This paper presents the development of unequally-spaced or irregularly observed traffic measurement prediction model. Traffic measurements from detectors are usually observed or assumed to be equally-spaced (e.g., every 30 seconds and 1 minute) for transportation research. However, some traffic measurements may not be observed or assumed to be equally-spaced, especially in arterial street and intelligent transportation systems (ITS) applications. Continuous-time Kalman filtering may be used for modeling unequally-spaced traffic measurements, especially for arterial street incident detection purpose.
Significant efforts have resulted in improved knowledge about the effects of congestion on the motoring public. The Urban Mobility Report (UMR) has be...
This study resolves the controversy over the stability of constant time-gap policy for highway traffic flow. Previous studies left doubt as to the eff...
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