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Transportation Research Board [20] and [5] consider additional adjustment factors for structural road parameters and vehicle types.
A priori information concerning vehicle and road parameters should be adapted very carefully to the regional traffic conditions.
The following a priori information: road data base (routes in two directions) [16], vehicle sizes for passenger cars and trucks, road parameters (number of lanes, lane width) and solar azimuth and zenith angles is used in the proposed method.
The model is derived from a priori information about the vehicle sizes and road parameters [15], the road network, e.g. road data base [16], and the spacing between the vehicles.
The method puts various techniques together: the vehicle detection on road segments by change detection between two images with a short time lag, the usage of a priori information such as road data base, vehicle sizes and road parameters and a simple linear traffic model based on the spacing between vehicles.
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Existing road geometric parameters are necessary for the comparison with actual standards.
Table 2 depicts the road traffic parameters and describes characteristics of the car and truck traffic flows.
The reason for selecting this particular model is that it incorporates both traffic and road geometry parameters besides terrain characteristics.
The factors related to road geometric parameters analyzed in this study are deflection angle, deflection direction and radius of horizontal alignment.
The average travel times between any two cities in the case study area under normal conditions were obtained from the Baidu Map (Baidu Map n.d)., which provides reliable regional transport network information and road management parameters.
Indications about all the road-related parameters to consider (traffic, signs, posted speed, drainage, visibility, etc).
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