Traffic state estimation by backward moving observers: An application and validation under an incident

This study analyzes measurements by backward moving observers that could be probe vehicles running backward on the opposite lane observing forward moving traffic to be investigated. These probe vehicles are called as backward probe vehicles (BP) and they are proven to measure the traffic flow and density. Using some advanced technology, a BP is assumed to estimate the flow of vehicles running forward from their passing time measurements along the BP trajectory. Then, as a useful application for the flow measurement by a BP, we propose a data assimilation method that estimates traffic states under an incident on an expressway section utilizing BP measurements in addition to conventional probe vehicles moving forward (forward probe vehicles) and detector data. Ample literature exists on traffic state estimation using several sensing data. However, they have difficulty in estimating traffic states during an incident, since the observations of the incident period and the declined flow rate due to the incident may not be sufficiently accurate. Therefore, this study proposes a state space model (SSM) that estimates traffic states under an incident on an expressway utilizing BP measurements. The model validation using a hypothetical network with an incident confirms the promising potential of the proposed model; that is, the reproducibility of traffic states using BP measurements is superior to one using forward probe measurements.