# Multi-Objective Routing and Categorization of Urban Network Segments for Cyclists
## 2 Materials and Methods
### Experiments
#### 2.3.2 Data Collection  
This section will describe how the data collection and estimation of the parameter values was performed. Note that the data used for this study for each link are historical data. Driving against the flow of traffic (contraflow cycling): The values that these parameters can take are \([0,1]\) and depend on the direction of the cyclist at each link. The data were taken from the Google Maps platform. In addition, note that in the case of using links with \(k=p1,p2,b1\), i.e., links of sidewalks, crosswalks, and bike lanes, the value of the parameter will be 0 since at these links, bicycle users do not encounter vehicles moving in the opposite direction. Average speed: This categorization refers to road sections used by cars. Data collection is again carried out through Google Maps. Specifically, at a time of reduced traffic (e.g., 2:00 a.m.), where the density of vehicles tends to be 0, we have the maximum speed of crossing a link N\({}_{\text{i,j,k}}\). The reason for measuring at minimum density (and therefore maximum speed) is to have a more conservative approach to this variable which is directly related to the safety criterion. Another reason for this choice is to try to obtain a diverse and representative sample of average speeds. It is stated that if the measurements were taken--for example--at rush hour, the average speeds on motorways would not differ from those on single-lane access roads (narrow streets), resulting in a sample with low diversity, in which the feeling of insecurity of cyclists riding on motorways where the average speed can be high would not be reflected. For the minimum density hour, therefore (2:00 a.m.), the travel time for each roadway is measured via Google Maps in minutes. The length of the roadway is divided by the travel time, giving us the average speed on that roadway. It should also be noted that--again--in the case of using links with \(k=p1,p2,b1\), i.e., links of sidewalks, pedestrian crossings, and cycle lanes, the value of the parameter will be 0 since on these links the bicycle users do not encounter vehicles. Width of the road to the right--overtaking possibility: A study by the Dutch Ministry of Transport found that a minimum overtaking distance of 1.5 m is required for cars to safely overtake bicycles at speeds of up to 30 km/h. This distance is increased to 2 m for speeds up to 50 km/h and 3 m for speeds up to 70 km/h [37]. In this study, after first defining the average speed for each link N\({}_{\text{i,j,k}}\), these sections will be categorized into overtaking and non-overtaking roads. However, it appears from the study area that the links where the average speed is above 30 km/h can only be found in the Avenues where there are at least 2 lanes in each direction and overtaking is eminently feasible. In the case of using links with \(k=p1,p2,b1\), i.e., links of pavements, footpaths, crossings, and cycle lanes, the value of the parameter will be 1 since on these links cycle users are not confronted with vehicles wishing to overtake them and are, therefore, considered to treat these links in the same way as they would treat a road link (\(k=r1,r2\)) where overtaking is possible regarding this variable. It is worth noting that there is also no overtaking possibility at link 1, 82, r1 (turn from Eratosthenous Street to Vasileos Konstantinou Avenue). Although there is overtaking ability both at Eratosthenous Street and at the Avenue, at this link there is no overtaking possibility for a vehicle when there is a turn (see Figure 4). Bus transit: The value of the parameter related to the presence of bus traffic in a network link is again binary (0 or 1). The data collection is performed through the website of OASA (Athens Urban Transport Organization) [38]. In Figure 5, all the roads within the boundaries of the study area are outlined, through which, according to OASA, bus and trolley lines pass.