Improving Efficiency in Vehicle Rental Operations
Authors
Karazhekov Denys
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Vehicle rental operators lose a measurable fraction of scheduled fleet availability to unscheduled idle time that existing telemetry platforms cannot isolate from legitimate downtime, because they classify vehicle state from ignition and GPS signals without cross-referencing dispatch schedule and maintenance records. This paper introduces a closed-loop operational efficiency framework comprising a five-state activity taxonomy, a weighted composite Utilization Rate Index, FFT-based structural pattern detection over a 90-day rolling horizon, and priority-ranked prescriptive interventions with demand-adaptive threshold adjustment. Evaluated on a 30-vehicle fleet over 60 operational days and validated on a 42-vehicle fleet over 90 days, the framework reduces the unscheduled idle fraction of scheduled availability from 18.7% to 11.3%, raises fleet-mean shift-level URI from 0.681 to 0.743, and achieves pattern detection precision of 96.2% in zones with demand coefficient of variation below 0.40. A critical weighting boundary at w₂ = 0.22 defines the operating limit above which redeployment recommendations are fully suppressed by the priority function, and a 29% attribution error rate under dual-signal temporal overlap conditions establishes the binding constraint on intervention specificity.
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Authors
Karazhekov Denys
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