Rural School Bus Routing and Scheduling

2025-07-22

AI Summary

To address the vicious cycle of excessively long rural school bus ride times, low vehicle utilization, and worsening campus-area traffic congestion caused by parental private-car drop-offs, this paper proposes a road-network-aware “clustering-then-routing” heuristic algorithm. The method integrates real-world transportation network characteristics, supports mixed-capacity constraints and irregular road topologies, and jointly optimizes student clustering and route planning. Evaluated on real-world data, the approach reduces total student ride time by 37–39%, increases school bus utilization by 17–19%, and decreases private-car commuting near schools by 12–17%. Its key innovations include embedding road-network topology into the clustering phase and designing a lightweight, decoupled solution framework tailored to rural operational constraints—thereby significantly improving scheduling feasibility and practical deployability.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Heuristic Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments

Abstract

Long school bus rides adversely affect student performance and well-being. Rural school bus rides are particularly long, incentivizing parents to drive their children to school rather than to opt for the school bus. This in turn exacerbates the traffic congestion around schools, further compounding the problem of long bus rides, creating a vicious cycle. It also results in underutilized school buses and higher bus operating costs per rider. To address these challenges, this paper focuses on the design of rural school bus routes and schedules, a particularly challenging problem due to its unique operational complexities, including mixed loading and irregular road networks. We formalize a rural school bus routing and scheduling model that tackles these complexities while minimizing the total bus ride time of students. We develop an original road network-aware cluster-then-route heuristic that leverages our problem formulation to produce high-quality solutions. For real-world case studies, our approach outperforms status quo solutions by reducing the bus ride times of students by 37-39 %. Our solutions also make the school bus more attractive, helping address both the underutilization of school buses and the prevalence of private commutes. Our routing and scheduling approach can improve school bus use by 17-19 % and reduce car trips that induce congestion near schools by 12-17 %. Many rural school districts share the operational characteristics modeled in this study, including long bus rides, high operational expenditures, mixed loading, and a high proportion of car-based school commutes, suggesting the broad applicability of our approach. Ultimately, by reducing student travel times, increasing school bus utilization, and alleviating congestion near schools, our approach enables rural school district planners to address transportation-related barriers to student performance and well-being.

Problem

• Minimize rural school bus ride times for students
• Reduce underutilization of school buses and operating costs
• Alleviate traffic congestion near schools from private commutes

Innovation

• Road network-aware cluster-then-route heuristic
• Minimizes total student bus ride time
• Reduces car trips and increases bus utilization