| Budget Amount *help |
¥1,800,000 (Direct Cost: ¥1,800,000)
Fiscal Year 1993: ¥400,000 (Direct Cost: ¥400,000)
Fiscal Year 1992: ¥1,400,000 (Direct Cost: ¥1,400,000)
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| Research Abstract |
Road users behavior to singal change intervals (yellow plus all-red intervals) changes depending upon the both geometric design, traffic flow condition and traffic control condition. In this study, this behavior was evaluated by using the traffic-related data collected from video-tape recorder at various signalized intersections. In particular, probability of stopping was examined as a function of intersection physical conditions, traffic flow features and signal control conditions.
In the first stage, the probabilistic features of stopping were discussed in detail. When faced with an amber indication, some drivers decide to stop and other some drivers proceed through the intersection. As the distance from the stop line (x, in thes equation shown later) increases, the probability of stopping increases. In case of pedestrian, similar phenomea also can be observed. The shape of function explaining this stopping percentage appears to be close to a logistic curve. Other reason of selecting
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this curve is that the shape of the curve can change variously with the combination of the two different model parameters of this function.
These model parameters can be thought to be a function of the surrounding conditions of each intersections. In order to estimate the above mentioned model, a set of observation of road user's reaction, recorded at eleven intersection for driver's model and nine spots for pedestrians in Tokyo and Yokohama, were applied.
Model parameters for each intersection first were estimated by the logistic regression techinique. And again, multiple regression technique was applied to the set of the estimated model parameters, to derive the relations between these estimated parameters and the surrouding roadway-traffic conditions of the intersections. Various explanatory variables were prepared.
Results of regression analysis were found out to be statistically significant. These models can be used to evaluate the stopping behavior of drivers and pedestrians during the clearance interval based on the physical conditions, traffic conditions and the signal control features of the intersections concerned. Less
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