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.
•A state space model for real-time risk evaluation of traffic standstills in winter is proposed.•The proposed method can evaluate the high-risk environment before the occurrence of traffic ...standstills on winter roads.•Probe vehicle data and weather data are used for model development.•The state space approach improves the accuracy of the risk evaluation.•The model performance is evaluated by ROC curves using data from 58 real cases.
A method that evaluates the risk of traffic standstills on winter roads in real time using a state space model is proposed herein. In Japan, large-scale anomaly events such as traffic standstills that cause serious road disturbances occur frequently every year because of heavy snowfall. However, if the risk of anomaly events is known in advance, appropriate preparation and management can be undertaken to prevent such events and/or alleviate their impacts on road traffic. Therefore, this study attempts to evaluate the risk of standstills based on the degraded road performance estimated from probe vehicle speeds using sequential Bayesian filtering in a state space model (SSM). The SSM comprises a system model constructed by learning historical data and a measurement model using several exogenous variables such as snowfall amounts and temperature. The risk of anomaly events is then determined as the deviation of the filtered vehicle speed by the SSM from the statistically feasible speed distribution. The validation is performed by applying the proposed model to 58 traffic-standstill cases in northern Japan, and we confirm that the model successfully evaluates risks at a reasonable level that permits the practical use.
In this paper we are introducing a nanoscopic traffic simulation model, that aims to support investigations on traffic phenomena, based on driving behavior, that are difficult to model in a higher ...level. Steering angle and throttle position are the main parameters to model driver behavior. To gather such information, the model has an integrated driving simulator that allows driving in a simulated 3D environment. Vehicle tracking from the driving simulator is used to update the parameters of the simulation, to achieve a realistic representation. In this study, we have used the model to investigate the congestion causing sag curve phenomenon.
The coordination of signal programs at adjacent intersections is a multivariate optimization problem with many constraints. To assess the quality of optimization procedures, the impact of different ...performance measures, and the effect of the quality of the input data, a methodology has been developed to compare different offline optimization strategies using complete information of the traffic flow. The complete information is obtained by using a traffic flow simulation. To have a benchmark for a given optimization function, the best possible coordination for given conditions is computed using Particle Swarm Optimization (PSO). Different strategies can then be compared to this benchmark.
This paper proposes a concept of critical post-encroachment time (PET) for all-red clearance interval design at signalized intersections that aims at achieving the optimum performance in both safety ...and mobility. The critical PET is defined as the minimum accepted PET at the conflict point by the first entering drivers. Variability of the accepted PETs in the case of late exit was analyzed at a study intersection in order to estimate the critical PET. Results showed that they follow a two-parameter Weibull distribution and tend to increase as the entering distance rises. Its 15th percentile value, approximately 2.0s, was then used as the critical PET to discuss the implication in the design of all-red time through numerical calculations. Conclusions supported that the calculated all-red time based on the critical PET could achieve significant operational and safety benefits, as compared with the all-red times based on the existing methods.
This paper presents a new methodology for optimizing the signal timing controls of oversaturated networks based on the cell transmission model and a goal programming technique with multiple ...objectives. The proposed model accounts for intersection spillovers, equity in delays, and system throughputs. This new formulation is solved by genetic algorithms to obtain signal timing plans. A case study with a nine-intersection network and a comparison between the proposed model and the throughput-maximizing strategy are examined. It is found that the new method can efficiently minimize spillovers, balance delay equity, and provide reasonable system throughputs in their respective order for oversaturated networks. The result also indicates that the throughput-maximizing strategy does not always yield minimum spillovers for oversaturated networks and occasionally provides a larger difference in average link delay at a spillover intersection than the proposed model does.
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