A threat based approach to computational offloading for collaborative cruise control

The interaction between discrete components of Internet of Things (IoT) and Intelligent Transportation Systems (ITS) is vital for a collaborative system. The secure and reliable use of Cruise Control (CC) with Cloud and Edge Cloud to achieve complete autonomy for a vehicle is a key component and a major challenge for ITS. This research unravels the complications that arise when Adaptive Cruise Control (ACC) is incorporated into a collaborative environment. It mainly answers the question of where to securely compute Collaborative Cruise Control’s (CCC) data in a connected environment. To address this, the paper initially reviews previous research in the domain of Vehicular Cloud, ITS architecture, related threat modelling approaches, and secure implementations of ACC. An overview application model for CCC is developed for performing a threat analysis with the purpose of investigating the reasons why a vehicle suffers collision. Through the use of interviews, the research analyses and suggests the location of computational data by creating a taxonomy between the Edge Cloud, Cloud and the On-board Unit (OBU) while validating the model

Enabling the Evaluation of Driver Physiology Via Vehicle Dynamics

Driving is a daily routine for many individuals across the globe. This paper presents the configuration and methodologies used to transform a vehicle into a connected ecosystem capable of assessing driver physiology. We integrated an array of commercial sensors from the automotive and digital health sectors along with driver inputs from the vehicle itself. This amalgamation of sensors allows for meticulous recording of the external conditions and driving maneuvers. These data streams are processed to extract key parameters, providing insights into driver behavior in relation to their external environment and illuminating vital physiological responses. This innovative driver evaluation system holds the potential to amplify road safety. Moreover, when paired with data from conventional health settings, it may enhance early detection of health-related complications.Comment: 7 pages, 11 figures, 2023 IEEE International Conference on Digital Health (ICDH

Smartphone-based vehicle telematics: a ten-year anniversary

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this recordJust as it has irrevocably reshaped social life, the fast growth of smartphone ownership is now beginning to revolutionize the driving experience and change how we think about automotive insurance, vehicle safety systems, and traffic research. This paper summarizes the first ten years of research in smartphone-based vehicle telematics, with a focus on user-friendly implementations and the challenges that arise due to the mobility of the smartphone. Notable academic and industrial projects are reviewed, and system aspects related to sensors, energy consumption, and human-machine interfaces are examined. Moreover, we highlight the differences between traditional and smartphone-based automotive navigation, and survey the state of the art in smartphone-based transportation mode classification, vehicular ad hoc networks, cloud computing, driver classification, and road condition monitoring. Future advances are expected to be driven by improvements in sensor technology, evidence of the societal benefits of current implementations, and the establishment of industry standards for sensor fusion and driver assessment