European Journal of Engineering Science and Technology ISSN2538-9181 ฀ Corresponding Author E-Mail Address: yavuz.delice@yalova.edu.tr 2538-9181/ © 2019 EJEST. All rights reserved. Estimation of the Intrazonal Travel Time of Different Modes for the Home-Based School Trips Using Regression Model Yavuz Delice 1* , Halit Özen 2 , and Ehsan Amirnazmiafshar 3 1 Yalova University, Department of Transportation Engineering, Faculty of Engineering,Yalova, 77200,Turkey. 2 Yildiz Technical University, Department of Civil Engineering, Faculty of Civil Engineering, Istanbul, 34220, Turkey. 3 Istanbul Technical University, Department of Transportation Engineering, Faculty of Civil Engineering, Istanbul, 34469, Turkey. ARTICLE INFO ABSTRACT Keywords: Intrazonal trips, travel time, home-based school trips, regression mode. In this study, the procedures for the estimation of intrazonal travel time by using the OD survey is developed with more than 13000 participants conducted in Denizli city in Turkey. The city area was subdivided several times as to provide 214 traffic analysis zones (TAZ). For home-based school trips, the intrazonal travel time of three different categorize of modes are studied including walking, public transport, and all trip modes together. The all trip modes model contains walking, public transport, private vehicle, and subscription bus. The correlation between the average intrazonal travel time and the most related factors, which have the important effect on it, is designated from the survey. Some geographic and especially socio-economic characteristics are investigated which received the less attention in the past studies. The results show that the population density of the TAZ has the highest effect on the intrazonal travel time of walking mode. The number of links in the network has the highest influence on the intrazonal travel time of the public transport, and this factor for all trip modes together is the population of the TAZ. Regarding these results and by using the regression model, the equation for each category is obtained. The finding shows that the best-fit trend for walking mode is logarithmic, for public transport and all trip modes models are polynomial. By testing the different values for transition points, the transition point for each category is provided which are 10000 people/area for walking mode, 800 link in the network for public transport and 15000 people for all trip modes. Introduction Sometimes, data related to the features of travel distribution patterns and street network are not easily accessible to explicate the trips in cities. For instance, average intrazonal travel time in cities affected by the characteristics of trips; environment and user profile which are not available to