Reducing Uncertainty In Location Prediction Of Moving Objects In Road Networks
Hariharan Gowrisankar, Silvia Nittel · 2002
Consider a database which tracks moving objects in road network following a prespecified route. In a city environment, the number of moving objects can be large, and the frequency of updating objects ’ location increases the load on the database management system. Hence, it is not feasible to update an object’s location constantly and explicitly. Instead, location of a moving object is stored as a dynamic attribute, e.g. motion vector function [3], whereby the location value is calculated when it is accessed, and it is updated when the parameters of the function change (speed, route, etc), and to increase location accuracy by comparing a possibly calculated location value with a measured value to keep the deviation bounded. Today, dead reckoning is used to implement the motion vector function, and to determine the current and future positions of an object based on knowledge of the underlying route network, the object’s pre-specified route and the object’s last position and speed [2]. However, tracking moving objects by dead reckoning techniques inherently introduces uncertainty in location determination and prediction since we do