During a period of high and growing bus ridership at a large city bus system, there was a need to systematically and quickly identify the routes and time periods that needed increases and where buses could be harvested at identified declines. With approximately 4,500 buses operating on 235 routes out of 20 bus depots, a convenient method was needed to redeploy the fleet from routes with spare capacity to routes over-capacity without exceeding the operating budget or meeting a specified budget increase.
We developed a strategic model in Excel to identify opportunities to adjust baseline service based on long-term changes in policy, supply, and demand. The inputs for this model included the current route-level bus ridership and service levels, the current assignment and utilization at peak load points, and operating cost factors. Services were compared across all routes and out of all depots on a systematic basis, utilizing route performance indicators such as seat utilization, yield, cost per passenger trip.
The model allowed planners for the first time to generate different budget scenarios to quickly identify over-served and under-served areas of the region and systematize their ridership and service level data collection. The output was a list of targeted areas where potential adjustments could improve the farebox recovery ratio and/or bus utilization.
This model was used as a basis to inform bus fleet changes for several years for the Schedules unit as well as test peak fleet requirements under different passenger loading standards (looking for savings) and helped to establish a practice of systematically and quantitatively analyzing utilization of buses and garage capacity at this agency.
