# Influence of the Analytical Segment Length on the Tram Track Quality Assessment
## 1 Introduction  
A prerequisite for safe and reliable rail system operation is an adequate assessment of rail-track quality based on the detected track geometry deviations or irregularities. Longitudinal level, horizontal alignment, gauge, cross-level, and twist are the five track geometry parameters used to effectively describe the track condition [1]. Track quality is defined by calculating the track quality index (TQI) on both high-speed and conventional standard gauge rail-track systems. This numerical value represents the relative condition of the abovementioned track geometries [2] over a track segment of a specific length. Segments on which the TQIs are calculated are defined as linear track geometry datasets with homogeneous characteristics of track-geometry degradation influential factors [3]. These factors can be classified into three groups: influential factors of designed alignment; influential factors of track structure; and influential factors of rail traffic [4]. The degradation of the track geometry is primarily due to the action of dynamic vehicle loads caused by irregularities on the contact surface of the wheels and rails or in the horizontal track alignment. Higher track-exploitation intensity and the speed of rail vehicles result in a higher degradation rate [5, 6]. In terms of structure, using rails with a higher steel hardness and its elastic fastening can slow down the degradation process [7, 8]. The design of the horizontal track alignment also has a significant effect, especially the track curvature--thedegradation of the track geometry on horizontal curves is faster than on the straight parts of the route [9; 10; 11]. In addition, one must not ignore the elements that could influence the overall track geometry condition on a segment, such as switches, stops, bridges, or level crossings. According to [3], the first studies of the conventional track geometry degradation analyses began during the 1980s and 1990s, when the track data availability, especially in a digital format suitable for thorough analysis, was very modest. Historically, the data were collected with track-recording cars, which produced statistically processed data (e.g., standard deviations) for fixed 100 m, 200 m, or 1 km long segments. This \"fixed segment\" was too rigid to demonstrate the actual degradation of the geometry along the track. Consequently, more sophisticated segmentation processes were developed. Today, track-recording cars can collect and store high-resolution track data, ensuring that identified individual segments behave as uniformly as possible throughout the track exploitation process. There are different procedures for TQI calculation adopted in railway systems around the world. Most of them use longitudinal level and horizontal alignment at least to represent the condition of the track [12]. TQIs calculated on segmented rail networks can be sorted into two main categories: (1) objective or single TQIs, which are expressed separately for each geometry parameter; and (2) artificial or synthetic TQIs, which combine and merge different track geometry parameters into a single index [13; 14]. The main difference between them is the base on which the TQI is calculated: as a standard deviation, an average value, or a weighted value over a track segment [15]. Once calculated, TQIs are compared to maximum permitted values, most often depending on the rail line speed, and then the decision on track maintenance is made. In addition to different calculation approaches, different TQIs are expressed for different track segment lengths, usually 3-25, 25-70, and 70-200m long [16]. The 200m long segment is used most often, but in some cases, a particular track or entire network is evaluated based on only one TQI value [14]. Recent studies of tram track quality used different techniques for determining the track segment: based on the type of track construction [17] or based on the horizontal elements of track alignment (straight, curve, and curve with transition curve segments) [18].