A lane-level road network model with global continuity. (October 2016)

• Record Type: Journal Article
• Authors: Zhang, Tao; Arrigoni, Stefano; Garozzo, Marco; Yang, Dian-ge; Cheli, Federico
• Is Part Of: Transportation research. Volume 71(2016)
• Page Start: 32
• Page End: 50
• Publication Date: 2016-10
• Subjects: Lane-level -- Road network -- Digital map -- Continuity -- Vehicle; Transportation -- Periodicals; Transportation -- Technological innovations -- Periodicals; 388.011
• DOI: 10.1016/j.trc.2016.07.003
• Languages: English
• ISSNs: 0968-090X

Abstract

Highlights: A lane-level road network model is proposed which possesses the global continuity for map route. Intersections are modeled considering all the geometrical, topological and traffic features. The rarefying algorithm is developed to extract the lane parameters under a given precision threshold. The joint lanes are generated to approximate turning trajectories with limited data requirement. Abstract: An increasing number of Intelligent Transportation System (ITS) applications require high accurate vehicle positioning, e.g., positioning at the lane-level. This requirement motives the development of modeling the road network at the lane-level. In this paper we propose a novel lane-level road network model. It can be considered an improvement to existing models in its capability of representing the road and intersection details at the lane-level in a uniform and precise way. As a result, the model can guarantee the global continuity for arbitrary map route, which better approximates the real vehicle trajectory. In addition, the map construction algorithms are also developed. Following the proposed methods, the lane parameters can be extracted efficiently under flexible precision requirement, and intersections with varying appearances can be precisely modeled with limited extra data. Experiments were performed to verify the proposed model in representing the lane-level geometrical and topological details of an urban area of Milan. The results also demonstrate the effectiveness of the map construction methods.