@incollection{DatkoSeepoldMart{\´i}nez Madrid2016, author = {Datko, Patrick and Seepold, Ralf and Mart{\´i}nez Madrid, Natividad}, title = {Stress map based information system for increasing road safety}, booktitle = {Mobile networks for biometric data analysis. - (Lecture notes in electrical engineering ; 392)}, editor = {Conti, Massimo and Mart{\´i}nez Madrid, Natividad}, isbn = {978-3-319-39700-9}, doi = {10.1007/978-3-319-39700-9_11}, institution = {Informatik}, pages = {135 -- 144}, year = {2016}, abstract = {Stress is becoming an important topic in modern life. The influence of stress results in a higher rate of health disorders such as burnout, heart problems, obesity, asthma, diabetes, depressions and many others. Furthermore individual's behavior and capabilities could be directly affected leading to altered cognition, inappropriate decision making and problem solving skills. In a dynamic and unpredictable environment, such as automotive, this can result in a higher risk for accidents. Different papers faced the estimation as well as prediction of drivers' stress level during driving. Another important question is not only the stress level of the driver himself, but also the influence on and of a group of other drivers in the near area. This paper proposes a system, which determines a group of drivers in a near area as clusters and it derives the individual stress level. This information will be analyzed to generate a stress map, which represents a graphical view about road section with a higher stress influence. Aggregated data can be used to generate navigation routes with a lower stress influence to decrease stress influenced driving as well as improve road safety.}, language = {en} }