George Yannis
  • Home
  • Education
  • Research
  • Publications
  • Scientific
  • Conferences
  • Engineering
  • en
    • el
Select Page

Roussou S., Ziakopoulos A., Ventura R., Yannis G., “Predicting Pedestrian Violations Using Object Detection and Deep Learning: A Comparative Study of LSTM & GRU Models”, Proceedings of the International Symposium Navigating the Future of Traffic Management, Athens, 29 June – 3 July 2025.


ID pc573
Presentation
Full Text
Tags

Search

X Bluesky X
Wikipedia Scopus X













Tags

accident analysis (241) information systems (328) international comparisons (243) road safety measures (261) road safety strategy (180) speed (40) driver behaviour (490) culture (77) driver distraction (87) pedestrians (59) cyclists (40) motorcyclists (74) enforcement (29) young drivers (39) older drivers (66) cognitive impairment (97) alcohol (23) road infrastructure (220) road safety audit (18) junctions (8) motorways (15) road design (20) road equipment (15) weather conditions (24) intelligent systems (92) telematics (94) traffic automation (59) driving simulator (136) naturalistic driving (84) field surveys (94) statistical modelling (381) big data (94) machine learning (61) artificial intelligence (11) impact assessment (69) eco-driving (11) urban mobility (194) electro mobility (19) public transport (15) traffic management (158) traffic simulation (16) parking (20) smart cities (32) metro systems (22) large events (12) intermodal transport (33) transport networks (164) transport terminals (43) logistics (45) COVID-19 (13) vehicle (15) survey (19) automation (5) electro mobolity (1) multi-modal transport (1) micromobility (14)

Archive

Recent Items

  • “Integrating Road Safety into Traffic Control Policy”, at the 3rd workshop on Traffic Control Systems for Future Mobility organized by Tongji University (Shanghai, 4 December 2025)
  • Sekadakis M., Garefalakis T., Moertl P., Yannis G., “Analyzing SHAP values of XGBoost algorithms to understand driving features affecting take-over time from vehicle alert to driver action”, Displays Volume 91, January 2026, 103263.
  • Li K., Gu M., Yuan W., Lu Y., Yannis G., “In full-touch HMI mode: How does car-following pressure, task complexity, and speed affect driver’s visual distraction characteristics?”, Accident Analysis & Prevention, Volume 223, December 2025, 108264.
  • Yannis G., Nikolaou D., Kaselouris K., Furian G., “Infrastructure use and related safety feeling of different road user types globally”, IATSS Research, Volume 49 (3), pp. 387-398, October 2025.
  • Andreas Englezos, “Driving Behavior Analysis Using Connected Vehicle Data”, Diploma Thesis, NTUA, School of Civil Engineering, Athens, November 2025.

George D. Yannis, Professor, Department of Transportation Planning and Engineering, National Technical University of Athens
Iroon Polytechniou 9, Zografou 157 73, Athens, Tel.: (+30) 210.772.1326, Fax: (+30) 210.772.1454, e-mail: geyannis@central.ntua.gr

© Copyright 2000-2025 George Yannis
/* ----------------------------------------- */ /* View: Tag Cloud View - start */ /* ----------------------------------------- */ .nrso-tag a { margin: 2px 4px; padding: 4px 8px; border: 1px solid #eaeaea; background-color: #efefef; color:#555; border-radius: 4px; display: inline-block; transition: none; } .nrso-tag a:hover { background-color: #0083eb; color: #fff; } /* ----------------------------------------- */ /* View: Tag Cloud View - end */ /* ----------------------------------------- */ /* ----------------------------------------- */ /* View: Recent items - start */ /* ----------------------------------------- */ .wpv-loop a { color: #2ea3f2; } .wpv-loop a:hover { color: #eaeaea; } .recent-items { margin-top:10px 0; padding:0; } .recent-items li { border-bottom: 1px solid #f1f1f1; padding-bottom: 10px; margin:0; line-height: 21px; } /* ----------------------------------------- */ /* View: Recent items - end */ /* ----------------------------------------- */
/* ----------------------------------------- */ /* Content Template: Publication Template - start */ /* ----------------------------------------- */ .nrso-featured-image { width: 40%; float: left; margin: 0 20px 10px 0; } .nrso-metadata-table { } .nrso-metadata-table .first-col { border-left:3px solid #4f9dc2; background:#f5f5f5; width: 30%; font-weight: bold; } .listview-doi { color: #ffa544; font-size:21px; padding-left:10px; } .listview-ppt { color: orange; font-size:21px; padding-left:10px; } .listview-pdf { color: #e60000; font-size:21px; padding-left:10px; } .listview-manuscript { color: #575757; font-size:21px; padding-left:10px; } /* ----------------------------------------- */ /* Content Template: Publication Template - end */ /* ----------------------------------------- */