Driver scheduling is an integral component of the Intelligent Transportation System (ITS). It improves travel efficiency by reducing traffic bottlenecks, irregularities, and accidents and enhancing passenger safety, and driver quality in public transport systems. The scheduling and maintenance of effective timetables are the biggest challenges in developing nations. Furthermore, competent and skilled drivers are not compensated extra for their work. To solve this problem, we proposed a bus transportation system that included a journey schedule and driver scheduling algorithm. Drivers are ranked based on their skill sets and standards. The schedule incorporates peak-hour passenger volume and schedules a set number of trips and lines. The drivers are selected based on their skills and attributes, encouraging them to improve and follow traffic laws, making the trip safe and secure. Our Quality-Aware Optimal Solution (QAOS) allocates the best drivers to complete journeys following labor rules. An alternative Quality-Aware Greedy Solution (QAGS) can complete the same number of trips in less time with more drivers due to the problem’s NP-hardness. Experimental results from a real-world case study reveal that our approach eliminates bus driver laborers, regulates labor limitations, maintains rest hours, and assigns qualified drivers to trips.
Quality-aware bus-driver scheduling for intelligent transportation system
2025
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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