PENGGUNAAN KENDARAAN PENYIDIK BERBASIS GPS UNTUK MEMPERKIRAKAN KEADAAN LALULINTAS

Abstract

Indirect vehicle growth rate will increase the risk of traffic problems, one of the problems caused by congestion that resulted in disruption of a trip. One of the parameters that can be used to estimate traffic situation is speed, the lower traffic speed means the worse traffic conditions on the road. Speed information is required as input on the traffic information system as speed data has a big impact on congestion.

The research methods in this study use the data information obtained from Global Positioning System (GPS) data via GPS-based test vehicles. When the test vehicle position data from control centre can connect directly to the road network information system, the average traffic speed on the various road segments can be known in real time. After knowing the average speed, the approach and prediction of a traffic condition on a road network using Greenshield, Greenberg, and Underwood modelling using data taken from traffic light survey in the first field, forecasting speed data is repaid in the equation gained from the selected modelling so that the data volume and density of forecasting speed data can be known.

The research conducted a survey of the field traffic twice, where the traffic survey data in the second field was taken as a comparator to correct the errors and inaccuracies of forecasting data and field data.

The accuracy of the GPS forecasting data and in-field data is measured by using a root approach of the average quadratic error Root Mean Square Error (RMSE) and the absolute value of Mean Absolute Error (MAE), which is largely the result of the RMSE and MAE < from 15% which means that the data can be used.

Keywords : traffic, speed, investigation, vechicles, estimate