## 1.2 Introduction
The research hypotheses are formulated as follows:  
* H0 (Null Hypothesis): There is no statistically significant difference in the speed-density and flow-density functional relationships obtained for continuous and periodically interrupted traffic flow conditions on the representative road segments of the selected regional road, and therefore, the same mathematical formulation of \"speed-density\" and \"flow-density\" models can be used for modeling traffic flow characteristics on the observed regional road, both in continuous and interrupted traffic stream conditions. * H1 (Alternative Hypothesis): There is a statistically significant difference in the speed-density and flow-density functional relationships obtained for continuous and periodically interrupted traffic flow conditions on the representative road segments of the selected regional road, and therefore, two alternative mathematical formulations of the \"speed-density\" and \"flow-density\" models need to be used to separately model the traffic flow characteristics under continuous and interrupted traffic stream conditions on the observed regional road. The specific contributions of this research stem from (1) determining the calibrated \"speed-density\" equations and regression functions representative of modeling continuous and interrupted traffic stream conditions on regional (lower tier) roads in Croatia by fitting the selected macroscopic traffic flow models to empirical data collected from an open road segment and a road segment with signalized intersection from the regional road ZC5210; (2) obtaining valuable insights into the distinctions between specific values of basic traffic flow parameters at boundary and critical points of \"speed-density\" and \"flow-density\" fundamental traffic flow diagrams of selected macroscopic traffic flow models, i.e., between the values of free flow speed, critical speed, critical density, jam density and practical road capacity representative of continuous and interrupted traffic stream conditions; (3) obtaining more realistic \"speed-density\" and \"flow-density\" relations due to the fact that empirical traffic flow density values are determined directly based on the actual number of vehicles present on the observed road segments in discrete time intervals, visible from the recorded aerial footage, i.e., they are not estimated based on occupancy or calculated indirectly by dividing empirical flow and speed values; (4) the possibility of applying the research findings to other geographic regions to identify the approximate functional formsof \"speed-density\" and \"flow-density\" fundamental diagrams, which could be used for modeling continuous and interrupted traffic stream conditions on other lower tier roads (regional and local roads) in the Republic of Croatia, as well as in comparable road categories in other countries. Regional and local road authorities could use these fundamental diagrams to make more informed decisions related to investment in road infrastructure, road traffic management, designing new and maintaining existing networks of regional and local roads. The aerial footage of observed road segments recorded in the scope of this research can be potentially used by researchers for the purpose of developing and integrating various algorithms and software based on artificial intelligence and machine learning, which would enable automatic video data processing, i.e., automatic detection and tracking of movements of individual vehicles in a traffic stream, automatic extraction of relevant traffic flow parameter values and automatic fitting of selected traffic flow models to collected empirical data. The subsequent sections of this paper are organized in the following manner. The following chapter gives an overview of research related to this paper. Chapter 3 defines the macro and micro study areas within which drone-based aerial traffic flow video recording was conducted to collect the input data necessary for performing correlation and regression analysis between relevant traffic flow parameters.