Spatiotemporal Traffic Density Estimation Based on ADAS Probe Data

This study aims to develop a spatiotemporal traffic density estimation method based on the advanced driver assistance system (ADAS) Probe data. uses vehicle trajectory data collected from ADAS equipped sample probe vehicles. Such are used firstly estimate distance headway between vehicles specific road section, and postprocessed finally density. The innovation aspect of proposed methodology in this is that can be estimated high accuracy only with small size points support ADAS. On other hand, existing requires large number its numerous sets including either global positioning or dedicated short-range communication To verify methodology, two-step evaluation performed: first step numerical estimates simulated data, second an empirical real-road both peak nonpeak periods. Beyond development, verified reliability under various conditions sampling rate ADAS-equipped Consequently, error decreased as increased. Estimation 90% higher was observed all scenarios when 50% higher. It indicates fairly accurate feasible using correspond half driven road. Therefore, practical approach expected mitigate burden estimation, particularly future systems which autonomous prevalent.