☆ 4.6 Article

A Data-Driven, Vehicle-Independent Usage Monitoring System for Shared Fleets: Assessing Vertical and Longitudinal Wear

IEEE VEHICULAR TECHNOLOGY MAGAZINE (2022)

Online Assessment of Driving Riskiness via Smartphone-Based Inertial Measurements

Simone Gelmini et al.

Summary: This study aims to design a 4-dimensional driving-style assessment system based on smartphone inertial sensor data. By processing dynamic features in detail, it is possible to comprehensively classify driving riskiness without relying on privacy-sensitive smartphone usage monitoring.

IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS (2021)

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Article Computer Science, Artificial Intelligence

A Novel Crash Detection Algorithm for Two-Wheeled Vehicles

Simone Gelmini et al.

Summary: This paper presents a crash detection strategy for motorcycles, utilizing GPS/GNSS and inertial measurements collected by telematic e-Boxes. The proposed approach improves detection performance by detecting and classifying crash-like situations, better generalizing motorcycle dynamics with respect to specific vehicles and driving styles. The approach has been tested and validated with experimental data covering motorsport and naturalistic scenarios.

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES (2021)

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Article Chemistry, Analytical