RECENT STUDIES OF COMPARATIVE PHILOSOPHY IN THE BALKANS: INTERVIEW WITH JANA S. ROŠKER

ADAS&M

Driver and vehicle behaviour to power train failures in electric vehicles : experimental results of field and simulator studies

New electric power trains can be subject to different failures when compared to those arising in conventional vehicles. The objectives for active safety investigations within the EVERSAFE project were to address vehicle stability under these failure conditions and the driver response to relevant types of failures. Failure conditions that affect the vehicle stability are believed to be significantly different from today’s conventional internal combustion engine cars, and may potentially be a substantial safety problem if not treated in a correct manner. To study these effects, two examples of system failures and their consequences on the driver response and vehicle stability were investigated with the help of three studies. The first two studies investigated a failure of wheel hub motors (WHMs), an emerging technology among the future generation of electric vehicles (EV). The main benefits of a WHM are its controllability, high efficiency, high power density and low weight. However, the direct connection to the wheel comes along with the potential disadvantage in case a failure occurs in the system. The third study conducted within the active safety focus of the EVERSAFE project examined a failure of the regenerative braking (RB) system. The latter is a system designed to convert kinetic energy to chemical energy stored in the energy storage system (i.e. battery) while the vehicle decelerates.EverSaf

Driver Distraction and Inattention

In UDRIVE, the major focus of the work on driver inattention and distraction has been focused on obtaining a better understanding of whether and how drivers manage their secondary task activities — when they choose to engage, what tasks they select, whether they adjust their activity to different situations and whether they are willing to surrender secondary task activities as the primary task of driving becomes more demanding. In other words, the focus is on self-regulation, on how drivers manage their secondary task activity in the context of the dynamics of the traffic and road situation. That management includes the determination not to engage in such tasks in the first place or only to engage in some particular activities. NDS are particularly suited to such an investigation, since experimental studies in driving simulators and even on test tracks tend to suffer from an instruction effect, in that participants are typically instructed to carry out an activity at a given moment. Thus such experimental studies provide insight into how driver attention, driver information processing and driving performance are affected by secondary tasks, but are less useful when research is focused on driver management of task activity

The UDrive dataset and key analysis results

UDrive is a large European naturalistic driving study, sponsored by the European Commission (FP7). Nineteen partners across Europe have come together and, along with stakeholders, defined research questions, developed data acquisition, collected and managed data, and finally, performed a first analysis on the UDrive dataset with respect to driver/rider behaviour related to traffic safety and the environment (ecodriving). This document presents key results of the UDrive analysis performed in UDrive Sub-project 4: Data analysis. It also describes the UDrive dataset and, in brief, how we got here

The UDrive dataset and key analysis results

UDrive is a large European naturalistic driving study, sponsored by the European Commission (FP7).Nineteen partners across Europe have come together and, along with stakeholders, defined researchquestions, developed data acquisition, collected and managed data, and finally, performed a first analysis onthe UDrive dataset with respect to driver/rider behaviour related to traffic safety and the environment (ecodriving).This document presents key results of the UDrive analysis performed in UDrive Sub-project 4: Data analysis.It also describes the UDrive dataset and, in brief, how we got here