Empirical evidence on cruising for parking

The literature on car cruising is dominated by theory. We examine cruising for parking using a nation-wide random sample of car trips. We exclude employer-provided and residential parking. We focus on the Netherlands, where levels of on-street and off-street parking prices are locally the same. We demonstrate then that due to this price setting the average cruising time in the Netherlands is only 36 s per car trip. Furthermore, we show that cruising is not random. It is more common in (large) cities that receive more car trips, particularly for shopping and leisure activities. Cruising time increases with travel duration as well as with parking duration. Cruising has a distinctive pattern over the day with a peak in the morning, so the order of arrival is essential to parking. Because cruising has a spatial and time component, policies may be considered that reduce cruising time through flexible pricing of parking or improved information about vacant parking spaces.     

Analysis of parking cruising behaviour and parking location choice

ABSTRACT

This paper explores car drivers’ cruising behaviour and location choice for curb parking in areas with insufficient parking space based on a survey of car drivers in Beijing, China. Preliminary analysis of the data show that car drivers’ cruising behaviour is closely related to their parking duration and parking location. A multinomial probit (MNP) model is used to analyse cruising behaviour and the results show that the closer to the destination car drivers are, the more likely they choose to park on the curb. The adjacent locations are the basis of car drivers’ sequential parking decisions at different locations. The research results provide a better understanding of cruising behaviour for parking and recommendations for reducing cruising for parking. The provision of parking information can help regulate the parking demand distribution.     

Parking Benefit Districts – The transferability of a measure to reduce car dependency to a European context

Parking Benefit Districts (PBDs) are a parking measure where revenues from on-street parking charges are returned to the area where they are charged, and stakeholders in the area participate in prioritizing how the revenues are to be spent. The purpose of this article is to analyse whether and how a PBD programme can be transferred to a European context, and whether it can contribute to reduced car dependency. The first part of the article provides an overview of some salient features of PBD programmes in the USA through a literature survey. This is followed by results from interviews and from a focus group with civil servants and a deputy mayor in Stockholm. The results are used to analyse the conditions for implementing a PBD programme in Stockholm, as well as for analysing how such a programme can be designed to reduce car dependency. A main conclusion is that there are no legal barriers that render a PBD programme impossible in Stockholm, even though there are some legal restrictions. We also conclude that a PBD programme might contribute to reduced car dependency in two different ways, either by increasing acceptance for parking charges or by improving the alternatives to private cars. There seem to be several aspects in a PBD programme that can contribute to increased acceptance for parking charges. However, there is no tradition of working with these principles in Sweden and the programme’s redistributional effects need to be taken into account when designing the programme.     

Optimisation of parking guidance and information systems display configurations

Operators of parking guidance and information (PGI) systems often have difficulty in determining the best car park availability information to present to drivers in periods of high demand. This paper describes a behavioural model of parking choice incorporating drivers perceptions of waiting times at car parks based on PGI signs. This model was used to predict the influence of PGI signs on the overall performance of the traffic system.Relationships were developed for estimating the arrival rates at car parks based on trip patterns, driver characteristics, car park attributes as well as the car park availability information displayed on PGI signs. Drivers' perceptions of waiting times at car parks were assumed to be influenced by the PGI signs for observers of the signs and actual car park utilisation levels for non-observers. The model assumes that the choice of car park does not change after entering the city centre, even if conditions observed are different from those initially perceived.A mathematical programme was formulated to determine the optimal display PGI sign configuration to minimise queue lengths and vehicle kilometres of travel (VKT). The model was limited to off-street parking choices and illegal parking was not incorporated. A simple genetic algorithm was used to identify solutions that significantly reduced queue lengths and VKT compared with existing practices.These procedures were applied to an existing PGI system operating in Tama New Town near Tokyo. Significant reductions in queue lengths and VKT were predicted using the optimisation model. This would reduce traffic congestion and lead to various environmental benefits.     

Expansion of a Controlled Parking Zone (CPZ) and its Influence on Modal Split: The Case of Edinburgh

Abstract

This article considers the inter-relationship between on-street parking and choice of mode for journeys to work in the Scottish city of Edinburgh. This city is typical of many in that its centre has significant on-street parking controls but, beyond a radius of 1 to 1 1/2 miles (1.5 to 2.5?km) from the centre, there are no controls and commuter parking on-street is commonplace. The article reviews the relevant literature, and then considers the results of a survey undertaken of Edinburgh city centre employees in order to ascertain their parking habits and likely response to the extension of existing on-street parking controls. The article concludes that the results are transferable to other cities but that the scale of the impacts in each will be related to site specific factors, particularly the demand for residential parking space on-street in areas close to the city centre.     

Trails,lanes, or traffic: Valuing bicycle facilities with an adaptive stated preference survey

This study evaluates individual preferences for five different cycling environments by trading off a better facility with a higher travel time against a less attractive facility at a lower travel time. The tradeoff of travel time to amenities of a particular facility informs our understanding of the value attached to different attributes such as bike-lanes, off-road trails, or side-street parking. The facilities considered here are off-road facilities, in-traffic facilities with bike-lane and no on-street parking, in-traffic facilities with a bike-lane and on-street parking, in-traffic facilities with no bike-lane and no on-street parking and in-traffic facilities with no bike-lane but with parking on the side. We find that respondents are willing to travel up to twenty minutes more to switch from an unmarked on-road facility with side parking to an off-road bicycle trail, with smaller changes associated with less dramatic improvements.     

Electric vehicles and residential parking in an urban environment: Results from a stated preference experiment

This paper presents the results of a preference survey of 1545 respondents’ willingness to purchase electric vehicles (EVs) in Philadelphia. We pay particular attention to respondents’ willingness to pay for convenient charging systems and parking spaces. If the value of dedicated parking substantially outweighs the value of convenient charging systems, residential-based on-street charging systems are unlikely to ever be politically palatable. As expected, respondents are generally willing to pay for longer range, shorter charging times, lower operating costs, and shorter parking search times. For a typical respondent, a $100 per month parking charge decreases the odds of purchasing an EV by around 65%. Across mixed logit and latent class models, we find substantial variation in the willingness to pay for EV range, charge time, and ease of parking. Of note, we find two primary classes of respondents with substantially different EV preferences. The first class tends to live in multifamily housing units in central parts of the city and puts a high value on parking search time and the availability of on-street charging stations. The second class, whose members are likelier to be married, wealthy, conservative, and residing in single-family homes in more distant neighborhoods, are willing to pay more for EV range and charge time, but less for parking than the first group. They are also much likelier to consider purchasing EVs at all. We recommend that future research into EV adoption incorporate neighborhood-level features, like parking availability and average trip distances, which vary by neighborhood and almost certainly influence EV adoption.     

Modeling and optimization of multimodal urban networks with limited parking and dynamic pricing

Cruising-for-parking constraints mobility in urban networks. Car-users may have to cruise for on-street parking before reaching their destinations. The accessibility and the cost of parking significantly influence people's travel behavior (such as mode choice, or parking facility choice between on-street and garage). The cruising flow causes delays eventually to everyone, even users with destinations outside limited parking areas. It is therefore important to understand the impact of parking limitation on mobility, and to identify efficient parking policies for travel cost reduction. Most existing studies on parking fall short in reproducing the dynamic spatiotemporal features of traffic congestion in general, lack the treatment of dynamics of the cruising-for-parking phenomenon, or require detailed input data that are typically costly and difficult to collect. In this paper, we propose an aggregated and dynamic approach for modeling multimodal traffic with the treatment on parking, and utilize the approach to design dynamic parking pricing strategies. The proposed approach is based on the Macroscopic Fundamental Diagram (MFD), which can capture congestion dynamics at network-level for single-mode and bi-modal (car and bus) systems. A parsimonious parking model is integrated into the MFD-based multimodal modeling framework, where the dynamics of vehicular and passenger flows are considered with a change in the aggregated behavior (e.g. mode choice and parking facility choice) caused by cruising and congestion. Pricing strategies are developed with the objective of reducing congestion, as well as lowering the total travel cost of all users. A case study is carried out for a bi-modal city network with a congested downtown region. An elegant feedback dynamic parking pricing strategy can effectively reduce travel delay of cruising and the generic congestion. Remarkably, such strategy, which is applicable in real-time management with limited available data, is fairly as efficient as a dynamic pricing scheme obtained from system optimum conditions and a global optimization with full information about the future states of the system. Stackelberg equilibrium is also investigated in a competitive behavior between different parking facility operators. Policy indications on on-street storage capacity management and pricing are provided.     

Turning meter transactions data into occupancy and payment behavioral information for on-street parking

Over 95% of on-street paid parking stalls are managed by parking meters or kiosks. By analyzing meter transactions data, this paper provides a methodology to estimate on-street time-varying parking occupancy and understand payment behavior in an effective and inexpensive way. We propose a probabilistic payment model to simulate individual payment and parking behavior for each parker. Aggregating the payment/parking of all transactions leads to time-varying occupancy estimation. Two data sets are used to evaluate the methodology, parking spaces near Carnegie Mellon University (CMU) campus, and near the Civic Center in San Francisco. The proposed model generally provides reliable estimations of occupancies at a low error rate and substantially outperforms other naive models in the literature. From the results of the experiments we find that people generally tend to slightly underpay in CMU area, whereas for Civic Center area, payment behavior varies by time of day and day of week. For Fridays, people generally tend to overpay and stay longer in the mornings, compared to underpaying and parking for shorter durations in the late afternoons. Parkers’ payment behavior, in general, is more variable and noisier around Civic Center than around CMU. Moreover, we explore the effective granularity, defined as the highest spatial resolution for this model to perform reliably. For CMU areas, the effective granularity is around 10–20 spaces for each block of streets, while it is 150–200 spaces for the Civic Center area due to more random parking behavior.     

Is the curb 80% full or 20% empty? Assessing the impacts of San Francisco’s parking pricing experiment

The city of San Francisco is undertaking a large-scale controlled parking pricing experiment. San Francisco has adopted a performance goal of 60–80% occupancy for its metered parking. The goal represents an heuristic performance measure intended to reduce double parking and cruising for parking, and improve the driver experience; it follows a wave of academic and policy literature that calls for adjusting on-street parking prices to achieve similar occupancy targets. In this paper, we evaluate the relationship between occupancy rules and metrics of direct policy interest, such as the probability of finding a parking space and the amount of cruising. We show how cruising and arrival rates can be simulated or estimated from hourly occupancy data. Further, we evaluate the impacts of the first two years of the San Francisco program, and conclude that rate changes have helped achieve the City’s occupancy goal and reduced cruising by 50%.     

Understanding parking decisions with a Bayesian network

In this paper, a Bayesian network is developed to investigate three intertwining parking decisions, namely parking period, parking location, and parking duration, and the impacts of a number of parking-related factors on these decisions. With parking information from Beijing, China in 2005, the structure and parameter of a Bayesian network were learnt by employing the K2 algorithm and Bayesian parameter estimation method respectively. The results show that the decision on how long to park follows that on where to park, and both of them are affected by the decision of when to park. This suggests that parking policies aimed at intervening in one specific parking decision may have an indirect influence on other parking decisions, which embraces an integrated view in the development of parking policies. The findings facilitate the development of measures for regulating parking behavior by identifying important contributing factors.     

Parking management for promoting sustainable transport in urban neighbourhoods. A review of existing policies and challenges from a German perspective

ABSTRACT

The organisation of parking is a key challenge to more sustainable mobility in urban areas, as its pricing and availability affect the rates of private car ownership and use. However, changing parking policies is a challenging issue for local politicians and planners because residents frequently oppose changes or restrictions to conditions they have taken for granted such as on-street parking in a public space. The aim of this paper is firstly to assess how the parking policy of an urban neighbourhood can be structured to contribute to more sustainable mobility and to increase liveability in the neighbourhood. The second aim is to apply the policies reviewed to an example neighbourhood. For this purpose, we systematically reviewed academic literature and identified five types of relevant parking policies: (i) maximum parking requirements, (ii) physical detachment of residence and parking space, (iii) residential parking permits and the limitation of available parking space, (iv) performance-based pricing and (v) parking as a demand management strategy. We discovered that most research focuses on econometric models about parking and that studies rarely address the effects of parking on the quality of life in neighbourhoods. Therefore, we need further research regarding the relationship of parking and liveability. We conclude that for the implementation of such parking policies in an example neighbourhood, the municipality needs to develop a mobility vision for its city. It has to understand parking as a tool for transportation demand management to increase the acceptance of parking policy concepts and to avoid spillover problems. Finally, in the German case, as in most other countries, states and municipalities need to redesign their legal frameworks to be able to manage parking supply better and to react to changes related to digital developments and parking. The findings have implications for other European neighbourhoods regarding the transfer from research to local circumstances and applications for the whole city.     

Parking demand and responsiveness to supply,pricing and location in the Sydney central business district

This paper investigates the role of parking pricing and supply by time of day in whether to drive and park in the central business district (CBD). A stated preference survey of car drivers and public transport users was undertaken at a number of parking locations, public transit interchanges, and shopping centres in Sydney CBD during 1998. In the context of a current trip to the CBD, respondents were asked to consider six alternatives, including three parking locations in the CBD, park outside of the CBD with public transport connection to the CBD, switch to public transport, or forego that trip to the CBD. The three parking locations were defined by hours of operation, a tariff schedule, and access time to the final destination from the parking station. Data from the survey were then used to estimate a nested logit model of mode and parking choices, which was then used to simulate the impacts of supply pricing scenarios on CBD parking share. The change in CBD parking share attributable to supply by time of day is less than 3%, compared to 97% attributable to parking prices.     

Decision support for simulating the car park activity in an urban area

Complexity of car park activity is reproduced from a concurrent execution of behaviour of various drivers. This paper presents a step in the development of a multimodal traffic simulator based on multi‐agent paradigm and designed as a decision aid tool as well as a video game. The user‐player has the opportunity to test different scenarios. We propose an approach for designing the decision‐making rules and the learning mechanism for a car driver agent. For that, a panel of methods such as stated preference modelling, Design Of Experiments and data fusion is used. Initial behavioural models, based on similar preferences, are developed for specified categories. Each agent will adapt its behaviour after executing its learning process. Our approach can be used in order to optimize needs of road network users and those of people in charge of traffic regulation. A demonstrator has been developed to test parking policies in an urban area as well as changes of car park characteristics.     

上海市城市机动车停车场(库)环保设计优化研究

对上海市7家建筑、环评设计院的15位工程师开展问卷调研,运用Cronbach’sα系数量化了问卷的信度,并根据调研结果,随机实测4座停车场16辆车的洗车污水,进行对标分析与Kruskal-Walli test,最终对城市机动车停车场(库)提出了设计优化建议。结果表明:问卷的Cronbach’sα系数为0.639,信度较好。未经过处理的停车场洗车污水样本存在超标现象,COD的超标区间为[4.23%,108.32%],TP的超标率为10.00%,BOD₅的超标区间为[22.40%,139.40%]。COD、BOD₅、SS的检测结果受车型大小的影响,呈正相关关系。建议从洗车设施、绿荫绿化等方面优化城市停车场(库)的环保设计。     

The time dimension of parking economics

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.     

The trouble with minimum parking requirements

Urban planners typically set the minimum parking requirements for every land use to satisfy the peak demand for free parking. As a result, parking is free for 99% of automobile trips in the United States. Minimum parking requirements increase the supply and reduce the price – but not the cost – of parking. They bundle the cost of parking spaces into the cost of development, and thereby increase the prices of all the goods and services sold at the sites that offer free parking. Cars have many external costs, but the external cost of parking in cities may be greater than all the other external costs combined. To prevent spillover, cities could price on-street parking rather than require off-street parking. Compared with minimum parking requirements, market prices can allocate parking spaces fairly and efficiently.     

Determinants of bicycle commuting in the Washington,DC region: The role of bicycle parking,cyclist showers,and free car parking at work

This article examines the role of bicycle parking, cyclist showers, free car parking and transit benefits as determinants of cycling to work. The analysis is based on commute data of workers in the Washington, DC area. Results of rare events logistic regressions indicate that bicycle parking and cyclist showers are related to higher levels of bicycle commuting—even when controlling for other explanatory variables. The odds for cycling to work are greater for employees with access to both cyclist showers and bike parking at work compared to those with just bike parking, but no showers at work. Free car parking at work is associated with 70% smaller odds for bike commuting. Employer provided transit commuter benefits appear to be unrelated to bike commuting. Regression coefficients for control variables have expected signs, but not all are statistically significant.     

Maximum car ownership under constraints of road capacity and parking space

This paper presents a model for determining the maximum number of cars by zones in view of the capacity of the road network and the number of parking spaces available. In other words, the proposed model is to examine whether existing road network and parking supply is capable of accommodating future zonal car ownership growth (or the reserve capacity in each zone); i.e. the potential maximum zonal car ownership growth that generates the road traffic within the network capacity and parking space constraints. In the proposed model, the vehicular trip production and attraction are dependent on the car ownership, available parking spaces and the accessibility measures by traffic zones. The model is formulated as a bi-level programming problem. The lower-level problem is an equilibrium trip distribution/assignment problem, while the upper-level problem is to maximize the sum of zonal car ownership by considering travellers’ route and destination choice behaviour and satisfying the network capacity and parking space constraints. A sensitivity analysis based heuristic algorithm is developed to solve the proposed bi-level car ownership problem and is illustrated with a numerical example.     

Parking preferences among tourists in Newport,Rhode Island

Like many tourist destinations, Newport, Rhode Island relies upon high season tourist volumes for its economic health. Most visitors arrive by car, concentrated during certain hours on summer weekends, severely congesting the town’s major arteries and forcing many visitors to spend considerable time in their car. A transportation planning strategy which reduced congestion would enhance the quality of the visiting experience, increase the time visitors are able to spend in shops and at attractions, and draw additional visitors. However, identifying effective solutions requires understanding factors that affect tourists’ transit choices. We develop a conceptual model of Newport visitors’ parking and transit choices, expanding traditional transit choice models to include features such as scenery we expect to influence tourists. Using a stated preference survey of visitors, we find scenery, transit mode options and congestion are the major drivers of tourists’ parking choices. We also develop welfare estimates to enable analysis of proposed transportation plans.