Driverless Car for Next Generation Commuters - Key Factors and Future Issues

In today’s world, as the technology is increasing day by day, road accidents are becoming more and more prevalent. Driver error is the most common cause of traffic accidents, and with cell phones, in-car entertainment systems, more traffic and more complicated road systems, it isn't likely to go away. To reduce the human error, there arises a possibility if with use of technology this error can be reduced and driving can be safer. Driverless cars are one of the major topics where transportation and innovation are considered to be perfectly combined for the safety on roads. Every automotive player is trying its best to make it practically possible in whichever it could. Companies developing and/or testing driverless cars include Audi, BMW, Ford, Google, General Motors, Tesla, Volkswagen and Volvo. One of the major ongoing projects is “Waymo” by Google. In this project we designed a prototype of driverless car with basic features using Arduino uno. We have used gmaps to create a map where we used to give the source and destination to get the route then we download the route in Keyhole Markup Language (KML) file format then we go to convertcsv.com site to extract latitude and longitude from the KML file that we just downloaded from the gmaps. We copy the latitude and longitude to our Arduino uno code where we keep the latitudes and longitudes in form of an array. Then we have built an app which uses the mobile Assisted Global Positioning System (AGPS) sensor to sense the current real time position in terms of latitudes and longitudes and send them to things peak cloud and simultaneously displaying them on a real time map. Arduino uno then receives the latest data sent from the mobile to the cloud and to do that Arduino uno uses a Wi-Fi module (esp 8266) to connect to the internet. Then the thingspeak cloud send the data receive from the mobile to the Arduino uno and then using that data we calculate the degree and distance required to move the car according to the latitudes and longitudes stored in the array which we got from the gmap route.