6 Case Study IV: Parking in San Francisco

Chapter overview

This chapter examines how parking requirements in U.S. cities affect urban density, congestion, and driving. The first part describes the problems of free, suburban, and parking requirements. The second part examines the actions some cities in the United States, including the Twin Cities in Minnesota, are implementing to address their parking challenges. The third part contrasts the benefits and drawbacks of the San Francisco Parking Management Program that seeks to curb traffic congestion. The last section concludes with takeaways for improving the implementation and efficiency of San Francisco’s parking program regarding air pollution mitigation and equity.

The implications of minimum parking requirements

The rapid urbanization and expansion of cities to suburban locations, poor access to low-density transit areas, and minimum parking requirements induce car-oriented cities (Parmar, Das, & Dave, 2020). Minimum parking requirements determine the amount of land for parking that developers must include in land-use planning. Minimum parking stems from the notion that residential and commercial land use must accommodate residents’ and users’ parking demands during peak hours. Parking standards influence sprawl and low-density development and reduce available urban land for other uses, such as affordable housing, transit, or non-motorized transportation. Parking standards induce commuters to drive personal cars for different trip purposes due to the sense of available and free parking near their destinations. Local governments establish parking requirements. Many cities replicate strict minimum requirements from other cities. Table 6.1 shows some of the parking requirements for some land uses published by the city of Fort Worth, Texas. Parking requirements influence cities’ urban form and thus the possibility to support (or not) sustainable mobility practices.

Source: Zoning Ordinance of the City of Fort Worth Code, 2022. by City of Forth Worth. (https://codelibrary.amlegal.com/codes/ftworth/latest/ftworth_tx/0-0-0-32923). In the public domain.

Rapid urbanization in the cities’ outskirts increases the demand and supply of parking, especially in areas with services and jobs that attract workers and visitors. For decades, minimum parking requirements influenced cities’ urban form and increased the costs of residential land use. Consequently, many commuters prefer places with free and extensive parking despite the high prices for land-use planning. Weinberger (2012) examined the implications of residential off-street parking on travel behavior in New York City. The study showed that off-street parking increases car driving. Minimum parking requirements influence parking behavior by increasing the demand for free parking and, at the same time, exceeding the available parking supply. Minimum requirements influence the urban form and travel behavior and impact the available land for alternative transportation modes. Seattle has implemented some progressive parking strategies. First 2006, the city granted flexible parking requirements in commercial zones.  Later, in 2012, Seattle eradicated minimum parking requirements for multifamily zones in urban centers. Also, the city reduced minimum requirements for residential land use in urban centers with relatively good access to transit services (Weinberger 2012). A recent study found that modifying Seattle parking requirements has enabled land-use planning changes. Developers avoided erecting 18,000 parking spaces and thus saved $500 million between 2012 and 2017. More importantly, developers allocated more land to housing and green spaces (Gabbe, Pierce, & Clowers, 2020).

The costs of free parking

Parking requirement regulations negatively affect urban form by reducing density and undermining local governments’ capacity to manage parking properly. Some cities have limited resources, such as technologies and infrastructure, to charge drivers for the externalities of parking. Externalities such as sprawl and congestion are (Shoup, 1997). In the late 1990s, Shoup estimated that the total amount of land dedicated for parking in the U.S. was as big as the state of Connecticut. It has only increased in size as cities have grown and with population growth in the last three decades. Also, expansive areas of parking undermine the affordability of residential land use. For example, a study conducted in San Francisco in 1997 found that requirements for off-street parking increased housing prices by $47,000 and thus increased the annual income potential buyers required for housing from $67,000 to $76,000 (Shoup, 1997). Residential land use with flexible parking requirements may increase housing supply, especially in more dense urban areas with access to public transportation.

Parking lots typically occupy 30% of the total land in multi-family areas and 60% of commercial land uses (Ferguson 2005). Empirical studies reveal that excessive parking areas decrease densities. Car-oriented cities and excessive parking surges transportation energy use and thus greenhouse gas emissions, undermining sustainability and smart growth (Cutter & Franco, 2012). Excessive parking also reduces the extent of impervious surfaces in cities and thus increases the risk of floods and the vulnerability of cities to torrential rains or extreme climate events. Smart growth, sustainability, and social equity advocates have called for significant changes in parking regulations (Wilson and Roberts, 2011).

Cutter and Franco (2012) found that excessive parking in US cities increases costs and thus reduces the profits and revenues for developers. Because the marginal value of building parking is less than the marginal value of urban land with infrastructure, the construction of excessive parking is not  cost-effective for developers. Cutter and Franco (2012) call for a parking pricing policy that carefully understands how residents and users of buildings commute to understand their precise parking requirements. A comprehensive understanding of parking behavior that informs equitable parking pricing policy may reduce driving and cruising in urban areas (Cutter and Franco 2012).

Cruising and Congestion

When drivers cannot find a parking spot near their destination, they cruise until it is found. Cruising for parking occurs when drivers cannot find a suitable parking spot for their vehicles in terms of price and proximity to their destination. Cruising increases traffic, congestion, and air pollution, especially downtown or urban areas. Shoup (2006) found that cruising traffic during peak times accounts for 30-50% of total traffic in U.S. cities. Past studies revealed that around 30% of the traffic was associated with cruising for parking in different cities during the 90s, and the average time to find a suitable on-street space ranged between 3.5 and 14 min (Shoup, 2006).

Transportation planners should understand the factors that affect parking behavior and the solutions to support sustainable mobility. Cruising for parking has economic implications for commuters because it increases gasoline consumption and vehicle miles traveled (VMT), resulting in higher travel costs and travel times. From the public perspective, cruising increases congestion, air pollution, and loss of economic activity. It is important to understand the factors determining the optimum parking pricing, which refers to an equilibrium or balanced relationship between curb and off-street parking, which minimizes cruising time. These factors include off-street parking availability, pricing, occupancy rate, and technological innovations to manage parking properly. Relatively expensive parking also increases cruising (Shoup, 2006). A proper policy to improve parking and reduce cruising should carefully understand parking costs and the implications for drivers with different socioeconomic backgrounds.

Transportation planners study travel behavior theory to understand parking demand in urban areas. Choice models help identify the factors that influence drivers’ decisions for parking in different urban contexts. These studies suggest drivers prefer to park in a location just before their destination (Behrendt, 1940). Thus, distance to the destination is a significant factor influencing parking choices. Parking behavior is complex because numerous factors influence the final decision (Parmar, Das, & Dave, 2020).

Studies concur that social-economic factors such as income, age, parking availability, and space influence parking behavior. Complex models have addressed the limitations of previous studies. For example, Guo et al. (2013) compared two choice models. One model assumes that all drivers make decisions simultaneously, and the other model considers the variety of individual psychological characteristics. The results showed that the latter had a higher accuracy for prediction. Ottomanelli, Dell’Orco, and Sassanelli (2011) used a model to study behavior about uncertainty. In this model, the imperfect knowledge was about the pricing scheme, the enforcement of parking violations, the distance between parking spot and opportunity (destination), and the presence of congestion. Overall, the psychological and socioeconomic characteristics of drivers, the parking facility, and the characteristics of alternative parking impact choices. Also, parking pricing, cruising time, and walk time are more significant predictors of parking behavior than fuel cost and commuting time (Parmar, Das, and Dave, 2020). Scholars agree that informed, dynamic, and publicly available information on pricing policies, rather than free parking, can alleviate the auto-dependency rate, decrease car trips, and prevent the negative externalities of parking or the emergence of the proliferation of informal or illegal parking.

Reassessing minimum parking requirements

This section discusses the implications of minimum parking requirements, which often use simplistic methods to estimate the parking needs by building use and structure. These assessments consider the peak parking occupancy collected in surveys in suburban areas, which typically results in overestimating parking demand.

Some cities simply replicate the parking requirements of other cities, and thus the excessive or insufficient parking spreads. Alternative approaches could stop the spread of outdated or excessive municipal parking requirements. One alternative strategy could include curbside/on-street parking spaces to meet the minimum requirement. In addition, the transportation engineers and planners determining typical parking demand could consider the average parking demand instead of peak demand.  This may be a more precise estimate of parking needs throughout the year. Excessive parking in U.S. cities also increases the rate of vacancy or underutilization of land. Studies in U.S. cities have reported a vacancy rate that ranges from 40 to 60% (Shoup 2006) and an oversupply of parking ranging between 30 to 90% in downtowns and between 20 to 66% in the suburbs (Weinberger & Karlin-Resnick, 2015). This means parking lots associated with vacant or low-occupied buildings are usually empty or underutilized. Thus, scholars recommend reducing vacancy to 35% because it will affect required parking (Shoup 2006). More recent strategies pose a vacancy rate of 15% in parking areas as an optimum goal to reduce parking-related traffic because parking supply and demand remain balanced. This strategy may prevent car spillovers on roads looking for parking while ensuring vacancy or availability in parking spots.

Scholars also propose shared parking as another solution to support sustainable parking practices. Businesses may benefit from shared parking as they have more flexibility for their businesses and spaces. The city may also benefit as less land is dedicated to parking, reducing the demand for services and infrastructure.

Scholars and practitioners also recommend establishing a maximum parking ratio, a strategy many European cities use. Also, reducing parking for transit proximity is another innovative strategy that draws on the assumption that commuters will drive less in areas with good transit access. If parking land is optimum, cities may increase their population densities, and thus commuters will be likelier to use transit or non-motorized modes of transportation.

Pricing parking is another effective strategy to reduce cruising and parking congestion. This policy may also benefit cities by generating revenues supporting numerous urban improvements. Revenues can be used to improve neighborhoods or allow green spaces for people and promote sustainable mobility practices. Pricing parking helps compensate for the negative externalities of driving and could foster transportation equity (Rutman et al., 2013). The Twin Cities, Minneapolis, and Saint Paul have examined the potential benefits of eliminating, to some extent, minimum parking requirements. These benefits include improvements in urban design and densities, the mitigation of traffic congestion and air pollution, the revitalization of neighborhoods, and a reduction in the costs of goods and services.

Case Study: San Francisco’s Parking Management Program

This section examines the benefits and challenges of a pioneer program implemented in the San Francisco Area. In 2017, the San Francisco Municipal Transportation Agency (SFMTA) approved a program to manage parking demand using responsive pricing technology for on-street parking. This program uses state-of-the-art sensors and smart meters in parking lots. The logic behind demand-responsive pricing is that pricing will limit parking supply resulting in the balance between parking supply and demand. Prices fluctuate depending on the parking spots’ occupancy rates. Drivers may choose to park in vacant parking spots and walk longer distances to their destinations or pay higher prices for spots in highly occupied locations. This program seeks to estimate the pricing cost to enable sustainable parking behavior properly. Parking management allows cities to efficiently manage parking in congested areas, such as San Francisco’s downtown and its landmarks (Pierce and Shoup 2013).

The city of San Francisco first implemented a trial for its parking management program. This trial included seven pilot zones where sensors helped document the occupancy rate of curb parking on each space in all blocks within the zones. Sensors use occupancy variables to estimate variable pricing according to the levels of vacancy and the time of the day. The initial objective was to achieve an average occupancy rate between 60% and 80%. Parking is more expensive as occupancy increases, and the price decreases as occupancy decreases. Parking management allows motorists to make decisions depending on the price and proximity of parking to their destinations.

The implications of San Francisco’s demand-responsive parking for mobility

San Francisco’s management parking shifted occupancy from high to low in congested areas where drivers park for long periods. This program also contributes to a more uniform and homogenous distribution of parking demand across different neighborhoods rather than excessive or low demand in one area, such as downtown locations. Pierce and Shoup (2013) estimated parking demand price elasticities to examine this program’s implications. Their study showed that price elasticities vary according to urban factors. Drivers are likelier to change their driving behavior in the commercial than in residential land use. Also, parking demand is more responsive to the policy in the afternoon than in the morning when changes are insignificant. This is explained by the fact that work and school trips occur in the morning while commuters conduct social recreation trips in the afternoon. Social recreation trips were associated with users of parking management.

Price is another factor that influences the behavioral responses of drivers. Elasticities fluctuate according to changes in prices. One interesting result from the San Francisco parking program is that price elasticities vary across different locations (even adjacent blocks), indicating that other factors besides price influence parking demand. For example, San Francisco’s parking program mostly restricts drivers and thus barely affects low-income commuters who mostly use transit. Moreover, the San Francisco Transportation Authority uses revenues from the parking management program to support transit, supporting the commutes of low-income residents.

However, one possible challenge with this demand-responsive program is providing real-time data for drivers demanding to park. Another empirically observed issue is disabled placard abuse from users. Technological innovations to monitor compliance may help address this issue. Also, future research should use predictive models that help explain the behavioral responses of drivers to the policy. Furthermore, parking management should understand how parking behavior changes during holidays, celebrations, and parades. For example, the program does not sufficiently consider the increased parking demand during Christmas. The program should therefore consider changes in parking demand throughout the year.

The new San Francisco parking program aims to maintain an occupancy rate of around 80% to mitigate cruising by motorists (Arnott and Rowse 1999). Millard-Ball, Weinberger, and Hampshire (2014) found that the program effectively reduces cruising time. However, drivers can also park in alternative locations that lack metered parking, increasing driving and commuting distances. This occurs when strategic drivers choose to park in areas where parking is more expensive but for shorter periods of time (Glazer and Niskanen 1992). The temporal pattern of cruising also shows that the probability of a block being full and the average cruising time would rise drastically immediately after SF parking operation time. Most price-sensitive drivers delay their arrival until after the operating hours of the SF program.

Another challenge in implementing the program is the emergence of informal parking forms. Future and more comprehensive assessments of the efficacy of the San Francisco Management Program should consider various metrics or variables, including average occupancy in different block sizes and land uses (Millard-Ball, Weinberger, and Hampshire 2014). The San Francisco Management Program has developed a fine-grained database that could allow transportation planners to understand the effectiveness of responsive pricing better. The data can also be used to understand better how the program influences travel behavior and congestion.

Conclusion

This chapter unpacks the negative consequences and costs of minimum parking policies and standards in US cities and how they have contributed to sprawl, low-density, car-oriented land development pattern, and induced car trips. The chapter further elaborates on cruising for parking in congested areas as a parking behavior that significantly impacts traffic volumes on different corridors, such as an increase in VMT. This chapter reviews current programs across US cities that have tried reducing minimum parking requirements to free up land and reduce car trips. The case of the San Francisco parking program (SF-Park), which is a demand-responsive parking pricing scheme for on-street parking, shows how these new policies can adjust parking demand and supply, produce more parking vacancy rates, and more.

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