Panichpapiboon, Sooksan
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Panichpapiboon, Sooksan
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sooksan.pa@kmitl.ac.th
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Item type:Publication, Characterization of Passenger Search Time Under Varying Supply-Demand Imbalance(2026-08-01)Passenger search time is an essential variable in a street-hail taxi operation. Fundamentally, the statistical distributions of passenger search time form the basis of analytical and simulation models for describing the taxi system’s dynamics. To create accurate analytical and simulation models that realistically represent the dynamics of the actual taxi system, it is inevitable to characterize the type of statistical distributions that can effectively model the empirical distributions. While the probability distribution functions of passenger search time are critical elements of analytical and simulation models, their empirical distributions under different levels of supply-demand imbalance have not been characterized in any existing studies. In this paper, based on more than eight million real taxi trips in Bangkok, Thailand, and formal statistical analysis, we identify the probability distributions that can effectively model the empirical distributions of passenger search time under different levels of taxi supply-demand imbalance. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Time-headway distributions on an expressway: Case of bangkok(2015-01-01)Traffic flow modeling is one of the fundamental keys to solving a traffic engineering problem. Among many parameters, time headway is frequently used to model traffic flow characteristics. A statistical analysis of time headways is immensely important to both theoretical traffic modeling and simulation-based traffic modeling. Basically, it allows researchers to describe an inherently random pattern of traffic flows. Past studies have mainly focused on the time headways of vehicles on highways, freeways, and arterials. However, studies of time headways on urban expressways are rather limited and still need further investigation. In this paper, the author investigates and characterizes the time-headway distributions of vehicles traveling on an urban expressway in Bangkok, Thailand. Particularly, the exponential distribution, the lognormal distribution, and the generalized extreme value (GEV) distribution are used to model the time headways. It is found that the GEV distribution is most effective in modeling time headways. In fact, the GEV distribution can describe more than 90% of the empirical distributions on most lanes and sections of the expressway. On the other hand, the exponential distribution is the least effective distribution. It can only describe the empirical distributions during the periods when the traffic is extremely light. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Modeling the Distributions of Taxi Supply: A Case Study in Bangkok(2025-04-01)Taxi is one of the most popular public transportation systems that is commonly available in many cities. It allows passengers to travel to their destinations conveniently. Nonetheless, traditional street-hail taxi systems are known to have low efficiency. Passengers often have to wait for a long time, while many vacant taxis spend a considerable amount of time searching for passengers. This inefficiency is a result of an imbalance between supply and demand. Understanding the statistical distributions of taxi supply and demand is vital to solving this imbalance problem. Moreover, to realistically simulate the number of vacant and busy taxis with a traffic simulator, it is necessary to know the types of distributions that can properly represent the empirical variation of taxi supply and demand. In our previous work, we have successfully characterized the temporal distribution of taxi demand. In this study, we investigate the supply side and characterize the temporal distribution of vacant taxis. Contrary to the conventional belief, we show that modeling the temporal distribution of taxi supply with a Poisson distribution is mostly invalid. Finally, we demonstrate that a geometric distribution is suitable for modeling the distribution of taxi supply in most scenarios.