# Road Safety Management of Uncontrolled Access Points:
## 2 Materials and Methods  
The selected case study is the state road SS18, an important element of the Southern Italy road network oriented in a North-South direction. The case study road segment has a length of 106.250 km (39\({}^{\circ}\)55\({}^{\prime}\)29.82\({}^{\prime\prime}\) N, 15\({}^{\circ}\)46\({}^{\prime}\)7.13\({}^{\prime\prime}\) E and 39\({}^{\circ}\)3\({}^{\prime}\)54.42\({}^{\prime\prime}\) N, 16\({}^{\circ}\)5\({}^{\prime}\)27.43\({}^{\prime\prime}\) E are the lat-long coordinates of the start and end points, respectively) and can be classified as a secondary rural road (C1 class road) for its technical and constructive characteristics, in accordance with the national regulations [32], with the function of penetration towards the local network; moreover, in many sections it constitutes an urban crossing, passing through built-up areas. The selected road is a two-lane road with one traffic lane in each direction and with no median treatments. There is no significant difference in the roadway geometry between the rural sections and the urban ones. The process utilised geographic information system (GIS) software aimed at creating a collaborative GIS framework to support the management of several sources of information. Furthermore, the GIS project can be easily updated and is configured as a functional tool for the immediate planning of adequate safer strategies. The traffic crash data used in this study were directly acquired from the CRISC database [33]; this road safety monitoring centre collects information on fatal and injury accidents occurring within the regional area. Furthermore, the information on the geographic position of each accidental event allows for easy GIS-based data management. For the case study section, the accident data were acquired over a five-year period (from 2016 to 2020); the output of this activity is a 482-item crash database. The road crash data acquired for this study do not include accidents with only material damage, but at least one person is injured in the accident. Accident precise location and accident consequences (number of fatalities and injured persons) are available for each accident. The GIS-based spatial analysis of accesses was carried out by identifying and characterizing each access point along the selected road section. A total of 857 access points were analysed; the elemental categorisation is shown in Figure 1. The main criteria for the classification of access points are the following: (i) the presence/absence of access management measures; (ii) travel direction (N-S = North-South or S-N = South-North); (iii) urban or rural area. Satellite images, Google Maps, Google Earth, Google Street View, and QGIS tools supported data collection. In particular, each access point was deeply analysed by collecting a set of qualitative and quantitative variables mostly related to geometry. Data on the specific access point include the angle between the access and the main roadway, the access width, and the entry/exit radius. Furthermore, an analysis of the connection transition shapes is carried out. Access connection transition shape plays a basic role as it influences the correct interpretation of the intersection scene. [PERSON] et al. [34] classified four types of shapes: perpendicular edge, rectangular apron, flare/taper, and curved radius. In their study they assigned some scores to each shape according to different design purposes; in particular, the curved radius access allows the best definition of the edge for motorists and turning vehicles, on the other hand, it implies the most difficult process of construction [34]. According to AASHTO [29], flared access points are preferred, as they are more easily discernible from intersections. Figure 1: Summary of the elements characterised in the study.