Analysis of vehicle driving behavior on special road segments using context-specific information

Typical telematics and fleet-management systems today use embedded systems attached to the vehicle and get their driving data from their diagnostics port to identify the action of driver and grade it to provide feedback based on their quality of driving to efficiently handle the vehicle and also their driving behavior. Today’s insurance companies provide embedded devices or the customer’s smartphone to analyze basic driving parameters such as speed, rpm, GPS location to understand driver’s braking, acceleration and distance traveled over a period and use it to assess quotes for insurance premium. But most of the solutions above do not consider of context-specific information in the cases of fixed-route scenarios whose details can be understood better in the first place and use it to grade the driver’s performance for the trip more efficiently. In this experiment, a driver’s behavior on a pre-defined route is analyzed on different perspectives by also taking into account of the road context, such as turns, straight road segments, traffic lights, stop signs, etc. and graded accordingly and providing a score to reflect their behavior in each segment of the road as well as a complete score for their tri

Analyzing driving behavior from CAN data using context-specific information

Typical telematics and fleet-management systems today use embedded systems attached to the vehicle and get their driving data from their diagnostics port to identify the action of driver and grade it to provide feedback based on their quality of driving to efficiently handle the vehicle and also their driving behavior. Today’s insurance companies provide embedded devices or the customer’s smartphone to analyze basic driving parameters such as speed, rpm, GPS location to understand driver’s braking, acceleration and distance travelled over a period and use it to assess quotes for insurance premium. But most of the solutions above do not consider of context specific information in the cases of fixed-route scenarios whose details can be understood better in the first place and use it to grade the driver’s performance for the trip more efficiently. In this experiment, a driver’s behavior on a pre-defined route is analyzed on different perspectives by also taking into account of the road context, such as turns, straight road segments, traffic lights, stop signs etc. and graded accordingly and providing a score to reflect their behavior in each segment of the road as well as a complete score for their trip

Context-Aware Sensing and Implicit Ground Truth Collection: Building a Foundation for Event Triggered Surveys on Autonomous Shuttles: Artikel

The LINC project aims to study interactions between passengers and autonomous vehicles in natural settings at the campus of Technical University of Denmark. To leverage the potential of IoT components in smartphone-based surveying, a system to identify specific spatial, temporal and occupancy contexts relevant for passengers’ experience was proposed as a central data collection strategy in the LINC project. Based on predefined contextual triggers specific questionnaires can be distributed to affected passengers. This work focuses on the data-based discrimination between two fundamental contexts for LINC passengers: be-in and be-out (BIBO) of the vehicle. We present empirical evidence that Bluetooth-low-energy beacons (BLE) have the potential for BIBO independent classification. We compare BLE with other smartphone onboard sensors, such as the global positioning system (GPS) and the accelerometer through: (i) random-forest (RF); (ii) multi-layer perceptron (MLP); and (iii) smartphone native off-the-shelve classifiers. We also perform a sensitivity analysis regarding the impact that faulty BIBO ground-truth has on the performance of the supervised classifiers (i) and (ii). Results show that BLE and GPS could allow reciprocal validation for BIBO passengers’ status. This potential might lift passengers from providing any further validation. We describe the smartphone-sensing platform deployed to gather the dataset used in this work, which involves passengers and autonomous vehicles in a realistic setting

Підсистема формування індивідуального плану аспіранта

Анотація Робота містить теоретичні та практичні аспекти заповнення анкети аспірантом, . Метою бакалаврської роботи є проектування, створення і впровадження модулю «Заповнення анети» на веб порталі «Підсистема формування індивідуального плану аспіранта». Для досягнення поставленої мети створено модуль, який спрощує процес заповнення анкети, та поліпшує систему роботи з опрацюванням даних аспіранта в програмі "Підсистема формування індивідуального плану аспіранта".The work contains theoretical and practical aspects of completing the questionnaire by a graduate student,. The purpose of the bachelor's work is the design, creation and implementation of the module "Completion of the questionnaire" on the web portal "Subsystem for the formation of an individual plan of the graduate student" and. To achieve this goal, a module has been created that simplifies the process of filling out the questionnaire and improves the system of working with postgraduate data processing in the program "Subsystem for the formation of an individual plan of the graduate student."Работа содержит теоретические и практические аспекты заполнения анкеты аспирантом,. Целью бакалаврской работы является проектирование, создание и внедрение модуля «Заполнение Анеты» на веб портале «Подсистема формирования индивидуального плана аспиранта» . Для достижения поставленной цели создан модуль, который упрощает процесс заполнения анкеты, и улучшает систему работы с обработкой данных аспиранта в программе "Подсистема формирования индивидуального плана аспиранта"

Програмно-апаратний модуль агента моніторингу параметрів мікроклімату будівлі

В роботі розглянуто теоретичні та практичні аспекти розробки програмного продукту для програмно-апаратного комплексу з використанням сучасних методів і технологій розробки. Метою роботи є розробка програмно-апаратного модуля моніторингу параметрів мікроклімату будівлі і навколишнього середовища, який без участі людини вимірює температуру навколишнього повітря, відносну вологість і атмосферний тиск. Для досягнення мети обґрунтований вибір інструментальних засобів розробки програмного забезпечення з урахуванням особливостей програмної і апаратної архітектури, описана архітектура програмного забезпечення, що розробляється, розроблено програмно-апаратний модуль для моніторингу параметрів мікроклімату будівлі і навколишнього середовища.The paper discusses the theoretical and practical aspects of developing a software product for a hardware and software complex using modern methods and technologies of development. The aim of the work is to develop a software and hardware module for monitoring the parameters of the microclimate of premises and the environment, which without human intervention measures the ambient temperature, relative humidity and atmospheric pressure. To achieve the goal, the choice of software development tools was substantiated, taking into account the features of the software and hardware architecture, the software architecture of the system being developed was described, a software and hardware module was developed for monitoring the parameters of the building microclimate and the environment.В работе рассмотрены теоретические и практические аспекты разработки программного продукта для программно-аппаратного комплекса с использованием современных методов и технологий разработки. Целью работы является разработка программно-аппаратного модуля мониторинга параметров микроклимата помещений и окружающей среды, который без участия человека измеряет температуру окружающего воздуха, относительную влажность и атмосферное давление. Для достижения цели обоснован выбор инструментальных средств разработки программного обеспечения с учетом особенностей программной и аппаратной архитектуры, описана архитектура программного обеспечения разрабатываемой системы, разработан программно-аппаратный модуль для мониторинга параметров микроклимата здания и окружающей среды