PRE2016 3 Groep13: Difference between revisions
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== State of the Art == | == State of the Art == | ||
There are a lot of different navigation devices available currently. The most simple one is only able to tell you the shortest route. A small upgrade also allows the user to exclude certain routes, like toll roads and tunnels. These often also give a choice for the user to either take a fastest (time) or shortest (distance) route. Some devices also allow traffic information incorporation which ask you to reroute if there is a traffic jam. When combining such a navigation system with a self driving car it is also possible to make the decision automatically. These all however respond to a situation instead trying to avoid certain situations. | |||
== Approach == | == Approach == |
Revision as of 12:08, 12 February 2017
Introduction
This wiki page will display the possibilities of self learning navigational software. Throughout the report several points of attention will be introduced, investigated and processed in the prototype navigational system. The goal of the system is to create a cooperative/inter-vehicular, high-level (Think about; no traffic lights) and based on the current situation (hardly any self driving cars, not all people have navigational systems). This research is set up trying to answer the following research question:
How can the travel time be minizied while maximizing overall utility, looking at user and society, by using a self learning, inter-vehicular cooperative navigation system?
Table of contents
-Objectives
-State of the art
-Approach
-ToBeContinued
State of the Art
There are a lot of different navigation devices available currently. The most simple one is only able to tell you the shortest route. A small upgrade also allows the user to exclude certain routes, like toll roads and tunnels. These often also give a choice for the user to either take a fastest (time) or shortest (distance) route. Some devices also allow traffic information incorporation which ask you to reroute if there is a traffic jam. When combining such a navigation system with a self driving car it is also possible to make the decision automatically. These all however respond to a situation instead trying to avoid certain situations.