An Efficient Algorithm for Roadways Obstacles Detection using Smartphone in Infrastructure-less Environment

Apart from having smart systems in modern vehicles, roadways traffic positions in infrastructure-free environment are in various ways not suitable for driving which causes roadways accidents. Smart systems are costly, training and maintenance is not practiced by all, hence they are not useful for vehicles running in infrastructure-less environment. Modern days Smartphone are multifunctional, easily operated and consists of numerous sensors, can be utilized for roadways obstacles detection in infrastructure-less environment. In this study, we proposed an efficient algorithm depth learning approach for roadways obstacles detection using Smartphone which is useful for planned as well as unplanned roads. In this, road information is collected using Smartphone accelerometer sensors, data normalization take place using Euler angle method and location determination of obstacles take place using space interpolation method. In comparison to other same type of approach, our algorithm is efficient and cost-effective.