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Author: search.filters.author.Chalermwongphan, Karn

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    Comparing the traffic operation, fuel consumption, and pollutant emission of bike lane pattern design with AIMSUN microscopic simulation model: A case study of nakhon sawan municipality in Thailand
    (2019-01-01)
    Chalermwongphan, Karn
    ;
    Upala, Prapatpong
    Background: The present research aimed to compare and evaluate two forms of shared roadways, which were Conventional Bike Lane (CBL) and Median Bike Lane (MBL). Methods: The road network and traffic conditions of Nakhon Sawan Municipality, comprised of 712 links and 237 nodes, simulated by using the AIMSUN microscopic simulation software in order to compare the delay time, operating speed, total travel time, fuel consumption, and emission of carbon dioxide (CO<sup>2</sup>), nitrogen oxide (NO<sup>X</sup>), Particulate Matter (PM), and Volatile Organic Compounds (VOC). Results: The obtained results can be used as efficiency data for designing a campaign to encourage private car drivers to change their daily transportation mode to bicycle, which will ultimately help to solve traffic congestion problems and reduce environmental impacts in a sustainable way. The research results showed that a campaign encouraging a change in transportation mode should focus on reducing 36 percent of all private cars in the road network (at least 9,691 veh/hr). Conclusion: This approach will minimize the delay time in the road network by 0.89 sec/km and reduce 1,228.66 liters of fuel consumption, 2,769,764.47 g/km of carbon dioxide, 8654.86 g/km of nitrogen oxide, 1,463.33 g/km of particulate matter, and 1,383.93 g/km of volatile organic compounds.
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    The analysis of dynamic O/D adjustment for bicycle traffic demand estimation with aimsun simulation model: A case study of nakhon sawan municipality in Thailand
    (2018-01-01)
    Chalermwongphan, Karn
    ;
    Upala, Prapatpong
    Aim: This research aimed to present the process of estimating bicycle traffic demand in order to design bike routes that meet the daily transportation needs of the people in Nakhon Sawan Municipality. Methods: The primary and secondary traffic data were collected to develop a virtual traffic simulation model with the use of the AIMSUN simulation software. The model validation method was carried out to adjust the origin and destination survey data (O/D matrix) by running dynamic O/D adjustment. The 99 replication scenarios were statistically examined and assessed using the goodness-of-fit test. The 9 measures, which were examined, included: 1) Root Mean Square Error (RMSE), 2) Root Mean Square Percentage Error (RMSPE%), 3) Mean Absolute Deviation (MAD), 4) Mean Bias Error (MBE), 5) Mean Percentage Error (MPE%), 6) Mean Absolute Percentage Error (MAPE%), 7) Coefficient of Determination (R2), 8) GEH Statistic (GEH), and 9) Thiel’s U Statistic (Theil’s U). Results: The resulting statistical values were used to determine the acceptable ranges according to the acceptable indicators of each factor. Conclusion: It was found that there were only 8 scenarios that met the evaluation criteria. The selection and ranking process was consequently carried out using the multi-factor scoring method, which could eliminate errors that might arise from applying only one goodness-offit test measure.
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    Empirical experiment on origin destination estimation using automatic licence plate matching on a rural road of Thailand
    (2017-10-19)
    Watanachaturaporn, Pakorn
    ;
    Chalermwongphan, Karn
    ;
    Huntajidkul, Achaya
    ;
    Vongchumyen, Charoen
    ;
    Watthanakul, Jettarin
    The growth of economic influences city authorities to plan and build infrastructure. The growth prediction mostly uses modern mathematical models. The accuracy of the model is highly depended on reliable parameters. Two crucial parameters for most models are traffic capacity and average travel speed along road networks and obtained from an origin-destination (OD) estimation. Thus, an OD estimation is necessary to obtain reliable parameters for the predictive models. Traditionally, the OD estimation is performed by human observation; however, an automatic license plate recognition and matching algorithm show potential of obtaining such data. Additionally, the observation is able to perform long term observation which is impractical for human. Therefore, this paper reports an empirical experiment on OD estimation using automatic license plate matching along with a real-world human observation survey in Mukdahan province. The results from both types of surveys are reported and compared. The different results between the both raises an opportunity for researching an optimal method of OD estimation in Thailand.