Smartphone-based identification of dangerous driving situations: Algorithms and implementation

• Main Authors: Alexander Smirnov, Alexey Kashevnik, Igor Lashkov, Olesya Baraniuc, Vladimir Parfenov
• Format: Article
• Language: English
• Published: FRUCT 2016-04-01
• Series: Proceedings of the XXth Conference of Open Innovations Association FRUCT
• Subjects: contextual information; driving behaviour; dangerous driving situations
• Online Access: https://fruct.org/publications/fruct18/files/Smi.pdf

In this paper, we demonstrate the concept of the situation analysis of dangerous driving events for smartphones to fully understand the driving situation in a given scenario in a real time and to undertake actions necessary to avoid road accidents. To fulfil these, we utilize a wide array of sensors for creating a consistent and extendable description of most common dangerous situations, a situation model and situation analysis. In the situation model, on-board smartphone sensing signals are used to build up a representation of the environment around and within the vehicle. On top of the situation model, a situation analysis is established to detect driver hazards, according to the given description of the driving situation, and provide a driving strategy to prevent such dangerous situations. The paper describes the details of the algorithms, following by simulation results, which show the feasibility of the proposed algorithm.