A smart trip advice model by inter-car voting data over Internet towards pleasant driving

Almost every day we can observe that most of people spend quite a long time in traffic environment. In the course of driving, motorists occasionally desire to get traditional travel information, such as traffic, road, car and safety related driving data. In the near future, we shall quite likely mention about new generation drivers who wish to get social based data and its manipulation. Hence, we should develop new driver necessity strategies satisfying Internet based requirements of new generation drivers. Here, we propose a system offering sub-trip options without ruining driver´s primary trip plan. In fact, we consider driving efficiency taking pleasure in driving by means of social computing rather exploiting traditional data manipulations such as safe driving, fuel-efficient driving, and obtaining traffic data. For the sake of new generation driver wishes, we develop a model using trip data and feedback information provided by drivers earlier visiting intended attraction place. Then, we utilize a social platform associated with central server holding social data such as road safety, weather conditions, and satisfaction rate of attraction place. In this study, we earlier define driver profiles as gourmand, shopaholic, adventurer, art lover, and technophile. Therefore, we propose a system satisfying possible sub-trip expectations of drivers having different profiles. Eventually, we have modeled a new generation inter car sub-route advice platform for pleasant and efficient trip.