The Geographical Information Systems (GIS) for Autonomous Vehicles

1.Introduction
Autonomous Vehicles(AV) are an important part of Intelligent Transport Systems(ITS). Due to their high intelligence these kind of vehicles are capable of reducing traffic congestions and accidents, thus improve the efficiency of whole ITS. Increasingly complex urban environments are forcing AV to identify a huge amount of environmental information. This issue is done by introducing the Geographical Information System (GIS) which has a great ability to store and manage geographic information. A method for creating GIS database combines aspects and characteristics of urban traffic and needs for observing the environment of AV. This is necessary for autonomous and safety moving of AV in the urban traffic scenario. For creating maps, OpenStreetMap has been used.[1]
1.1 Autonomous Vehicles (AV)
AV observe surrounding by using built-in sensors to determine road information, obstacles and GPS location, so that this vehicle could be safely and reliably driven through environment without human input. In nowadays it seems that the Google driverless car has reached a high level in terms of artificial intelligence. This means, in near future AV could probably be used in everyday life. By reading some IEEE articles, we can realise that AV would reach 75% of total cars by year 2040 . Assuming that future belongs to the AV, that is why every research on this topic is very important.
Classical way of controlling vehicle is that a driver perceive the environment and control vehicle. This scenario could be represented as closed-loop system of “vehicle-road-driver”[2]. In the case of driverless vehicles, controlling is done by using closed-loop control system “vehicle-road”. The environment data which have to be observed by AV are:
-Traffic lights, traffic signs, police’s gestures and other information about the traffic rules.
-Information about the road, length and width, number of lanes, grade of the road, parking spots etc.
-Data about current position, speed, obstacles, other vehicles, pedestrians and other relevant information.

The environment changes daily, therefore it is more difficult for AV to observe it in correct and efficient way. To solve this issue, we need some information about environment which could be stored and known in advance. This is a part where GIS plays its main role. GIS is capable of storage, management and visualization for geographical information. By applying GIS to AV we can construct a database with all information about environment in the certain area to achieve efficient and detailed autonomous navigation for AV.