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The economizing of curb parking space
... It is rather well-known that parking is usually provided free to users (Shoup, 2005). There is however surprisingly little information to what extent not charging for parking creates welfare losses, although this is the central theme in the economics of parking literature (Vickrey, 1954;Roth, 1965;Arnott et al., 1991;Inci, 2006, 2010;Anderson and De Palma, 2004;Kobus et al. 2013;Van Ommeren et al., 2011. One recent paper concluded that underpricing of parking for workers may create substantial welfare losses . ...
... We continue on this theme by estimating the welfare loss of nonoptimal pricing of parking of hospital workers in the Netherlands. Vickrey (1954) recommended to use time-varying parking tariffs to deal with variation in demand for parking. 2 This is in line with the more general principle that the price of a good must be vary with time-shifts in demand when changes in supply are costly. 3 It is unknown to what extent efficiency losses in the parking market are substantial when time-invariant parking tariffs are applied. ...
... In particular, it varied the parking price over the days of the week, after a period when it varied only with workers' commuting distance. To vary price per day is rather uniquewe are not aware of any other organisation employing this practiceand in line with economic theory to deal with variation in demand (Vickrey, 1954). Importantly, for the current paper, charging on a daily basis is useful as a quasi-natural experiment to identify the causal effect of pricing on workers' parking demand. ...
... Predictive models for demand have also a great value for parking operators and can be used to develop forecasts of revenue [3] or to improve prices through performance pricing [4]. Recommendations for variable pricing of parking are around for a long time [5]. Understanding the demand of competitors is also beneficial to improve parking policies [6]. ...
... http://www.mdm-portal.de.4 As of September 2015: Aachen (only charging stations), Düsseldorf, Frankfurt am Main, Kassel, Magdeburg, and Wuppertal.5 Parties interested in accessing the data still need to register with the MDM portal and setup security certificates to receive data. ...
This paper focuses on demand forecasts for parking facilities. Our work utilizes open parking data for predictions. Several cities in Europe already publish this data continuously in the standardized DATEX II format. Traffic related information will become more ubiquitous in the future as all EU-member states must implement real-time traffic information services including parking status data since July 2017 implementing the EU directives 2010/40 and 2015/962. We demonstrate how to extract reliable and easily comprehensible forecast models for future-parking demand based on open data. These models find multiple use cases not only on a business planning level and for financial revenue forecasting but also to make traffic information systems more resilient to outages and to improve routing of drivers directing them to parking facilities with availability upon predicted arrival. Our approach takes into consideration that the data constitutes irregular time series and incorporates contextual information into the predictive models to obtain higher precision forecasts.
... Starting from Vickrey (1954), economic theory in general, and multiple studies in particular, prescribe to tackle the problem of curbside parking congestion with price regulation. ...
... This paper develops a policy of pricing parking that formalizes the intuition of congestion pricing by Vickrey (1954). It is shown that the optimal policy differs from the occupancy target policy currently being implemented in San Francisco and in Los Angeles: the price should depend not only on the occupancy but also on the arrivals rate. ...
A model of demand for parking, evolving over time, is proposed. The model features both extensive (whether to park) and intensive (for how long to park) margins of parking demand, allows multidimensional heterogeneity of parkers, and evolution of demand throughout the day. I show that the optimal price for parking is proportional to the rate of arrival of new parkers and is inversely related to the square of the occupancy rate, which is different from previously discussed pricing methods. I show that the primary purpose of pricing is to regulate departures, rather than arrivals, of parkers. I also find that asymmetric information about parkers’ characteristics does not prevent the parking authority from achieving the social optimum. A numerical example compares the optimal policy against the alternatives.
... As a result, on the few days that it is hot there is extreme congestion on roads close to the beach as well as parking congestion at the beach as travelers aim to arrive at the same destination around the same time (Arnott et al., 1991). This congestion problem receives relatively little attention in transportation research and policy, although it receives quite some attention in the media. 1 We emphasise that public authorities do not use economic tools to reduce demand for travel to the beach by car or car parking near beaches during peak hours, although time-varying pricing of parking at beaches may result in strong welfare gains as both demand for parking as well as travelling to beaches will be reduced (Vickrey, 1954;Arnott and Inci, 2006). Furthermore, it is extremely expensive to increase supply of roads as well as parking near beaches, because peak demand occurs only a limited number of days per year. ...
... It is emphasized that the application of road pricing which depends on weather conditions is hardly feasible. However, our results indicate that the introduction of appropriate weather-specific pricing of parking at beaches likely result in strong welfare gains as both demand for parking as well as traffic congestion near beaches will be reduced (Vickrey, 1954). In the Netherlands, electronic parking charges are standard so adapting parking charges on a daily basis is straightforward, so this policy seems feasible and cheap to implement and information on the price variations can easily be obtained via the internet. ...
This paper investigates the welfare effect of adverse weather through changes in the speed of individuals' car commuting trips in the entire Netherlands. Weather measurements are local and time specific (hourly basis). As most commuters travel twice a day between home and work, we are able to estimate the effect of adverse weather employing panel data techniques, which is novel in this context. We find that for most commuters the welfare effects of adverse weather conditions are negative but small. However, the commuters' welfare costs due to rain are rather substantial during rush hours in congested areas (and up to 15 percent of the overall commuting costs).
... On-street parking in urban environments has a spectrum of adverse impacts, including increased traffic from parking space searches and the associated greenhouse gas emissions (Shoup, 2006;Van Ommeren et al., 2012); as such, parking policies form a critical part of efforts to reduce these emissions and achieve the Sustainable Development Goals set by the United Nations (Wenz et al., 2020). Implemented parking management policies, like pay parking, have been shown to influence transportation decisions and user behaviour, delivering benefits such as reduced parking search, increased parking turnover, and improved spatial parking distribution among users (Ball, 2013;Vickrey, 1954). ...
Due to the issues of land redevelopment and changes of use within urban areas, many cities must adopt measures to reorganise and optimise parking space. This paper proposes a methodology to study one of them by implementing parking information systems (PIS). This solution offers users a competitive advantage by allowing them to know about the free parking spaces at the moment of decision-making. To achieve this goal, microscopic simulations are conducted to analyse the effects of various scenarios involving the implementation of PIS. The data used in these simulations is obtained from the Santander area in Spain. For the evaluation of results, a methodology has been developed that combines the evaluation of social factors for citizens and operational impacts for decision-makers. The results show significant improvements with increasing user information rate, e. g., the number of unsuccessful parking attempts before finding a final parking space is reduced by 55%, and 37% less particulate pollutants are emitted into the atmosphere.
... We listed it here separately because, due to the effectiveness of implementation, many cities and regions have adopted it as an acceptable administrative policy. The earliest research on this topic is Vickrey's study [37] of parking fees, which con-tributed to the conclusion that it is wise to change parking prices at various times or locations. An increasing number of scholars subsequently began to explore the parking pricing problem [38][39][40]. ...
Using an incentive measure to encourage people to share their private parking spaces could be an effective strategy for urban parking problems. This paper discusses an innovative mechanism of shared parking, “FlexPass,” which applies a reverse auction in which drivers propose bids in line with their individual expectations to share their idle parking spaces. The auction mechanism, hypotheses on bidding process principles, the competitive environment, and the risk-averse decisions of providers with regard to parking spaces are analysed to explore the sustainability of the economic benefits obtained for FlexPass parking spaces. A total of 216 respondents from the University of California, Berkeley, were invited to participate in bidding in an actual survey during their daily use of parking spaces. The analytical results show that operational rules based on risk aversion can enable profit-seeking with a bounded capability to obtain considerable economic benefits and release parking resources in an environment of demand competition. Particularly in some scenarios, FlexPass would sacrifice a certain monetary income to ensure the perceived benefits of parking space providers. With the improvement of people’s enthusiasm for participating in shared parking, the benefits to individuals and parking lots would be further enhanced, suggesting that our mechanism can operate sustainably over the long term. These findings are helpful for policymakers to formulate feasible shared parking policies from the perspective of monetary incentives.
... Pricing of curbside parking can reduce the demand for parking very effectively. As early as 1954, Vickrey (Vickrey, 1954) claimed that parking prices should be varied spatially and temporally to respond to demand heterogeneity. Shoup (2006) continued this line and suggested that keeping 85 % occupancy on every block, or about 1 in 7 vacant parking places, would allow drivers to find parking quickly and, at the same time, be sufficient for maintaining economic activities in the area. ...
Scarcity of on-street parking in city centers is a known factor motivating drivers to drive slowly (“to cruise”) while searching for an available parking place and is associated with negative externalities e.g. congestion, accidents, fuel waste, and air pollution. Finding the correct prices is suggested to bring cruising to a sustainable level. Current research methods based on surveys and simulations fail to provide a complete understanding of drivers’ cruising preferences and their behavioral response to price changes. We used the PARKGAME serious game, which provides a real-world abstraction of the dynamic cruising experience. Eighty-three players participated in an experiment under two pricing scenarios. Pricing was spatially designed as “price rings” decreasing when receding from the desired destination point. We analyzed search time, parking distance, parking location choice, and spatial searching patterns. We show that such a pricing policy may substantially reduce the cruising problem, motivating drivers to park earlier—further away from the destination or in the lot, especially when occupancy levels are extremely high. We further discuss the policy implications of these findings.
... Parking, as one of the major contributors to urban congestion, brings great challenges to public agencies [1][2][3][4][5][6]. A study by Axhausen et al. [7] points out that the time spent cruising for parking can account for 40% of total travel time. ...
Parking plays an essential role in urban mobility systems across the globe, especially in metropolises. Hong Kong is a global financial center, international shipping hub, fast-growing tourism city, and major aviation hub, and it thus has a high demand for parking. As one of the initiatives for smart city development, the Hong Kong government has already taken action to install new on-street parking meters and release real-time parking occupancy information to the public. The data have been released for months, yet, to the best of our knowledge, there has been no study analyzing the data and identifying their unique characteristics for Hong Kong. In view of this, we examined the spatio-temporal patterns of on-street parking in Hong Kong using the data from the new meters. We integrate the t-SNE and k-means methods to simultaneously visualize and cluster the parking occupancy data. We found that the average on-street parking occupancy in Hong Kong is over 80% throughout the day, and three parking patterns are consistently identified by direct data visualization and clustering results. Additionally, the parking patterns in Hong Kong can be explained using land-use factors. Overall, this study can help the government better understand the unique characteristics of on-street parking and develop smart management strategies for Hong Kong.
... Active management can take many forms, but the most developed experience has been in the realm of parking, where there is a large body of literature on the policies that can be used to manage the parking supply in the face of variable demands and raise revenues for municipalities. Economists have endorsed the idea of pricing transportation infrastructure, such as parking spaces at least since Pigou (1920), and of varying this price by time-of-day (Vickrey, 1954). Despite the theoretical benefits, the practice of pricing street parking has been controversial since the first parking meters were installed in Oklahoma City in 1935(ITF, 2018. ...
Demands for use of the curb space (curbside lanes and the adjacent sidewalk space) are evolving quickly across the Commonwealth of Massachusetts as municipalities of all sizes juggle the competing needs of pedestrians, cyclists, transit, transportation network companies (TNCs), in addition to conventional uses for parking, goods delivery, and emergency access. The problem is further complicated by the potential deployment of e-bikes, scooters, and automated vehicles. Guidance for curb management is needed for communities of all sizes across the Commonwealth where the context can vary from dense urban environments to small town centers. Whereas curb management policies in the past have typically focused on vehicles and parking, future curb policies must recognize the diverse ways that people use the curb in a multimodal transportation system. This study addresses two objectives: 1) to explore the demands on the curbside lane and identify strategies for curb management for municipalities across the Commonwealth of Massachusetts, and 2) to identify future demands on the curbside lane and how these demands can be accommodated. The guidance in this report is based on a review of recent literature on curb management practices and focus group interviews with stakeholders from across Massachusetts.
... The external costs of parking provision comprise the external costs of cruising for parking, stemming from the time losses caused by searching for a space, and the external costs of open space lost to convert land to parking space (see also Inci, 2015). External costs of congestion and air emissions vary across space and over time and, hence, parking tariffs should ideally be space-and time-variant (Vickrey, 1954, cited in Inci, 2015. Perhaps the most well-known real-world application of space-and time-varying parking tariffs is San Francisco's SFpark programme (see Pierce and Shoup, 2013). ...
This chapter discusses policies to control urban sprawl and direct urban development to more sustainable pathways. It describes a number of land-use and transport policy instruments that can be used to achieve these objectives and analyses their potential benefits, but also the challenges arising in their implementation. The land-use policy instruments analysed include urban containment policies (e.g. greenbelts, urban growth boundaries), minimum density restrictions, property taxation, development rights and incentives for private provision of public infrastructure. Road pricing, parking policies, motor fuel taxes and investments in sustainable transport infrastructure are the main transport-related policy instruments considered in this chapter. The chapter also highlights the importance of taking into account interactions between different instruments when it comes to the development of urban policy. Finally, it emphasises the need for an integrated approach to make urban development patterns more sustainable.
... Even if on-street parking spaces in an area might have low occupancy rates at specific times of the day, there might be times when drivers must spend a considerable amount of time cruising for parking (Shoup (1999(Shoup ( , 2005(Shoup ( , 2006). Vickrey (1954) was the first to discuss the possibilities of achieving a specific on-street parking occupancy rate such that there is a parking space on each block available at almost all times. His proposal decreases congestion and the cruising-for-parking time on the network, and it could be achieved through smart onstreet parking pricing policies. ...
Parking policies and their interactions with the urban traffic and parking systems can have significant impacts on the traffic performance and the congestion in an urban area. These impacts have a long-term component affecting the travel demand and the travelers’ preferences, and a short-term component affecting the traffic and parking operations. This dissertation studies multiple parking policies focusing on pricing and occupancy aspects and analyzes their short-term impacts on the parking searchers and the performance of the traffic and parking systems, which, in turn, might impact the efficiency of the parking policies themselves. In other words, we investigate the interdependencies between different parking policies and parking-caused traffic issues. In particular, we evaluate the influences on the searching-for-parking traffic, the congestion in the network, the total driven distance, and the revenue created by parking, park and ride (P+R) fees, and/or congestion tolls for the city. We show the results for the different parking policies in some case studies of a central area within the city of Zurich, Switzerland. Our easy to implement model uses a dynamic macroscopic framework which saves on data collection efforts and reduces the computational costs significantly as all values correspond to aggregations at the network level over time. Our work clusters the parking policies into two types. First, we study static and dynamic parking pricing strategies and second, we investigate parking occupancy related strategies.
i. At the beginning of this dissertation, we focus on a macroscopic on-street and garage parking framework which allows us to model the drivers’ decision between searching for an on-street parking space or driving to a parking garage instead. Different static on-street and garage parking fee ratios are analyzed with respect to the impacts on the traffic system and the parking search model over time. Our framework shows how traffic performance issues might influence the drivers’ decision between on-street and garage parking in the short-term. This decision is faced by multiple user groups with respect to their value of time (VOT). We study the impacts of different parking policies, including the availability of real-time garage usage information, and the conversion of on-street parking to garage parking spaces. The recovered on-street curb can then be used for other activities (e.g., bike lanes) in order to improve the quality of life for the city’s residents.
Another strategy for cities might be to establish a P+R facility outside the city in order to reduce the searching-for-parking traffic in the central area. We analyze a P+R policy with static fares and compare it to a congestion pricing scenario and/or parking pricing policy in the network. In case the area consists of a high number of public parking spaces, parking pricing could be considered as a viable alternative to congestion pricing in terms of improving the performance of the traffic and parking system (i.e., traffic performance, parking availability, revenue for the city, etc.). Different parking fees or traffic conditions might, however, affect the drivers’ decision between entering the network by car or using P+R instead. We propose a decision model with respect to the drivers’ VOT and integrate it into a multimodal macroscopic traffic and parking framework focusing on parking and congestion pricing. We evaluate the distributional effects of our heterogenous VOT model on the drivers’ decision of which mode (P+R or car) to use when entering the area. Additionally, the proposed methodology can be used by city councils to find the trade-offs between the parking fee and the congestion toll when looking to reduce the average cruising time in the network, or increase the total revenue for the city.
Moreover, we study a dynamic responsive parking pricing scheme which takes the parking search phenomenon and the parking occupancy into account. This macroscopic pricing policy maximizes the parking revenue for a city while minimizing the searching-for-parking time simultaneously. In different words, our pricing algorithm changes in response to the parking occupancy rate and the number of searching vehicles on the network. It checks whether the cost of paying the current parking fee is lower than the cost of keep on searching for another available parking space depending on the drivers’ VOT. The latter cost includes paying the predicted parking fee for the next available parking space at a future time slice under consideration of the driving and penalty costs to get there. We show the short-term impacts of the proposed dynamic parking pricing scheme on the urban traffic and parking systems, including the financial benefits of the pricing scheme and the benefits (or disbenefits) for the traffic performance in the area.
ii. As the second type of parking policies, we study parking occupancy strategies in this dissertation. Here, we model the optimal parking occupancy rate over, e.g., the peak hours of the day, to guarantee an optimal trade-off between an efficient usage of the parking infrastructure and a high likelihood of finding parking to improve the traffic performance in a central area. In other words, our framework tries to find the optimal equilibrium between a high occupancy rate and a low average searching time in the network. It is based on the same macroscopic traffic and parking model that we used in the first part of the thesis. We extend it to include multiple vehicle types allowing us to generate insights about the parking occupancy’s dependency on specific vehicle types (e.g., fuel and electric vehicles). We evaluate a differentiated and a hierarchical parking policy for parking supply with and without battery chargers, and compare the results to a parking scheme without any parking differentiation. Our optimal parking occupancy strategy allows local governments to evaluate how to react towards a constantly varying parking demand (e.g., a modal shift towards electric vehicles), and how much parking supply to dedicate to electric vehicles in order to have the best balance between traffic performance, optimal parking occupancies, social impacts, and a high parking revenue for the city. Additionally, we provide cities a tool to analyze the influences on the optimal parking occupancy rate caused by a change in parking demand, supply, or parking duration in the area.
In general, we discuss various parking policies in this dissertation and develop the tools for cities to evaluate the short-term impacts on the traffic and parking system when applying such policies. We show how to evaluate them macroscopically with the minimum amount of data requirements and costs, as our algorithms can easily be implemented with a simple numerical solver. Parking planners, traffic managers, consultants, practitioners, and local authorities can then use the new insights about these parking policies to develop the best fit for their city.
... Economists were among the first both to question free parking and to explore how to optimally price parking. As early as the 1950s, economic studies verified that congestion would be reduced by increasing the cost of parking (Vickrey 1954, Roth 1965, Inwood 1966. Verhoef et al. (1995) suggested the possibility of using parking fees as a substitute for road pricing. ...
Metropolises in China, a rapidly motorizing nation, are confronted with the
challenge of managing parking pressures. Given the generally increased
affordability of cars, most local authorities are making efforts to provide more
parking spaces to accommodate additional cars. Although the worldwide
paradigm of managing parking is shifting from a supply-focused approach
to a restraint mind-set, China has been slow to follow this trend. To untangle
the factors that contribute to delays implementing desirable parking policy
reforms, this paper examines the development of parking policies in China.
This paper characterizes the challenge of parking in Chinese cities as a spatio�temporal mismatch. In the context of rapid motorization, local authorities
are subject to political pressure to cater to the increased parking demand
by increasing the minimum parking requirements. However, this approach
fails to mitigate parking shortages and results in unintended consequences,
including relatively high parking density in central and transit-rich areas
and imbalanced parking across neighbourhoods. This paper suggests four
strategies, including market-based pricing, geographically differentiated
supply regulations, and district-based parking management (“Parking
management is referred to as various policies and programs that result
in more efficient use of parking resources”). These strategies represent
policy-reform targets to establish more efficient parking systems in rapidly
motorizing urban settings worldwide.
... The external costs of parking provision comprise the external costs of cruising for parking, stemming from the time losses caused by searching for a space, and the external costs of open space lost to convert land to parking space (see also Inci, 2015). External costs of congestion and air emissions vary across space and over time and, hence, parking tariffs should ideally be space-and time-variant (Vickrey, 1954, cited in Inci, 2015. Perhaps the most well-known real-world application of space-and time-varying parking tariffs is San Francisco's SFpark programme (see Pierce and Shoup, 2013). ...
This book provides a new perspective to the nature of urban sprawl and its causes and environmental, social and economic consequences. This perspective, which is based on the multi-dimensionality of urban sprawl, sets the foundations for the construction of new indicators to measure the various facets of urban sprawl. The report uses new datasets to compute these indicators for more than 1100 urban areas in 29 OECD countries over the period 1990-2014. It then relies on cross-city, country-level and cross-country analyses of these indicators to provide insights into the current situation and evolution of urban sprawl in OECD cities. In addition, the report offers a critical assessment of the causes and consequences of urban sprawl and discusses policy options to steer urban development to more environmentally sustainable forms.
... Economists were among the first both to question free parking and to explore how to optimally price parking. As early as the 1950s, economic studies verified that congestion would be reduced by increasing the cost of parking (Vickrey 1954, Roth 1965, Inwood 1966. Verhoef et al. (1995) suggested the possibility of using parking fees as a substitute for road pricing. ...
Metropolises in China, a rapidly motorizing nation, are confronted with the challenge of managing parking pressures. Given the generally increased affordability of cars, most local authorities are making efforts to provide more parking spaces to accommodate additional cars. Although the worldwide paradigm of managing parking is shifting from a supply-focused approach to a restraint mind-set, China has been slow to follow this trend. To untangle the factors that contribute to delays implementing desirable parking policy reforms, this paper examines the development of parking policies in China. This paper characterizes the challenge of parking in Chinese cities as a spatio-temporal mismatch. In the context of rapid motorization, local authorities are subject to political pressure to cater to the increased parking demand by increasing the minimum parking requirements. However, this approach fails to mitigate parking shortages and results in unintended consequences, including relatively high parking density in central and transit-rich areas and imbalanced parking across neighbourhoods. This paper suggests four strategies, including market-based pricing, geographically differentiated supply regulations, and district-based parking management (“Parking management is referred to as various policies and programs that result in more efficient use of parking resources”). These strategies represent policy-reform targets to establish more efficient parking systems in rapidly motorizing urban settings worldwide.
... In 1950, the joint committee formed to solve metropolitan problems in Washington, Vickrey (1954) emphasised that like other products, parking should be priced based on its social marginal cost. He stated that the price of parking is a result of demand; therefore, it should be varied spatially and temporally. ...
The aim of this study is to assess and predict the effects of on-street parking cost elasticity on the mode choice behaviour of motorists. The stated preference method was used for data collection in the central business district of Qazvin, Iran, and the mode choice behaviour of motorists was modelled through different pricing scenarios. Using a multinomial logit model, it can be concluded that the price value of the motorist's car, car ownership per household, hourly parking rate, maximum hourly parking rate that the users are willing to pay, trip purpose and the education level of the users are significant in users' mode choice utility due to pricing. The results have indicated that by increasing the parking hourly rate from 500 to 60 000 IRR (Iranian Rial), 74% of users will shift their modes from private cars. Shares of choosing a taxi or bus will increase 28 and 18%, respectively.
... Early work focused largely on parking supply and demand [Vickrey, 1954], and refinement of the economic view of parking continues through today [Inci, 2015]. The costs of congestion caused by cruising for parking [Shoup, 2005, Shoup, 2006 have motivated research in modeling urban parking dynamics, and economizing of parking spaces has led to a desire to control demand levels via price. ...
To gain theoretical insight into the relationship between parking scarcity and congestion, we describe block-faces of curbside parking as a network of queues. Due to the nature of this network, canonical queueing network results are not available to us. We present a new kind of queueing network subject to customer rejection due to the lack of available servers. We provide conditions for such networks to be stable, a computationally tractable "single node" view of such a network, and show that maximizing the occupancy through price control of such queues, and subject to constraints on the allowable congestion between queues searching for an available server, is a convex optimization problem. We demonstrate an application of this method in the Mission District of San Francisco; our results suggest congestion due to drivers searching for parking stems from an inefficient spatial utilization of parking resources.
... The average percentage of cruising as a proportion of overall traffic observed in 10 studies from 1927-2011 was 34% (Shoup 2004). As long ago as 1954, Nobel-winner William Vickrey suggested that curb prices could be manipulated in order to suppress or stimulate demand with the goal of ensuring enough parking availability to eliminate or decrease cruising (Vickrey 1954). Traffic engineers have determined that approximately 80-85% average occupancy represents an optimal point at which one space per block should be available (Shoup 2004) (Millard-Ball, Weinberger and Hampshire 2014). ...
This paper analyzes a small, dynamically‐priced curb parking pilot that took place in Pittsburgh, PA from 2013 to 2015. Dynamic pricing of curb parking is a recent innovation – one which is designed to manage parking congestion through price manipulation in order to optimize occupancy and reduce traffic congestion. I find that prices declined during the pilot, revenues rose and occupancies moved towards target ranges set by program administrators. In the scant few studies of such pricing schemes, disagreement has arisen amongst scholars as to whether elasticities are appropriate to measure the effect of price changes on driver behavior. This paper demonstrates the use of the regression discontinuity statistical model in estimating the effects of price change effects on driver behavior. Regression discontinuity models suggest that prices had the intended effect on driver behavior during the Pittsburgh pilot, but such effects took a couple weeks to develop.
... Glazer and Niskanen (1992) noted that economists (e.g. Vickrey, 1954) generally assumed curbside parking to be a private good to justify marginal cost pricing. On the contrary, the authors demonstrated that insufficient parking spaces lead to cruising behavior, which results in increased costs for both travelers looking for parking as well as in-transit travelers. ...
In this study we present an on-street parking model for downtowns in urban centers that incorporates the often-neglected parking demand of delivery trucks. The behavior of truck deliveries is distinctly different from commuter parking: trucks do not cruise for parking spaces, and demand for goods delivery is driven by customers and is practically inelastic to the delivery costs. We generalize the downtown on-street parking model from Arnott and Inci (2006) to study the relationship between passenger vehicles’ parking and truck delivery behaviors, and provide tools for policy makers to optimize the trade-offs in parking space allocation, pricing, and aggregate network congestion. The social optimum can be obtained by solving a nonlinear optimization problem. The parking model is able to replicate the commuter-only scenario as a special case. It is shown that ignoring truck delivery behavior can significantly overestimate travel speeds and cruising stock. We applied the model to a case study of downtown Toronto and found that compared to a baseline scenario representative of Toronto in 2015, increasing parking fees from CAD 7.85/hour and assigning 4.1% of parking spaces to truck deliveries would eliminate cruising and truck double-parking, resulting in a social surplus gain of over CAD 2.47/hr would eliminate cruising and double-parking while increasing social surplus by CAD $24,883/hr/mi2. These model findings are along the same level of effect as demonstrated in the literature.
... Glazer and Niskanen (1992) noted that economists (e.g. Vickrey, 1954) generally assumed curbside parking to be a private good to justify marginal cost pricing. On the contrary, the authors demonstrated that insufficient parking spaces lead to cruising behavior, which results in increased costs for both travelers looking for parking as well as in-transit travelers. ...
This study presents an on-street parking model for downtowns in urban centers that incorporates the often-neglected parking demand of commercial vehicles. The behavior of truck deliveries is distinctly different from commuter parking: trucks do not cruise for parking spaces when parking is saturated, instead they are more likely to double-park near their destinations and occupy a travelling street lane.
The study generalizes the downtown on-street parking model from Arnott and Inci (2006) to investigate the relationship between commercial and passenger vehicles’ parking behaviors, and provide tools for policy makers to optimize the trade-offs in parking space allocation, pricing, and network congestion. The social optimum can be obtained by solving a nonlinear optimization problem.
The model is applied to a case study of downtown Toronto. It is shown that developing an inclusive policy, one that captures the effect of all road users including commercial vehicles, leads to considerable efficiency gains.
... Glazer and Niskanen (1992) 14 noted that economists (e.g. Vickrey, 1954) 15 generally assumed curbside parking to be a private good to justify marginal cost pricing. On the contrary, the authors demonstrated that insufficient parking spaces lead to cruising behaviour, which results in increased costs for both travelers looking for parking as well as in-transit travelers. ...
... The first to discuss regulation of parking in an economic context might be Vickrey (1954), who suggested time-varying parking fees as a means of regulating the use of parking space. Glazer and Niskanen (1992) present an analysis where parking fees are analyzed as a substitute for road pricing. ...
We consider commuting in a congested urban area. While an efficient time-varying toll may eliminate queuing, a toll may not be politically feasible. We study the benefit of a substitute: a parking fee at the workplace. An optimal time-varying parking fee is charged at zero rate when there is queuing and eliminates queuing when the rate is non-zero. Within certain limits, inability to charge some drivers for parking does not reduce the potential welfare gain. Drivers who cannot be charged travel when there is queuing. In some cases, interaction between morning and evening commutes can be exploited to remove queuing completely.
... It has a significant impact on the optimization of the model. As suggested by previous studies, the percentage of free stalls should not be less than 15% (Vickrey, 1954). For this problem, the entire process of determining the OD matrix, modal choice and assignment, can be solved with an algorithmic approach; however, the determination of the optimal rate of parking is resolved by an heuristic process, which will be explained below. ...
The purpose of this study has been the develop of a model for designing an efficient parking pricing policy. The aim is an intelligent control and management system of parking pricing integrated with a redefinition of the circulation scheme for a limited traffic zone in the Central Business District (CBD) of Palermo.
The effectiveness of congestion charges and parking prices as monetary disincentives to reduce car traffic and alleviate congestion in highly demanded urban areas is investigated, focusing on Jerusalem's diverse and congested city center. A tailored MATSim agent-based simulation model was used to examine various payment scenarios and assess the congestion level impacts of entry charges to the city center. Entry charges directly influence the number of vehicles entering the area; parking prices mostly the dwell time. Implementing a moderate daily payment of €10, either as a combined charge or separately, resulted in a substantial 25% reduction in congestion and potentially a reduction of 7.5% to 30% of emissions in the city center. Parking pricing advantages are augmented as the charged area expands. Strategic implementation of these monetary tools can effectively allow cities to manage traffic congestion, reduce pollution, and encourage a shift to sustainable transportation modes.
The parking cruising problem can be attributed to the unbalanced spatial parking space occupancy in the parking lot with multiple trip purposes and high traffic volumes, and it has already become an obstacle to improving travel efficiency. This study aims to investigate the reasons for the unbalanced occupancy of parking spaces and develop strategies to achieve spatial equilibrium by reducing parking cruising time. A field survey is first conducted to analyze the factors influencing parking space choice behavior, such as searching distances, walking distances, parking price, and parkers’ attributes. Based on the survey, a mixed logit model is calibrated to reveal parking space choice patterns of different parkers. Afterwards, the parking lot is divided into three zones based on searching distances and walking distances, using the K-means algorithm. According to the results, a simulation-based optimization model is then established, for minimizing the variance of average occupancy. An optimal pricing strategy is obtained at last. A case study in Nanjing, China, is conducted to verify the feasibility and rationality of the proposed method. The difference between weekdays and weekends is explored. The results show that, with the optimal strategies, the standard deviation of average occupancy in each zone decreases by 39.52% during weekends and 42.29% during weekdays. Finally, political implications and recommendations on the layout design of facilities and the adoption of differential parking pricing strategies are provided.
This article analyses the impact that different parking management policies may have on public roads. Policies were simulated using a new parking model based on two sub models: choice of parking place and search for parking place. The model considers curb traffic and was implemented into a traditional microsimulation traffic software. The parameters for the sub models were estimated from data collected in the city centre of Santander (Spain) and from a stated preferences survey asked to users of parking spaces. The model for testing policies was run on Aimsun simulation software creating a personalised API programmed using Python 3.7. The proposed model was able to dynamically simulate various policies based on charging for on-street parking spaces with fare updates at short time intervals of between 5 and 15 min. A sensitivity analysis was performed on different fare scenarios and considering different levels of information available to the users. As a result, this work demonstrates some benefits of dynamic fares such as reducing searching time, curb induced traffic and emissions as well as a new modal redistribution of parking choice between off-street and on-street supply. On the contrary, dynamic fares implied that users needed to spend a bit more time from their parking location to their destinations.
Existing surveys look at parking solutions from the perspective of sensors, communication protocols, and the hardware-software interface. While this is a worthwhile approach, it suffers from three obvious shortcomings, namely that present-day sensors are likely to become obsolete in a few years, communication protocols get discontinued, and present-day software will almost certainly not run on tomorrow's platforms. Consequently, these approaches are not promising for the Smart Cities of the near future. Unlike previous surveys, we look at parking in Smart Cities through the lens of market-based allocation of goods and services. In competitive markets prices act as signals used to allocate goods to those who value them most. In the case of parking spots, some drivers are willing to pay higher prices for the use of those parking spots that offer them the highest utility. What makes our survey unique is that we are looking at the recent literature with an eye for market-oriented solutions including pricing as an instrument for shaping traffic and for incentivizing socially-desirable driver behavior. We believe that one of the important contributions of any survey paper, over and above being a compendium of known art, is to suggest new lines of research. With this in mind, we have peppered the manuscript with slightly unorthodox perspectives. These perspectives are intended to be thought-provoking and to open new avenues for possible investigations.
On-street parking policies have a huge impact on the social welfare of citizens. Accurate parking occupancy data across time and space is required to properly set such policies. Different imputation and forecasting models are required to obtain this data in cities that use probe vehicle measurements, such as Amsterdam. In this paper, the usage of traffic data as an explanatory variable is assessed as a potential improvement to existing parking occupancy prediction models. Traffic counts were obtained from 164 traffic cameras throughout the city. Existing models for predicting parking occupancy were reproduced in experiments with and without traffic data, and their performance was compared. Results indicated that (i) traffic data are indeed a useful predictor and improves performance of existing models; (ii) performance does not improve linearly with an increase in the number of counting points; and (iii) placement of the cameras does not have a significant impact on performance.
Practitioners need to know the level of cruising for parking when designing parking poli- cies. Existing methodologies, such as counting, experiments, and survey, are either too ex- pensive or infeasible to be undertaken on a large scale. Inci et al. (2017) introduce an instrumental-variables-based econometric methodology using administrative data to esti- mate the average level of cruising when parking is close to full occupancy. This paper introduces a novel methodology to estimate the marginal external cruising time (and thus cost) across time and space. Our methodology is easier to implement, requires even less data, estimates the whole distribution rather than the average, and does not require park- ing to be near full occupancy. It also allows for welfare evaluations of parking fees and supply. To illustrate all these, we apply our methodology to Melbourne, which generates rich policy insights. We also apply it to the same dataset that Inci et al. (2017) use for Istanbul and find consistent results, rendering confidence to both methodologies.
This paper considers an auction-based parking reservation problem where a parking management platform is the auctioneer and the drivers are bidders. The platform is in charge of multiple homogeneous parking spaces. A winner may leave earlier or occupy the parking space longer than the time he has reserved. The phenomena are known as (ex post) demand disturbances, which can occur only after the last auction terminates. The platform may penalize or compensate a driver who causes demand disturbance. Besides, investigation is conducted into three types of driver behaviors, namely, gain/loss neutrality, loss aversion, and gain seeking, and the reference effects are examined. An effective multi-stage Vickrey–Clarke–Groves (MS-VCG) auction mechanism is raised. Expect for the disturbance makers, the MS-VCG auction is capable to achieve allocative efficiency, incentive compatibility, and individual rationality. As shown by computational results, in the absence of reference effect, both penalty and compensation rise with the number of bidders. If drivers are gain/loss neutral, the average utility of winners reaches the highest, while the penalty and compensation reach the lowest, as compared to loss-averse and gain-seeking drivers. The total VCG payment received by the auctioneer increases with the reference price. Finally, based on our proposed model, the platform has the ability to deal with the demand disturbances by holding a certain number of parking spaces that are not auctioned for reservation.
Paid curbside parking can be advantageously modeled as a network of interdependent queues. To this end, we introduce methods for analyzing a special class of networks of finite capacity queues where drivers arrive from an exogenous source, join the queue if there is an available parking space, or continue to search at an adjacent queue for an available space. Furthermore, we apply this model to estimate the proportion of drivers cruising in the neighborhood of Belltown, Seattle, WA, USA. Using occupancy approximated by parking transaction data, we estimate the percentage of drivers cruising for curbside parking by comparing the rate of drivers unable to find parking to bulk through-traffic measurement data. We find percentages of up to 50% for a Belltown's 1st Ave. depending on the time, day, and direction of travel. We then calculate a per vehicle travel-time cost to social welfare incurred by this proportion: upward of a 10% increase in travel time to all drivers along 1st Ave. Last, we introduce a simulation tool and test assumptions made when estimating interesting performance metrics like the probability of a block-face being full. Our results suggest that while assuming exponential service time distributions is not justified, mean rate solutions under a Markovian relaxation of the problem is comparable to service times representative of parking transaction data in simulation.
This is a preview of my upcoming book with Elsevier, including the Table of Contents, a Foreword written by Professor Will Recker, and a Bibliography. The monograph serves as a reference book for researchers and practitioners who are increasingly working across disciplines to solve urban transportation and mobility problems in the context of smart cities.
Several recent papers have used the approximation that the number of curbside parking spaces searched before finding a vacant space equals the reciprocal of the expected curbside vacancy rate. The implied expected cruising-for-parking times are significantly lower than those that have been obtained through observation and simulation. Through computer simulation of cars cruising for parking around a circle in stochastic steady state, this paper shows that the approximation leads to underestimation of expected cruising-for-parking time and, at high occupancy rates, considerable underestimation. The paper also identifies several “effects” that contribute to the approximation being an increasingly poor one as the occupancy rate increases.
Dynamic parking pricing varies the cost of parking over location and time to achieve target occupancy rates. Such pricing seeks more efficient parking space use, reduced cruising for parking, and improved satisfaction with the parking experience. Evaluation practice in this field is developing as communities implement new programs. With four case studies, the programs and their evaluations are explained, and a comprehensive evaluation framework is developed. The framework differentiates between possible theory failure and program failure and distinguishes between direct, intermediate, goal, and program support outcomes. The review reveals that some metrics, such as congestion reduction, are not supported by theory or evaluation results. Other logical metrics, such as the efficiency of parking use as indicated by a ratio of district activity per parking space, are missing.
In dense urban areas, surface parking often poses an opportunity cost, and reuse of the land for urban development with parking relocated to a multi-story structure may be an attractive option. This paper analyzes the cost of replacing surface parking with a parking structure and finds that it may be equally cost effective to pursue travel demand management strategies. The paper analyzes what it costs to build a parking space in a multi-story structure (garage) using US average data as well as data from the case of a typical large US employer, the University of California, Berkeley. The Berkeley case illustrates how replacement of surface parking with structures can substantially escalate costs and necessitate price increases for everyone, unless costs can be offset through more efficient utilization rates (e.g., renting out employee parking for evening and weekend use) or the parking system is credited for the land value of former surface parking (not likely in the situation considered here). A transportation demand management (TDM) program offering incentives for other modes of commuting can reduce the need for new parking, and its annual costs are likely to be lower than the amounts needed to cover new parking construction. Parkers could be better off paying for TDM programs to reduce parking demand rather than paying to build new parking structures. The findings are case specific but are likely to resonate with many employers and institutions that provide parking in high-cost urban areas.
This paper investigates the drivers’ microscopic curbside parking behaviors under random distribution of vacant parking spaces. For each trip, the driver has a preferred arrival time at the destination and may incur schedule delay cost due to the uncertainty of searching process. The expected trip costs include the in-transit travel cost, the cruising cost, the walking cost, the schedule delay cost and the parking fee. To minimize the expected trip cost, there are two decisions require the driver to make, namely how long before the specified arrival time to initiate the trip and how far away ahead of the destination to search for a vacant parking position. Two possible searching state of the driver are illustrated. The “fastest parker” refers to the possible state of the driver parking successfully when just starts cruising with zero searching distance, and the “luckiest parker” refers to the possible state that driver parks exactly on her/his destination and incurs zero walking distance. Based on the schedule delay states of being the fastest parker and the luckiest parker, three searching strategies are distinguished. The “Early-park-early-arrival” strategy refers to the driver has the expectation that arrives at the destination early when being the fastest parker; the “Early-park-late-arrival” strategy refers to the driver has the expectation that arrives at the destination late when being the fastest parker and arrives early when being the luckiest parker; the “Never-early” strategy refers to the driver has the expectation of late arrival whatever being the fastest or the luckiest parker. The analytical proofs reach some interesting findings: the “Never-early” strategy can never be optimal; if the unit time cost of early arrival is larger than that of late arrival, the optimal parking strategy is “Early-park-late-arrival”; if the “Early-park-early-arrival” strategy is optimal, the driver's possibility of parking before the destination is larger than 50%. Several numerical results are illustrated to verify the analytical propositions and show that the “Early-park-early-arrival” strategy is preferred to the “Early-park-late-arrival” strategy under higher parking charge，higher unit time cost of walking.
The field of parking is going through a period of extreme innovation. Cities in the United States are now exploring new technology to improve on-street parking. One such innovation is dynamic pricing based on sensors and smart meters. This paper presents the results of two surveys and an ethnographic study in the context of LA Express ParkTM to understand users’ behaviors, knowledge and perceptions around parking. Survey results demonstrated that a high number of users misunderstood one of three tested stickers that convey time of day pricing. Furthermore, after discovering the availability of cheaper parking spots nearby, people expressed willingness to change their future behavior to park in those places. Ethnographic field studies found that it is common for many parkers to use handicapped placards for over eight hours in one parking session. A percentage of these parkers may be using placards illegally. We propose that increasing some parking restrictions during the day may curb placard use by making it more difficult to park for long periods.
Referring to the classic circular city model, a curbside parking model based on the Markov chain theory is formulated. According to its Markov properties, the cruising competition queue is depicted through the viewpoints of the system and drivers, respectively. Consequently, the probability density function of the searching distance is derived, which proves that the traditional binomial distribution is limited in describing the competition behaviors between drivers. Then, a simulation algorithm is established to verify the theoretical results of the Markov model and find that besides the competition behavior, the continuouslyparking phenomenon is another major reason for difficult curbside parking. The finding extends our knowledge of curbside parking and can be helpful in designing the curbside parking policies.
This paper reviews the literature on parking with an emphasis on economic issues. Parking is not just one of the most important intermediate goods in the economy; it is also a vast use of land. Many theoretical and empirical papers analyze the quantity and pricing of parking by concentrating on particular aspects of the issue. The aspects covered in this review are cruising for parking, spatial competition, (minimum and maximum) parking requirements, parking pricing and road pricing in the bottleneck model, and temporal-spatial pricing. Various forms of parking, including residential parking, shopping mall parking, and employer-provided parking, are also reviewed before identifying understudied topics that should be on the research agenda.
On-street parking, just as any publicly owned utility, is used inefficiently if access is free or priced very far from market rates. This paper introduces a novel demand management solution: using data from dedicated occupancy sensors an iteration scheme updates parking rates to better match demand. The new rates encourage parkers to avoid peak hours and peak locations and reduce congestion and underuse. The solution is deliberately simple so that it is easy to understand, easily seen to be fair and leads to parking policies that are easy to remember and act upon. We study the convergence properties of the iteration scheme and prove that it converges to a reasonable distribution for a very large class of models. The algorithm is in use to change parking rates in over 6000 spaces in downtown Los Angeles since June 2012 as part of the LA Express Park project. Initial results are encouraging with a reduction of congestion and underuse, while in more locations rates were decreased than increased.
Problem, research strategy, and findings: Underpriced and overcrowded curb parking creates problems for everyone except a few lucky drivers who find a cheap space; all the other drivers who cruise to find an open space waste time and fuel, congest traffic, and pollute the air. Overpriced and underoccupied parking also creates problems; when curb spaces remain empty, merchants lose potential customers, workers lose jobs, and cities lose tax revenue. To address these problems, San Francisco has established SFpark, a program that adjusts prices to achieve availability of one or two open spaces per block. To measure how prices affected on-street occupancy, we calculated the price elasticity of demand revealed by over 5,000 price and occupancy changes during the program's first year. Price elasticity has an average value of -0.4, but varies greatly by time of day, location, and several other factors. The average meter price fell 1% during the first year, so SFpark adjusted prices without increasing them overall. This study is the first to use measured occupancy to estimate the elasticity of demand for on-street parking. It also offers the first evaluation of pricing that varies by time of day and location to manage curb parking. Takeaway for practice: San Francisco can improve its program by making drivers more aware of the variable prices, reducing the disabled placard abuse, and introducing seasonal price adjustments. Other cities can incorporate performance parking as a form of congestion pricing.
Donald Shoup, following Vickrey, has long advocated cashing out free and underpriced parking. How should this be implemented for curbside parking in practice, considering the stochasticity of curbside parking vacancies? Shoup has proposed adjusting meter rates such that, for each block and time period, a target (average) curbside parking occupancy rate of 85% is achieved. This paper develops a simple structural model of stochastic steady-state curbside parking in an isotropic space, solving for the surplus-maximizing occupancy rate and the corresponding meter rate. By increasing curbside occupancy, a curbside parker imposes a curbside parking externality. The optimal meter rate internalizes this externality. The central comparative static result is that, ceteris paribus, the optimal occupancy and meter rates are higher, the higher is demand relative to curbside parking capacity. This suggests that, in practice, the occupancy rate should be higher in more trafficked locations and at busier times of the day.
Shortages of street parking can cause cruising, a major source of urban congestion. We used SFpark, a federally funded experiment in market-priced parking in San Francisco, to study how changes in meter prices influenced on-street parking availability. We supervised observations of more than 13,400 vehicles parked on a subset of dynamically priced and control blocks at three points in time during 2011 and 2012. Repeated-observation, change-on-change regressions show that when prices rose, the block-level occupancy of parking fell, suggesting that SFpark worked as intended. But blocks where prices rose showed no discernible improvement in parking availability—the share of time at least one space on a block face was vacant. Price increases also had no association with other factors we would expect to be influenced by price, including parking duration, vehicle turnover, and carpooling. These relationships were robust to controlling for the parking zone, the previous price level, nearby employment, and the weather. A price system designed to improve average occupancy may not improve parking availability, and thus may not reduce cruising. Cities trying to reduce cruising may need to adjust prices based on minimum vacancy, and price changes may need to be larger in many cases.
We estimate welfare losses of policies that provide on-street parking permits to residents almost free of charge in Dutch shopping districts that are predominantly downtown. Our empirical results indicate that parking supply is far from perfectly price elastic, implying that there are substantial welfare losses related to underpriced parking permits. Our results suggest that the provision of residential parking permits in downtown shopping districts induces a yearly welfare loss of about €275 per permit, which is about 15 percent of the supply cost of a parking place.
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