ntime, the need for preemption prior to the ERV reaching the vicinity of an intersection. The DP\u003Cbr \/\u003E\r\nstrategy is based on several generalized traffic demand and simplified traffic flow assumptions.\u003Cbr \/\u003E\r\nSecond, a machine learning approach was utilized to develop an EVP call strategy that sought\u003Cbr \/\u003E\r\nto (1) preemptively clear queues at intersections prior to ERV arrival, (2) create a \u0022delay-free\u0022\u003Cbr \/\u003E\r\npath for the ERV, and (3) minimize excess delay to the conflicting traffic in the event of an EVP\u003Cbr \/\u003E\r\ncall. The ML approach utilizes currently available vehicle detection data streams and is trained\u003Cbr \/\u003E\r\nbased on simulated EVP scenarios. Existing field strategies and the developed strategies were\u003Cbr \/\u003E\r\ntested under varying scenarios, on a simulated signalized corridor testbed. It was observed that\u003Cbr \/\u003E\r\nthe proposed methodologies showed tangible improvement over the existing baseline\u003Cbr \/\u003E\r\nalgorithms for EVP, both in terms of ERV travel time and delay to the conflicting movements. In\u003Cbr \/\u003E\r\nsummary, this research is expected to lay the foundation for use of novel computational\u003Cbr \/\u003E\r\napproaches in solving the EVP problem in traffic ecosystems with limited CV penetration, with\u003Cbr \/\u003E\r\nthe aid of microsimulation.\u003Cbr \/\u003E\r\nKeywords: Traffic Signals, Emergency Response Vehicle, Emergency Vehicle Preemption,\u003Cbr \/\u003E\r\nEmergency response Vehicle Preemption, preemption, dynamic preemption, Connected Vehicle\u003Cbr \/\u003E\r\ntechnology\u003C\/p\u003E\r\n","summary":"","format":"limited_html"}],"field_subtitle":"","field_summary":[{"value":"\u003Cp\u003ESee attached\u003C\/p\u003E\r\n","format":"limited_html"}],"field_summary_sentence":[{"value":"Emergency Vehicle Preemption Strategies using Machine Learning to Optimize Traffic Operations"}],"uid":"27707","created_gmt":"2023-04-11 19:08:06","changed_gmt":"2023-04-11 19:08:06","author":"Tatianna Richardson","boilerplate_text":"","field_publication":"","field_article_url":"","field_event_time":{"event_time_start":"2023-04-21T11:30:21-04:00","event_time_end":"2023-04-21T14:02:21-04:00","event_time_end_last":"2023-04-21T14:02:21-04:00","gmt_time_start":"2023-04-21 15:30:21","gmt_time_end":"2023-04-21 18:02:21","gmt_time_end_last":"2023-04-21 18:02:21","rrule":null,"timezone":"America\/New_York"},"location":"SEB122","extras":[],"groups":[{"id":"221981","name":"Graduate Studies"}],"categories":[],"keywords":[{"id":"100811","name":"Phd Defense"}],"core_research_areas":[],"news_room_topics":[],"event_categories":[{"id":"1788","name":"Other\/Miscellaneous"}],"invited_audience":[{"id":"78761","name":"Faculty\/Staff"},{"id":"78771","name":"Public"},{"id":"174045","name":"Graduate students"}],"affiliations":[],"classification":[],"areas_of_expertise":[],"news_and_recent_appearances":[],"phone":[],"contact":[],"email":[],"slides":[],"orientation":[],"userdata":""}}}