Car navigation – computing routes that avoid complicated crossings

Abstract

Personalized navigation and way-finding are prominent research areas of location-based service (LBSs). This includes innovative concepts for car navigation. Within this paper, we investigate the idea of providing drivers a routing suggestion which avoids ‘complicated crossings’ in urban areas. Inexperienced drivers include persons who have a driver’s license but, for whatever reason, feel uncomfortable to drive in a city environment. Situations where the inexperienced driver has to depend on a navigation device and reach a destination in an unfamiliar territory may be difficult. Preferences of inexperienced drivers are investigated. ‘Fears’ include driving into ‘complicated crossings’. Therefore, the definition and spatial characteristics of ‘complicated crossings’ are investigated. We use OpenStreetMap as a road dataset for the routing network. Based on the topological characteristics of the dataset, measured by the number of nodes, we identify crossings that are ‘complicated’. The user can choose to compute an alternative route that avoids these complicated crossings. This methodology is one step in building a full ‘inexperienced drivers’ routing system, which includes additional preferences from the user group, for example, as avoiding left turns where no traffic light is present.