Velocity Approximation of Kuala Lumpur Bus Rides: Weekday vs. Weekend Comparison Using the Discrete Least Squares Method
Year: 2025
Type: conference-paper
Abstract: This study investigates the application of the Discrete Least Squares Method (DLSM) to approximate and analyze the difference between weekday and weekend traffic flow in Kuala Lumpur, Malaysia. The data acquisition involved collecting time and distance between each of the 24 stations from the GOKL CityBus route from Titiwangsa to KL Sentral, starting at 1.00 p.m. for each weekday (Thursday) and weekend (Sunday). For weekdays, Thursday represents a normal day without extra traffic jams, like Mondays and Fridays, while for weekends, Sunday represents lighter traffic compared to Saturdays. The study derives continuous functions based on third-order polynomials using the Discrete Least Squares method to approximate velocities at each station. The results show that velocity approximation using continuous functions is more accurate on weekdays than weekends, indicating smoother traffic flow and less significant traffic congestion on weekends. The use of DLSM has provided an accurate polynomial model for approximating velocity, highlighting its usefulness in dealing with complex traffic patterns. Moreover, error calculations for continuous functions on both weekdays and weekends showed higher error compared to the piecewise continuous function, suggesting that continuous functions offer greater accuracy. Limitations include the scope of data collection being limited to a single bus route and a specific time. Hence, there is a need for more future comprehensive studies across different modes of transportation and schedules.
Authors: Zubaidah Sadikin, Aina Zulaikha Alauddin, Sidik Rathi, Nurziana Harun, Muhamad Syahrizam Salidin, Mohd Agos Salim Nasir, Nurzalina Harun
Institutions: Universiti Teknologi MARA System, Universiti Teknologi MARA
Language: English
Subfield: Transportation
Field: Social Sciences
Domain: Social Sciences
Open Access status: green
OpenAlex ID: W6930736731
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