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Energy-efficiency and safety became an important factor for car manufacturers. Thus, the cars have been optimised regarding the energy consumption and safety by optimising for example the power train or the engine. Besides the optimisation of the car itself, energy-efficiency and safety can also be increased by adapting the individual driving behaviour to the current driving situation. This paper introduces a driving system, which is in development. Its goal is to optimise the driving behaviour in terms of energy-efficiency and safety by giving recommendations to the driver. For the creation of a recommendation the driving system monitors the driver and the current driving situation as well as the car using in-vehicle sensors and serial-bus systems. On the basis of the acquired data, the driving system will give individual energy-efficiency and safety recommendations in real-time. This will allow eliminating bad driving habits, while considering the driver needs.
Functionally impaired people have problems with choosing and finding the right clothing. So, they need help in their daily life to wash and manage the clothing. The goal of this work is to support the user by giving recommendations to choose the right clothing, to find the clothing and how to wash the clothing. The idea behind eKlarA is to generate a gateway based system that uses sensors to identify the clothing and their state in the clothing cycle. The clothing cycle consists of (one and more) closet, laundry basket and washing machine in one or several places. The gateway uses the information about the clothing, weather and calendar to support the user in the different steps of the clothing cycle. This allows to give more freedom to the functionally impaired people in their daily life.
Besides the optimisation of the car, energy-efficiency and safety can also be increased by optimising the driving behaviour. Based on this fact, a driving system is in development whose goal is to educate the driver in energy-efficient and safe driving. It monitors the driver, the car and the environment and gives energy-efficiency and safety relevant recommendations. However, the driving system tries not to distract or bother the driver by giving recommendations for example during stressful driving situations or when the driver is not interested in that recommendation. Therefore, the driving system monitors the stress level of the driver as well as the reaction of the driver to a given recommendation and decides whether to give a recommendation or not. This allows to suppress recommendations when needed and, thus, to increase the road safety and the user acceptance of the driving system.
Vehicles have been so far improved in terms of energy-efficiency and safety mainly by optimising the engine and the power train. However, there are opportunities to increase energy-efficiency and safety by adapting the individual driving behaviour in the given driving situation. In this paper, an improved rule match algorithm is introduced, which is used in the expert system of a human-centred driving system. The goal of the driving system is to optimise the driving behaviour in terms of energy-efficiency and safety by giving recommendations to the driver. The improved rule match algorithm checks the incoming information against the driving rules to recognise any breakings of a driving rule. The needed information is obtained by monitoring the driver, the current driving situation as well as the car, using in-vehicle sensors and serial-bus systems. On the basis of the detected broken driving rules, the expert system will create individual recommendations in terms of energy-efficiency and safety, which will allow eliminating bad driving habits, while considering the driver needs.
Saving energy and road safety became important in the last decades, hence several driving assistant systems were developed that help to improve the driving behaviour. However, these driving systems cover the area of either energy-efficiency or safety. Furthermore, they do not consider the reaction of the driver to a shown recommendation and the driver stress level. In this paper, the decision process of showing a recommendation to the driver in an energy-efficient and safety relevant driving system is presented. The decision process considers the driver's reaction to a shown recommendation and the driver stress in order to increase the user acceptance and the road safety. The results of the evaluation showed that the driving system was able to show recommendations when needed, while suppressing recommendations when the driver ignored a recommendation repeatedly or when the driver was in stress.
Detecting the adherence of driving rules in an energy-efficient, safe and adaptive driving system
(2016)
An adaptive and rule-based driving system is being developed that tries to improve the driving behavior in terms of the energy-efficiency and safety by giving recommendations. Therefore, the driving system has to monitor the adherence of driving rules by matching the rules to the driving behavior. However, existing rule matching algorithms are not sufficient, as the data within a driving system is changing frequently. In this paper a rule matching algorithm is introduced that is able to handle frequently changing data within the context of the driving system. 15 journeys were used to evaluate the performance of the rule matching algorithms. The results showed that the introduced algorithm outperforms existing algorithms in the context of the driving system. Thus, the introduced algorithm is suited for matching frequently changing data against rules with a higher performance, why it will be used in the driving system for the detection of broken energy-efficiency of safety-relevant driving rules.
In the last decades, several driving systems were developed to improve the driving behaviour in energy efficiency or safety. However, these driving systems cover either the area of energy-efficiency or safety. Furthermore, they do not consider the stress level of the driver when showing a recommendation, although stress can lead to an unsafe or inefficient driving behaviour. In this paper, an approach is presented to consider the driver stress level in a driving system for safe and energy-efficient driving behaviour. The driving system tries to suppress a recommendation when the driver is in stress in order not to stress the driver additionally with recommendations in a stressful driving situation. This can lead to an increase in the road safety and in the user acceptance of the driving system, as the driver is not getting bothered or stressed by the driving system.
The evaluation of the approach showed, that the driving system
is able to show recommendations to the driver, while also reacting
to a high stress level by suppressing recommendations in
order not to stress the driver additionally.
A lot of people need help in their daily life to wash, select and manage their clothing. The goal of this work is to design an assistant system (eKlarA) to support the user by giving recommendations to choose the clothing combinations, to find the clothing and to wash the clothing. The idea behind eKlarA is to generate a system that uses sensors to identify the clothing and their state in the clothing cycle. The clothing cycle consists of the stations: closets, laundry basket and washing machine in one or several places. The system uses the information about the clothing, weather and calendar to support the user in the different steps of the clothing cycle. The first prototype of this system has been developed and tested. The test results are presented in this work.
Besides the optimisation of the car, energy-efficiency and safety can also be increased by optimising the driving behaviour. Based on this fact, a driving system is in development whose goal is to educate the driver in energy efficient and safe driving. It monitors the driver, the car and the environment and gives energy-efficiency and safety relevant recommendations. However, the driving system tries not to distract or bother the driver by giving recommendations for example during stressful driving situations or when the driver is not interested in that recommendation. Therefore, the driving system monitors the stress level of the driver as well as the reaction of the driver to a given recommendation and decideswhether to give a recommendation or not. This allows to suppress recommendations when needed and, thus, to increase the road safety and the user acceptance of
the driving system.
Saving energy and protecting the environment became fundamental for society and politics, why several laws were enacted to increase the energy-efficiency. Furthermore, the growing number of vehicles and drivers leaded to more accidents and fatalities on the roads, why road safety became an important factor as well. Due to the increasing importance of energy-efficiency and safety, car manufacturers started to optimise the vehicle in terms of energy-effciency and safety. However, energy-efficiency and road safety can be also increased by adapting the driving behaviour to the given driving situation. This thesis presents a concept of an adaptive and rule based driving system that tries to educate the driver in energy-efficient and safe driving by showing recommendations on time. Unlike existing driving-systems, the presented driving system considers energy-efficiency and safety relevant driving rules, the individual driving behaviour and the driver condition. This allows to avoid the distraction of the driver and to increase the acceptance of the driving system, while improving the driving behaviour in terms of energy-efficiency and safety. A prototype of the driving system was developed and evaluated. The evaluation was done on a driving simulator using 42 test drivers, who tested the effect of the driving system on the driving behaviour and the effect of the adaptiveness of the driving system on the user acceptance. It has been proven during the evaluation that the energy-efficiency and safety can be increased, when the driving system was used. Furthermore, it has been proven that the user acceptance of the driving system increases when the adaptive feature was turned on. A high user acceptance of the driving system allows a steady usage of the driving system and, thus, a steady improvement of the driving behaviour in terms of energy-efficiency and safety.
