Accurate efficient and robust travel time prediction is crucial to the development of advanced traveler information systems for providing route guidance information. To achieve this goal this paper proposed a travel time prediction through the matching of the current speed interval pattern to that in a historical database. Speed intervals instead of speeds are considered in this study to simplify the structure of matching patterns for improving matching efficiency. In this study speed interval patterns are defined by sets of link speed intervals that are either spatially or temporarily correlated with the link considered. With the speed interval patterns the algorithm is developed for searching the historical pattern(s) that is/are the closest match with the current one. Then link speeds from these matched patterns are combined for travel time prediction. By using the GPS probe taxi data which the collected speeds are aggregated in every 5 minutes the proposed travel time prediction system is implemented in Bangkok. With the speed data from probe taxi this paper has chosen four links/paths with different geometric and flow characteristics for testing the performance of the proposed travel time prediction system. From these tests it is found that the optimal speed interval pattern should include: 1) speeds of the studied link within three preceding time intervals and; 2) speeds of links in the first connection level of the studied link. Also while the computational time is capable of real-time application the proposed prediction algorithm is more accurate under uninterrupted flow conditions.

An optimal of walking path to travel in Lopburi City was the shortest distance of path anduses least travel time. The research methodology used the survey of 10 real locations togetherwith viewing satellite maps and diagrams from Google earth.com for graphing and weighting of edges (distance time). The result analysis used the basic ideas of graph theory by finding the path that has all the vertex and used the idea of matrix by finding the adjacency matrix. The result of the research shown that an optimal of walking path to travel in Lopburi City that is to be as following Wat Puen Wichayen House Prang Khaek Somdet Phra Narai National Museum Lopburi Wat Phrasi Rattana Mahathat Wat Bandai Hin Wat Inthra Wat Nakorn Kosa Phra Kal Shrine Phra Prang Sam Yot with a total distance of 2090 meters in 25 minutes.

The objectives of this special project were to product travel documentary of the National Museum in Suphan Buri Province and study of the satisfaction of thevisitors from 200 tourisms by using the questionnaire. The statistics to analyze data was frequency percentage average and standard deviation (S.D.) The result shown that the tourisms had high levels of satisfaction to the travel documentary of National Museum Suphan Buri Province.

Factors influencing the successful strengthening of supply chain management-oriented cooperation in export of Halal meat processing industry of Thailand to ASEAN countries This research aims to analyze the variables associated with factors that influence the development of a transport tourists with eco-friendly to accommodate the opening of the ASEAN logistics and to ensure the consistency of the model. Use research methods and quantitative surveys with empirical data. Contain variables with empirical data. The seven variables include factors such as the availability of resources. Factors Tour Reliability factor Environmental factors Factors of personnel quality of life. And factor shipping costs This study used quantitative research. By empirical research Questionnaires were used to collect data. The executives in the business sector in land transport of 410 people. Results show that The research also found that the availability of resources. Factors of environmental services. Factors of personnel quality of life Product Evaluation The direct positive influence on potential providers of transport tourists with eco-friendly reliability and exceptional factors. A summary of the recommendations to the land transport business in Thailand should have a transportation management system by introducing environmentally friendly transport tourists. Used in the business which would be good for the corporate image and showcase its social responsibility for the public sector should take strict measures for organizing transport by truck to the environmental standards increased.

CO2 emission of rail transportation system plays more important role including the expansion of BTS route that consume the energy and emit CO2 gas more and more. The purpose of this research was to find out amount of CO2 emission from travelling by BTS train and determine specific CO2 emission per product in the form of gCO2e/passenger/km then forecasting on CO2 emission from BTS operations. Research process was initiated from collecting monthly data on ridership distance and electricity for 55 months continuously then regression analysis CUSUM and time series analysis were used for prediction and analysis of CO2 emission. The finding indicated that BTS’s specific CO2 emission was 24.7 gCO2e/passenger/km. Forecasting CO2 Emission from BTS result that Winters Exponential Smoothing Method is most accuracy then Double Exponential Smoothing Method Trend Analysis Method and Decomposition Method respectively. The result of these analysis could be used to calculate carbon footprint from staff travelling by BTS train and promote people to use public transport by government as sustainable transportation concept.