## 2 Methodology  
### Study Area and Data  
The background of this study stems from a need for activity-based analysis of travel behaviors as part of a Czech national project, \"Smart City--Smart Region--Smart Community\" [23]. The study focuses on the Usti nad Labem catchment area, referred to as the district area. In general, a district area in the Czech Republic represents a functional region consisting of a central city and surrounding municipalities that are dependent on the central city in terms of jobs and services. The district of Usti nad Labem is located in the northwest part of the Czech Republic, shown in Figure 1. The main city (Usti nad Labem) and its surrounding 23 municipalities are home to 90,378 and 26,538 inhabitants, respectively, for a total of 116,916 residents [24] The Czech Land Survey Office provided zonal boundary data for the study area [25]. In recent decades, the city of Usti nad Labem had a dramatic transition from an industrial-based economy to service-oriented one. The city is a regional center with important administrative, cultural, and educational institutions, including a university. There is a complex railway junction connecting many national and international cities in the Usti nad Labem city center, making the city an important transportation hub. Census data (CD) provided by the Czech Statistical Office [26] was used to generate a synthetic population for the study area together with household travel surveys (HTS) to reflect travel demand and geographic datasets (GD) containing useful information about the buildings, facilities, and land use of the study area in order to increase the realism of travel demand assignment. Census data are collected every ten years in the Czech Republic, and the latest available census was conducted in 2011 (CD-2011). The CD-2011 provides demographics, travel attitudes, housing conditions, and work and education locations relative to home locations (e.g., in the same municipality or in another municipality of the same district) for each inhabitant. A demographic transition algorithm was applied to this dataset to reflect a realistic sociodemographic structure for the year 2016, as explained in the next subsection. Demographic transition was implemented by utilizing a dataset provided by the Czech Statistical Office containing birth rates, mortality rates, and the information about the residential mobility of inhabitants [27; 28; 29]. HTS represents travel data of a sample of the citizens containing transport mode preferences, daily activity purposes, daily activity chains, origins and destination (OD) points of trips, trip purposes, trip distances, and trip durations. Two household travel surveys were utilized here, one is at national level (Czech Republic HTS) and the other is at the city level (City HTS). The Czech Republic HTS was conducted by the Transport Research Center (CDV) in 2017, and this dataset is openly available [30]. The City HTS survey was conducted in 2016 by the NMS Research Center [31]. City HTS provided information about trips starting or ending in the city of Ustí nad Labem, while Czech Republic HTS was used to simulate travel demand for the remaining 23 municipalities. Czech Republic HTS and City HTS datasets provided travel behaviors of 21,209 and 2054 respondents, respectively. However, after some data filtering and cleaning (see the next subsection), the sample size was reduced to 12,397 and 937 respondents, respectively. The census and travel survey datasets do not contain weights showing how many respondents a specific entry represented. The weights of each sample were assigned based on their age and gender in the datasets. Furthermore, HTS datasets only provided information about inhabitants having trips on the day of the survey.