Multiclass Classification with Imbalanced Datasets for Car Ownership Demand Model – Cost-Sensitive Learning

In terms of the travel demand prediction from the household car ownership model, if the imbalanced data were used to support the transportation policy via a machine learning model, it would negatively affect the algorithm training process. The data on household car ownership obtained from the study project for the expressway preparation in the Khon Kaen Province (2015) was an unbalanced dataset. In other words, the number of members of the minority class is lower than the rest of the answer classes. The result is a bias in data classification. Consequently, this research suggested balancing the datasets with cost-sensitive learning methods, including decision trees, k-nearest neighbors (kNN), and naive Bayes algorithms. Before creating the 3-class model, a k-folds cross-validation method was applied to classify the datasets to define true positive rate (TPR) for the model’s performance validation. The outcome indicated that the kNN algorithm demonstrated the best performance for the minority class data prediction compared to other algorithms. It provides TPR for rural and suburban area types, which are region types with very different imbalance ratios, before balancing the data of 46.9% and 46.4%. After balancing the data (MCN1), TPR values were 84.4% and 81.4%, respectively

Feeder Bus Reformation for an Urban Rail Project: The Case of Khon Kaen City, Thailand

The ability to use public transportation should be available throughout the whole service area and the public transportation network should be well connected. This research compared the potential coverage of a feeder bus network in support of urban rail transportation, as well as the impact of future transit network plans on public transportation accessibility in the city of Khoan Kaen, Thailand. The performance of the public transportation system was predicted based on multimodal transport and the completed urban rail public transportation plan, as projected in the year 2036, in order to fill gaps in the existing feeder bus network. The feasibility and characteristics of the route reformation policy concept should provide an effective feeder network for the urban rail system. A comparative study was conducted on stakeholder impact for a three-fold scenario: 1) separate individual lines for bus routes; 2) both forms of feeder bus networks (conventional and reformed); and 3) access to three designated utility areas from the entire feeder bus network. In this scenario, the most effective urban mobility support was provided by public facilities combined with a major roadway directly connecting to the designated positions. The time used on the extended bus route network increased by around 11% on average for the entire trip, while accessibility increased by approximately 67.75%, 47.9%, and 43.68% for the entire multimodal transport network. These analytical results make a significant contribution to future knowledge on urban transformation through urban mass transit projects. The contribution of land acquisition was significant. Also, the demand-responsive connection approach used in this study can be adopted to determine feeder bus reformation options, particularly in emerging economies

Feeder Bus Reformation for an Urban Rail Project: The Case of Khon Kaen City, Thailand

The ability to use public transportation should be available throughout the whole service area and the public transportation network should be well connected. This research compared the potential coverage of a feeder bus network in support of urban rail transportation, as well as the impact of future transit network plans on public transportation accessibility in the city of Khoan Kaen, Thailand. The performance of the public transportation system was predicted based on multimodal transport and the completed urban rail public transportation plan, as projected in the year 2036, in order to fill gaps in the existing feeder bus network. The feasibility and characteristics of the route reformation policy concept should provide an effective feeder network for the urban rail system. A comparative study was conducted on stakeholder impact for a three-fold scenario: 1) separate individual lines for bus routes; 2) both forms of feeder bus networks (conventional and reformed); and 3) access to three designated utility areas from the entire feeder bus network. In this scenario, the most effective urban mobility support was provided by public facilities combined with a major roadway directly connecting to the designated positions. The time used on the extended bus route network increased by around 11% on average for the entire trip, while accessibility increased by approximately 67.75%, 47.9%, and 43.68% for the entire multimodal transport network. These analytical results make a significant contribution to future knowledge on urban transformation through urban mass transit projects. The contribution of land acquisition was significant. Also, the demand-responsive connection approach used in this study can be adopted to determine feeder bus reformation options, particularly in emerging economies

Factors Influencing Stopping Locations of Motorcycle Riders on Signalized Urban Intersection Approaches

In developing countries, motorcycle riders normally attempt to stop at their desired locations during queue formation on signalized intersection approaches. Under mixed-traffic conditions, motorcycle positioning in a queue affects the operational and safety performance of the intersection. This study aimed to identify factors influencing motorcycle riders’ stopping locations at signalized urban intersections. This study applied Unmanned Aerial Vehicles (UAVs) to observe the stopping behavior of 1413 motorcycle riders on 24 approaches from 10 signalized intersections in Thailand (N = 1413). Multinomial logistic regression analysis was used to determine the relationship between the stopping locations of motorcycle riders and rider- and motorcycle-related variables and traffic- and environmental-related variables. The statistical analyses presented a Cox and Snell R2 and Nagelkerke R2 of 0.466 and 0.499, respectively, indicating that the model accounted for almost 50% of the variation among the five stopping locations of motorcycle riders. The results showed that, under mixed-traffic conditions in Thailand with left-hand traffic, motorcycle riders intending to turn right, the morning peak period, the presence of shadows, motorcycle riders not wearing helmets, the presence of a larger vehicle in the queue, and the density of desired stopping locations significantly influenced the motorcyclists’ choice of stopping locations on signalized intersection approaches. Practical policy-related recommendations drawn from the findings are provided to improve motorcyclists’ safety on signalized intersection approaches