چکیده مقاله
Short term travel time prediction on urban arterials is an important component of Advanced Traveler Information Systems ATIS and Advanced Traffic Management Systems ATMS It can also be a key input to evacuation and emergency responses This study presents robust travel time prediction models that work efficiently for time variant turn movement shares in both congested and non congested conditions that urban arterials typically experience throughout the day and/or during special events The state space notion of traffic processes was found useful and State Space Neural Network models are proposed Models were developed for travel time prediction on links, arterials, and routes multiple links on different arterials Mean absolute percentage errors of modeled travel times on arterilas for through, left, and right movements ranged between 12 3% and 34 6% for testing data sets For routes, the MAPE ranged between 8 5 and 10%
کلیدواژهها
نویسندگان
Ghassan Abu-Lebdeh
Department of Civil Engineering, American University of Sharjah
Timothy J. Likens
Well Associates, Novi, Michigan, USA
شیوه ارجاع
Abu-Lebdeh, Ghassan and J. Likens, Timothy,1388,Arterial Travel Time Prediction with State-Space Neural Networks under Time-variant Turn Movements,8th International Congress on Civil Engineering,Shiraz
ارائهشده در
مجموعه مقالات هشتمین کنگره بین المللی مهندسی عمران21 اردیبهشت 1388 · شیراز