Using an improved rule match algorithm in an expert system to detect broken driving rules for an energy-efficiency and safety relevant 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

Intelligent Driving Assistant Based on Road Accident Risk Map Analysis and Vehicle Telemetry

Through the application of intelligent systems in driver assistance systems, the experience of traveling by road has become much more comfortable and safe. In this sense, this paper then reports the development of an intelligent driving assistant, based on vehicle telemetry and road accident risk map analysis, whose responsibility is to alert the driver in order to avoid risky situations that may cause traffic accidents. In performance evaluations using real cars in a real environment, the on-board intelligent assistant reproduced real-time audio-visual alerts according to information obtained from both telemetry and road accident risk map analysis. As a result, an intelligent assistance agent based on fuzzy reasoning was obtained, which supported the driver correctly in real-time according to the telemetry data, the vehicle environment and the principles of secure driving practices and transportation regulation laws. Experimental results and conclusions emphasizing the advantages of the proposed intelligent driving assistant in the improvement of the driving task are presented. Document type: Articl

Intelligent Driving Assistant based on Road Accident Risk Map Analysis and Vehicle Telemetr

El estudio espuesto a continuación presenta el desarrollo de un asistente inteligente de conducción basado en telemetría vehicular y análisis de mapas de riesgo de accidentalidad vial, cuya responsabilidad es alertar al conductor conforme se lleva a cabo el proceso de conducción para evitar de esta forma situaciones riesgosas que puedan ocasionar accidentes de tránsito. El asistente inteligente a bordo del vehículo reproduce alertas visuales-auditivas en tiempo real de acuerdo a la información obtenida de ambas fuentes, y las conducciones realizadas para su desarrollo y evaluación son obtenidas por un automóvil real en un entorno real. Como resultado, se obtuvo un agente de asistencia inteligente basado en el razonamiento difuso, que apoya correctamente al conductor en tiempo real de acuerdo a los datos de telemetría, al entorno vehicular y a los principios de prácticas seguras de conducción y regulación de transporte.

An adaptive and rule based driving system for energy-e cient and safe driving behaviour

Falta palabras claveSaving energy and protecting the environment became fundamental for society and politics, why several laws were enacted to increase the energye ciency. 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 energye ciency and safety, car manufacturers started to optimise the vehicle in terms of energy-e ciency and safety. However, energy-e ciency 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-e cient and safe driving by showing recommendations on time. Unlike existing driving systems, the presented driving system considers energy-e ciency 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-e ciency 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 e_ect of the driving system on the driving behaviour and the e_ect of the adaptiveness of the driving system on the user acceptance. It has been proven during the evaluation that the energy-e ciency 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-e ciency and safety