Destination-Based Parking Occupancy

Destination-based Parking Occupancy: The Application of Accessibility Measures to Parking Studies

Sasha Jovanović

Parking studies in many urban environments are conducted in settings which predate planning regulations requiring on-site parking. Unless these built environments have been aggressively retrofitted with parking, many of the destinations in these neighborhoods tend to have a heavy reliance on off-site parking, much of it located on the street. Within these destination-rich neighborhoods, residents, business interests, and visitors – who each generally perceive the supply to be limited, compete for this common fragmented parking supply. Parking studies are undertaken to assess how much of a parking supply is being used and when, to help cities make informed decisions about how to manage their parking supply most effectively to satisfy those competing stakeholders while also meeting a variety of other planning objectives that may be in conflict with parking, such as adding housing or improving sustainable transportation. Although there is no prescribed standard method for parking studies, these studies typically examine the main variables of parking: supply, occupancy (the percentage of parking supply being used at a given time), and in locations where parking occupancy is very high, frequency of parking turnover (How to Do a Parking Study, 2019).

Parking supply and occupancy are typically collected by each on-street segment and public parking lot in the area of study, and are subsequently presented and interpreted through tables and maps, as shown in Figure 1. However, this presentation of data often lacks the flexibility to communicate the complexity of how parking is sourced in urban environments reliant on off-site parking. The spatial distribution of parking within an urban street network is usually quite irregular with each source of parking having a varying quantity of spaces; also, because most parking is off-site, navigation is often required between the parking location and the destination. Without normalizing data for these factors, it can be difficult to accurately benchmark conditions or make consistent comparisons within a study area. The Destination-based Occupancy approach seeks to overcome those conceptual limitations through the application of accessibility measurements.

Figure 1: Parking occupancy symbolized by on-street segment and public parking lot (Downtown Carlsbad Parking Study (2021))

Accessibility is the measure of ease of reaching destinations or opportunities within a specified travel time or cost (El-Geneidy et al., 2006). Accessibility measurements facilitate consistent comparisons within every part of the study area by summarizing each destination’s parking supply and occupancy within a standardized travel distance. Geographic Information Systems (GIS) network travelsheds are generated for each destination to represent this travel distance and are the mechanism for spatially summarizing the parking data collection. This approach does not alter the way data is collected as it is only a post-processing technique, providing a supplemental way to interpret the data that improves upon the limitations of interpreting occupancy characteristics by the on-street and off-street locations of supply which vary in quantity and spatial distribution. CR Associates has pioneered this technical approach and has applied it in downtown parking studies for several municipal clients in California, including the cities of Chula Vista, Carlsbad and West Hollywood. Accessibility measurements are often used to help better understand travel behavior, mode choice, and analyze the nexus of transportation systems and land use. The concept of measuring accessibility has been around for decades, notably the theoretical measures advanced by Walter G. Hansen (1959). In recent years, the improvement in the processing capabilities of GIS software and the increasing availability of spatial datasets has allowed the application of accessibility measures in the study of transportation to flourish (Levinson & Cui, 2019) categorized accessibility measures into two typologies: primal measures – which measure opportunities accessible to an origin or destination within a specified travel time; and dual measures – which measure the travel time required to access a specified number of opportunities from an origin or destination.

Figure 2: Cumulative opportunity measurements count the number of opportunities within a given quantity of travel

Types of primal measures include cumulative opportunity measurements – the most basic measure, shown in Figures 2 and 3, is a count of opportunities that can be reached within a given quantity of travel from an origin or destination, and competitive access measurements – which recognize that some opportunities are rival (such as parking), and that once occupied are no longer accessible to others. Competitive access measurements thus consider both the supply and demand of the opportunity being measured, with the measure discounting opportunities by their corresponding demand or occupancy (as shown in Figure 4).

Figure 3: A cumulative opportunity measurement of parking supply within 1/8 mile for one destination. Destination-based Occuvpancy calculates this for every destination (operationalized as a parcel) in a study area and maps display the values measured for each destination

Figure 4: A competitive access measurement can be applied to count the quantity of parking spaces occupied within a 1/8 mile travel threshold of one destination

Figure 5: Map which summarizes public parking supply within 1/8 mile for every parcel/destination (Downtown Carlsbad Parking Study (2021))

Figure 6: Map which summarizes public parking occupancy within 1/8 mile for every parcel/destination (Downtown Carlsbad Parking Study (2021))

Destination-based occupancy is an application of primal accessibility measures to parking inventory and occupancy. To avoid additional complexity, the approach measures favor a simpler, distance-based operationalizing of the travel required, eschewing the incorporation of any cost or time factors. The approach uses a cumulative opportunity measurement to count parking supply within a fixed travel distance of every destination within a study area and a competitive access measurement to calculate an occupancy of parking supply that is destination-specific , providing a composite estimate of the remaining supply available from that destination within the fixed travel distance.

Products of this analysis include parcel-based summaries of total parking supply (Figure 5), percentage occupancy (Figure 6), estimated available parking supply, and peak occupancy time period. In the projects this approach has been used , it has evaluated existing parking supply conditions, temporal variations in parking demand, future scenarios with parking supply changes and future scenarios with both land use and parking supply changes.

Typical maps will display the summarized values of parking supply and occupancy for every destination in the study area by a standardized travel distance. A standardized measure of access to parking for each destination better communicates the irregular geographic distribution of parking conditions within a study area, accounting for the variability in size and spatial distribution of parking, and the navigation required to go from parking to destination in urban settings. The shortcomings corrected by a standardized access measure are evident in Figure 7 which overlays occupancy by supply and destination-based occupancy from one period on the same map. It is common, when comparing the occupancy values on the parcels to the occupancy of its adjacent supply, to find instances of the two occupancy measurements varying significantly from each other.

Figure 7: Overlay of occupancy by supply and destination-based occupancy from one period on the same map

Figure 8: Destination-based Occupancy can display how peak conditions vary geographically

By generating these standardized measures of access to parking for every destination, Destination-based Occupancy can also elegantly display how peak conditions vary geographically (as shown in Figure 8). Peak parking occupancy represents when parking demand is the highest and, if at high occupancy levels, would approximate the degree to which an area’s parking capacity is at its most strained. Study areas with a variety of land use types may have subareas which peak at different times and decline sharply at other times . Improved understanding of how peak conditions vary within a study area helped make strategic parking recommendations, such as finetuning parking in-lieu fees with better geographic precision, identifying where turnover enforcement or demand-based pricing would be most effective, and where the best opportunity areas may be to integrate future high parking demand land uses with existing parking supply. Destination-based Occupancy also provides a foundation for other meaningful forms of parking evaluation, including the appraisal of projects which impact the supply of parking and of planning scenarios which would change the demand for parking. This was done in the Downtown Chula Vista Parking Study, where staff wanted to assess how the loss of 43 parking spaces on Third Avenue to post-pandemic outdoor dining structures would impact parking demand if and when parking demand returned to pre-pandemic levels. The findings, shown in Figure 9, helped maintain the justification for outdoor dining structures by affirming that the loss of those parking spaces did not impact the availability of parking spaces within a short walking distance during the one of the district’s main peak periods. Projects which result in parking supply changes can be modeled easily into the Destination-based Occupancy framework to meaningfully assess the impacts. Calculating the destination-based parking occupancy under project conditions requires summarizing the new parking supply for each destination (Figure 10) and new parking occupancy after re-assigning parking occupants from the displaced parking sources to the nearest sources with available parking (Figure 11). Destination-based Occupancy can also work for modeling future planning scenarios, which was another application used in the Chula Vista study, the findings of which were used to inform an update of the district’s parking in-lieu fee program. Estimation of future parking generation and subsequent updating of the Destination-based Occupancy framework requires an assumption of parking spillover (new parking demand generated in excess of what can be accommodated on-site) based on information such as the development capacities of each developable site, their on-site parking requirements, and temporal parking generation rates by land-use type. Future scenario parking occupancy by supply is then calculated by adding the spillover parking generation to baseline parking occupancies (spillover parking calculations from each developable site are assigned to the nearest sources of available off-site parking based on baseline conditions). The Destination-based parking occupancy for future conditions is then obtained by generating a refreshed summarization.

Figure 10: Estimated occupancy of supply and available parking within the 1/8 mile travel threshold of one destination after the loss of the 50 parking spaces. Displaced parking occupants are re-assigned to adjacent parking sources with spare capacity.

Figure 11: Estimated occupancy of supply and available parking within the 1/8 mile travel threshold assuming pre-pandemic demand and post-pandemic parking supply (Downtown Chula Vista Parking Study (2021))

In political battles over projects which threaten parking supply, proponents of parking tend to fixate on the loss of supply directly in front of their destination of interest, despite property-adjacent parking only amounting to a tiny fraction of all parking within a short walk of the destination. While uncompromising expectations about parking may fuel much of this sentiment, this framing is also somewhat borne out of not having quality information (as was demonstrated in Figure 7). A standardized measure of access to parking, which Destination-based Occupancy provides, enhances the quality of information generated from studying parking in urban areas. This unique technical approach, first having been applied in Chula Vista, presents a potentially game-changing framework for analyzing how surrounding areas are impacted by projects which remove parking supply or alter the demand for parking.

About the Author

Sasha Jovanović has 14 years of professional experience as a transportation planner and geographic information systems (GIS) specialist. Throughout his career Sasha has worked on numerous mobility projects, transportation research and other transportation performance evaluation studies. His perspectives from both disciplines have helped give him the creativity to develop innovative technical approaches, many of which have been applied in the mobility planning practice of CR Associates.

References

Cui, M. & Levinson, D. (2019). Measuring full cost accessibility by auto. Journal of Transport and Land Use, 12(1), 649–672. https://doi.org/10.5198/jtlu.2019.1495

El-Geneidy, Levinson, D., Diab, E., Boisjoly, G., Verbich, D., & Loong, C. (2016). The cost of equity: Assessing transit accessibility and social disparity using total travel cost. Transportation Research. Part A, Policy and Practice, 91, 302–316. https://doi. org/10.1016/j.tra.2016.07.003

Hansen, W.G. (1959). How Accessibility Shapes Land Use. Journal of the American Institute of Planners, 25(2), 73-76, https://doi.org/10.1080/01944365908978307

How to Do a Parking Study. (2019, April). Metropolitan Area Planning Council. https:// www.mapc.org/wp-content/uploads/2010/02/HTD_5.pdf

Cover photo: Aerial view of cars in a parking lot (Unsplash)