Crowdsourcing-Driven Road Condition Marking and Traffic Diversion System

Abstract

Crowdsourcing technology has been widely used in navigation platforms, but the data judgement mechanism often causes data misjudgment, which is mainly reflected in two aspects: (1) the criterion is inflexible for judging data; (2) the lack of ability to integrate extreme data. This paper elaborates the dynamic programming data judgement algorithm driven by crowdsourcing mechanism for road condition information, and provides a novel method for eliminating the mechanization. The traffic diversion model and the road width assessment algorithm are further proposed, which enrich the function of the existing navigation systems. Based on the proposed algorithms and model, a road condition marking and traffic diversion system is realized. Theoretical analysis and system testing show that the algorithm can effectively judge the accuracy of the data and improve both the robustness and flexibility of the judgment criterion.