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This article purposed to present the maximum capacity and to develop the equation in the capacity estimation of 4 types of four-lane highways by using the micro-simulation model. Regarding the analysis, the factors affecting the capacity include access-point, heavy vehicles and median u-turn. According to the study, it was found that the maximum capacity of the four-lane highways in type 1 is 2194 passenger car/hour/lane. In the descending orders, the maximum capacity of the highways with four lanes in type 2, 3, and 4 are 2161, 2094 and 2017 passenger car/hour/lane, respectively. At the same time, the maximum capacity of the prevailing condition in the study is 1300-1600 vehicles/hour/lane, which is different from the HCM2010 method for 20-30%, due to the Thai's highway characteristics directly affect the traffic and driving behavior. Median u-turn affects the four-lane highways in type 1 and 2 the most, while access-point factor has the most influence towards type 3 and 4. In addition, the author has developed the equation models for capacity estimation, which the result derived from the relationship between the capacities and affecting factors. It was aimed at using as the guidelines in the capacity assessment of Thai's four-lane highways in the future.

The purpose of this article was to investigate driver's speed behaviors during the yellow-light period and how satisfied they were at the intersections under the Red-Light Cameras (RLC) project. The survey data was collected before the project implementation and 3 months after the project began. The data was analyzed by calculating the correlation between the distances from the intersection and the drivers' speeds entering the intersections during the yellow signal. In addition, the satisfaction was evaluated with 400 samples based on the questionnaire conducted when the RLC project was ongoing. The results showed that drivers speeded up significantly during the yellow signal when they were approaching the stop line, both at the intersections under the project and at the other intersection. Besides, it was found that the speed during the yellow light reduced significantly at all distances, i.e, 14-40% (6.5-22 km/hr.), resulting in 20-meter reduction of the maximum length of movement during the yellow signal period, compared to an unchanged distance at the control intersection. The analytical results corresponded to the 56% reduction of red-light runners after RLC project began. As for the drivers' satisfaction towards the RLC project, it was found that the majority (64%) showed positive satisfaction, and that 67% reported that the project resulted in speed reduction. In addition, some variables were found to significantly correlate with the attitudes towards RLC project. The study's findings can be used as references, and the approach can be applied in other locations to prevent traffic collisions at intersections. [ABSTRACT FROM AUTHOR]

The effect of motorcycle and shoulder width on two-lane highway capacity using a traffic micro-simulation model was investigated, together with other effect factors, which are heavy vehicles and access points. Four sections of a two-lane highway that have different shoulder widths were selected for the study. Under prevailing conditions, a two-lane highway with a shoulder width of fewer than 1.5 meters will cause a motorcycle to interfere with the carriageway and other impact factors that make capacity significantly less than HCM2010 calculation. The analysis of the base conditions model determined that the maximum capacity of a two-lane highway with a shoulder width of 2.0 meters was 1979 passenger car/hour/direction. Two-lane highways with shoulder widths of 1.5, 1.0 and 0.5 meters recorded maximum capacity at 1914, 1860 and 1789 passenger car/hour/direction, respectively, with all results higher than the HCM 2010 calculation. Model equations for capacity estimation were developed using multiple linear regression analysis derived from the relationships between capacity, shoulder width, and other affecting factors. Results can be used as guidelines for the future capacity assessment of two-lane highways in Thailand. [ABSTRACT FROM AUTHOR]

A railway level crossing is a risk area despite installations of the warning signal and arm gate that indicate a train approach. Accidents may nevertheless occur if vehicle drivers violate or fail to conform to the rules. Such action is considered a risk behavior that may cause severe collision, injury, and death. Thus, the driver behaviors are the key factors causing accidents. The objective of this study was thus to investigate the risk behaviors and the factors influencing above behaviors. These behaviors were recorded by a high-resolution video camera and the initial data analysis was based on descriptive statistics. An in-depth analysis of the factors influencing the risk behaviors was performed by using Pearson Chi-square technique and Binary Logistic Regression Analysis. The results showed that the railway crossing behaviors of more than half of the drivers under the study were the risk-taking, followed by opportunistic violation. Most violations occurred during the beginning of the warning signal. Overall, the motorcycle riders were found to be the group with greater chance of violating across the railway during the warning signal than the 4-wheeled vehicle drivers. Especially, during the period between the beginning of the warning signal and the complete arm gate closure, as well as the greater width of the crossing road. This could be due to the higher agility and evasive capability of motorcycle riders than 4-wheeled drivers. Additionally, this study recommends approaches to initially prevent or reduce this risky behavior and can serve as a guideline for enhancing areas with physical characteristics similar to the study area. [ABSTRACT FROM AUTHOR]