Parking Regulation and Management

The Emerging Tool for a Sustainable City

Daniel Albalate, Albert Gragera, Daniel Albalate, Albert Gragera

• Editorial: Routledge
• Año: 2020
• ISBN:
  9781000196535
• Edición: 1
• Categoría: Business
• Categoría: Transportation Industry

Containing some of the most recent and original studies on parking regulation and management from different disciplines, this book offers rigorous analysis from top researchers with a clear intention to deliver policy implications and provide information to the public.

The book is organized according to a variety of key topics. Among others, it covers the interaction of parking with other modes of transportation and its demand, its pricing and external effects, the role of information and digitalization, and the effects of regulation and its enforcement. Also, it includes the views of practitioners, who discuss present parking in cities and the future of its management.

Written primarily for scholars interested in transportation, mobility, planning and urban affairs, this book is also directly relevant to practitioners and policymakers in government with responsibilities in mobility. Additionally, the book will be of interest to the private sector as it offers a practical link between rigorous academic analyses and the needs of practitioners.

1 The external cost of parking

An overview of its impact on traffic systems

Monica Menendez

1 Relation between the urban parking and traffic systems

The urban parking and traffic systems are two essential components of the overall urban transportation structure. These two systems heavily depend on one another: When conventional cars are used, every trip must begin and end in a parking spot. Therefore, parking availability or lack thereof may determine the number of trips made by private cars (Marshall and Garrick, 2006). This, in turn, combined with the appeal and availability of other transportation modes, may determine the prevailing transportation mode share (Hess, 2001), ultimately affecting the activity patterns in the city and the usage of the transportation system, with its associated externalities (e.g. congestion, pollution). It is well known that parking (and private car) policies have a clear impact on the built environment and ultimately on the quality of life in urban areas. Cities that rely heavily on the use of private cars must provide large amounts of parking (McCahill and Garrick, 2010), which has been linked to the loss of ecosystem services, increased levels of runoff and pollutants (Davis et al., 2010), and the formation of urban heat islands (Onishi et al., 2010). To mitigate these negative externalities, many cities are limiting parking and/or car usage in specific areas. Nonetheless, it might be wise to implement such limits selectively to guarantee a minimum level of mobility through private cars. Finding the equilibrium can be complicated as short-term and long-term interactions between the urban parking and urban traffic systems must be taken into account.

In this chapter, we will describe those short-term and long-term interactions. In particular, we will focus on the impact of cruising for parking and how this phenomenon is affected by different parking regulations; the impact of illegal parking; and the impact of on-street parking maneuvers. We will also briefly discuss other parking externalities beyond traffic congestion and how these might change with new vehicle technologies.

1.1 Long-term interactions between urban parking and traffic systems

The long-term interactions between urban parking and traffic systems can undoubtedly shape the city and its quality of life. In particular, the availability of parking can, in the long run, shape a city’s modal transportation share and activity patterns (Habib, Morency and Trépanier, 2012). Availability, in this case, includes more than the overall parking supply (i.e., total number of parking spaces). It is also a reflection of any parking policies in place, e.g., pricing and time controls. Parking policies could, indeed, dictate turnover rate (i.e., how many cars can use a single parking space over a period of time). Therefore, parking policies and control mechanisms can shape the travel demand (Feeney, 1989) and ultimately the mobility in a city. For instance, restrictions in the parking supply, combined with high parking prices could, in the long run, shift the transportation demand towards other transportation alternatives, gradually reducing reliance on private cars.

1.2 Short-term interactions between urban parking and traffic systems

The short-term interactions between the urban parking system and the traffic system can greatly influence the individual performance of the two systems. For instance, the urban parking system can partially dictate the amount of traffic searching for parking (cruising for parking). This, in turn, can affect the total driven distance as well as the travel speeds in the network. On the other hand, traffic conditions can influence the amount of time spent searching for parking or even reaching a specific parking spot. This, ultimately, can affect parking usage and the resulting parking availability.

Unfortunately, while the long-term effects have attracted attention in the literature for quite a while (Young, Thompson and Taylor, 1991), the short-term interactions and their effects are less understood. These short-term interactions can lead to traffic congestion not only through the cruising-for-parking phenomenon mentioned above but also through other mechanisms. For example, a concentrated supply of parking might generate traffic peaks (e.g., people exiting a large parking garage in an urban area after a sports event). Alternatively, people wanting to enter a popular off-street parking location can queue on the road, blocking other traffic. Last, illegal parking and on-street (curbside) parking maneuvers can also affect traffic in urban networks by blocking driving lanes.

2 The impact of cruising for parking

The magnitude and impact of the cruising-for-parking phenomenon was all but ignored for some time. Since the work of Shoup (2005), however, there has been a growing interest in the quantification and understanding of this phenomenon, mostly aimed at designing countermeasures. Shoup (2005) estimated that vehicles cruising for free parking spaces can make up over 8% of the total traffic in a city and as much as 30% during rush hours in business areas. This additional traffic increases the city’s overall traffic density¹, which leads to lower speeds and potentially congested or hyper-congested traffic conditions (Geroliminis, 2015). The estimation, however, of the cruising-for-parking phenomenon is not a trivial task.

Empirical studies on the cruising phenomenon have relied on survey data, the observation of videos of urban traffic, and volunteers who personally cruise in an attempt to find parking spots. Some of these studies date back to 1927 (Shoup, 2006). Unfortunately, their accuracy is not as high as might be desired. Survey respondents tend to overestimate undesirable and/or very short tasks. A direct observation of traffic, or even the use of GPS tracking devices within vehicles, does not necessarily show when a driver starts looking for parking as this can happen even without changes in speed. Last, the employment of volunteers is typically quite limited so that the results obtained might or might not be representative of the overall system.

To overcome the data limitations, the cruising phenomenon can also be modeled based on the likelihood of finding parking. To that end, some of the models have proposed relatively complicated relationships between parking occupancy² and cruising, e.g., using a decreasing exponential function (May and Turvey, 1985). Others have resorted to a very simple description of the process, e.g., using Bernoulli trials where the probability of finding a parking spot is given by the ratio between the number of available parking spaces and the total number (Leclercq, Sénécat and Mariotte, 2017). This binomial approximation is mostly accurate in scenarios where the occupancy rate is low, but it can lead to underestimations of cruising time as the parking occupancy increases (Arnott and Williams, 2017). This happens because the cruising time is a function not only of the parking occupancy but also of the parking demand, represented by the competition between drivers (Cao and Menendez, 2015b). Especially, as the parking occupancy increases, the competition among drivers to find parking becomes more relevant (Jakob and Menendez, 2020a).

Therefore, it is evident that any policy that affects the likelihood of finding a parking space ultimately affects the cruising-for-parking phenomenon. Examples of such policies include overall parking supply, parking pricing, parking time controls, and the provision of parking information. All these policies have both advantages and disadvantages. Thus, before implementing one, it is advisable to conduct a holistic analysis regarding its impact, taking into account multiple parking and traffic metrics. Below, we provide additional details and briefly discuss the advantages and disadvantages associated with each of these policy types.

2.1 Overall parking supply

Given that every trip starts and ends in a parking spot, the regulation of parking supply can have significant consequences for car ownership, mode choice, etc. Unfortunately, calculating the optimal number of parking spaces that a city should provide is not so simple. On the one hand, too much parking takes up valuable space, increases car demand and potentially generates more traffic-related problems. On the other hand, not enough parking generates cruising, affects the overall traffic performance, creates delays and potentially damages the environment through additional emissions.

Traditionally, cities have set standards for the minimum levels of parking required (e.g., employers are expected to provide at least a minimum number of off-street parking spaces per unit of surface area or employee). More recently, some cities have been setting standards for maximum parking levels. The minimum parking standards have proven to be inefficient not only in the long run, by generating additional demand, but also in the short run, by generating vacant spaces and wasting resources. In contrast, the maximum parking standards can induce mode choice, potentially lowering the number of vehicles in an area in the long run (Arnott, 2006). In general, reducing the parking supply, especially in downtown areas, leads to higher usage of public transportation and, hence, less driving (Morrall and Bolger, 1996). For instance, a study of 770 households in the New York City region found that residential parking supply is more important than household income and demographic characteristics in the decision to own a car. Moreover, the type of parking (on-street vs. off-street, driveway spaces vs. parking garages) also makes a difference (Guo, 2013). For instance, off-street parking seems to be more important than on-street parking in this decision.

In the short run, it is evident that increasing the parking supply reduces cruising, and vice versa. However, since the relationship between parking supply and cruising time is non-linear, the impact of increasing vs. decreasing parking supply on average cruising time is not symmetric. On average, the extra cruising time generated by decreasing the parking supply is much larger than the cruising time saved by increasing it (Cao, Menendez and Waraich, 2019). In theory then, one could estimate the optimal amount of parking supply by balancing the total cruising time generated with the cost of offering such infrastructure.

When it comes to cruising time, the distinction between parking types is also very important as, normally, on-street parking generates more cruising than off-street parking. While some experts advocate for the use of on-street parking over off-street parking to promote a more efficient use of land (Marshall, Garrick and Hansen, 2008), some cities (e.g., Zurich in Switzerland) are converting on-street parking facilities into parking garages (Jakob and Menendez, 2019). This releases valuable urban space for other modes or activities. Moreover, it is possible that if all on-street parking spaces are converted into off-street parking, assuming there is enough capacity in the off-street parking facilities, cruising could be eliminated.

2.2 Parking pricing

Parking pricing can be a very effective mechanism to regulate long-term parking demand, e.g., high parking prices might deter people from driving into a specific area (Jakob and Menendez, 2020b). At the same time, in the short run, parking prices might be used to incentivize specific parking behaviors (e.g., increase turnover rate, direct drivers to specific parking areas, etc.).

When it comes to parking pricing, one must distinguish between on-street and off-street parking. These two systems oftentimes have different operators, thus different pricing policies. Traditionally, on-street parking is provided by the city government, while off-street parking (especially garage parking) might be privately owned and operated. As a result, off-street parking operators tend to have more flexibility in their pricing schemes. Unfortunately, such pricing schemes are rarely regulated and do not necessarily benefit the system. On average, off-street parking prices tend to be much higher than on-street parking prices, unintentionally promoting cruising (Jakob and Menendez, 2019). That being said, the private ownership of off-street parking is not necessarily a negative thing. If there are enough owners so that pricing is not set in a monopolistic manner but based on a competitive market, the equilibrium could be equivalent to a social optimum (Anderson and De Palma, 2004). Alternatively, if cities could regulate both on-street and off-street parking prices, it would be easier to find strategies leading to social optimum (Inci and Lindsey, 2015). An analysis of over 10,000 observations in the Netherlands revealed that only about 30% of trips involved some cruising, and the average cruising time was just 36 seconds (Van Ommeren, Wentink and Rietveld, 2012). These low cruising numbers were mostly explained by the Dutch policy of paid parking, where the average hourly fee for on-street parking is almost identical to that of off-street parking.

For most cities, however, this is not the case, and on-street parking is normally much cheaper than off-stre...