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.     

Modelling parking choices considering user heterogeneity

We examine car driver’s behaviour when choosing a parking place; the alternatives available are free on-street parking, paid on-street parking and parking in an underground multi-storey car park. A mixed logit model, allowing for correlation between random taste parameters and estimated using stated choice data, is used to infer values of time, both when looking for a parking space and for accessing the final destination. Apart from the cost of parking, we found that vehicle age was a key variable when choosing where to park in Spain. We also found that the perception of the parking charge was fairly heterogeneous, depending both on the drivers’ income levels and whether or not they were local residents. Our results can be generalised for personalised policy making related with parking demand management.     

Evaluating parking reservation policy in urban areas: An environmental perspective

This paper investigates a parking reservation mechanism to reduce car cruising to find parking. To consider the benefits for drivers and parking facility providers, we charge drivers for making reservations in addition to parking fees, by introducing a reservation pricing model that makes reservation prices equivalent to the value of saved search time. By modeling the number of vacant spaces as a stochastic variable, and applying binomial pricing methods, parking reservation prices are obtained. Numerical examples based on the data for two parking facilities in Taiwan are given.     

Effect of parking information on travelers' knowledge and behavior

In many urban centers the demand for parking increases sharply before Christmas mainly due to shopping activity — causing parking congestion. One way to ameliorate such congestion is by disseminating parking information. Informed drivers may divert to relatively under-utilized parking facilities relieving the pressure on congested facilities. The City of Nottingham in England tested a real-time parking information system designed to alleviate congestion in the City Center parking facilities. Real-time information was disseminated through the radio, while historical information regarding parking locations was disseminated through newspaper advertisements and leaflets. The objective of this study is to assess impacts of the parking information system on travelers' knowledge and decisions.Survey research was used to understand traveler response. Respondents' levels of knowledge regarding car parks were analyzed by developing Poisson regression models. Drivers were more likely to have greater knowledge of city center car parks if they used several information sources (radio broadcasts, newspaper advertisements or leaflets and word-of-mouth), were active seekers of parking information, and searched for parking rather than going directly to a parking facility. In addition, the study of behavior showed that drivers were more inclined to use the relatively under-utilized Park-and-Ride facilities instead of the city center car parks if they received parking information from Newspaper advertisements/leaflets. Overall, the parking information service in Nottingham was effective; it seems reasonable to establish such information dissemination and monitoring systems at parking facilities in other urban areas. Furthermore, to support informed travel and activity participation decisions, parking information should be integrated with traffic and transit information.     

Drivers’ parking location choice under uncertain parking availability and search times: A stated preference experiment

To assess parking pricing policies and parking information and reservation systems, it is essential to understand how drivers choose their parking location. A key aspect is how drivers’ behave towards uncertainties towards associated search times and finding a vacant parking spot. This study presents the results from a stated preference experiment on the choice behaviour of drivers, in light of these uncertainties. The attribute set was selected based on a literature review, and appended with the probabilities of finding a vacant parking spot upon arrival and after 8 min (and initially also after 4 min, but later dropped to reduce the survey complexity). Efficient Designs were used to create the survey design, where two rounds of pilot studies were conducted to estimate prior coefficients. Data was successfully collected from 397 respondents. Various random utility maximisation (RUM) choice models were estimated, including multinomial logit, nested logit, and mixed logit, as well as models accounting for panel effects. These model analyses show how drivers appear to accept spending time on searching for a vacant parking spot, where parking availability after 8 min ranks second most important factor in determining drivers’ parking decisions, whilst parking availability upon arrival ranks fourth. Furthermore, the inclusion of heterogeneity in preferences and inter-driver differences is found to increase the predictive power of the parking location choice model. The study concludes with an outlook of how these insights into drivers’ parking behaviour can be incorporated into traffic assignment models and used to support parking systems.     

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.     

Bicycle parking: a systematic review of scientific literature on parking behaviour,parking preferences,and their influence on cycling and travel behaviour

ABSTRACT

Cycling is experiencing a revival in many cities. Research has focused on the determinants of cycling – in particular the role of the built environment and road infrastructure. Bicycle parking has received little attention – even though bicycles are parked most of the time. This article reviews the scientific literature on bicycle parking and identifies existing gaps in research and knowledge. The review analyses 94 peer-reviewed papers identified through a search in Scopus and Web of Science, in December 2017. The annual number of papers increased 15-fold between 1995 and 2017. Overall, the level of evidence on the importance of bicycle parking is limited. The majority of studies are based on cross-sectional data with the presence of parking as a binary independent variable. Most studies focus on bicycle parking at public transport stops and at work places. Few studies report on bicycle parking throughout cities, and hardly any on parking at residential locations. Bicycle parking supply and quality appears to be a determinant of cycling for current and potential cyclists. Our findings can serve as input for an evidence-based debate on the role of bicycle parking. For practitioners, our research supports investment in bicycle parking, but acknowledges that a proper evaluation of such initiatives needs to be conducted to increase the level of evidence.     

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.     

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.     

Addressing electric vehicle (EV) sales and range anxiety through parking layout,policy and regulation

Electric Vehicles (EV) are highly beneficial due to their reliance on electricity and Climate Change response yet EV sales are lower than would be expected due to range anxiety. If a potential buyer cannot be assured of having constantly-available and compatible charging stations, they will not purchase an EV. To increase the sales of EVs through improved charger availability, this paper examines parking configurations, charger design, convenient “EV only” parking, free charging, etiquette in unplugging another’s vehicle, and legislation. Data were derived from academic publications, trade market press, conversations, personal observations, and laws. The results show that chargers are often in a lot’s corner and thus accessible only to one vehicle, EV owners leave their charged car in the space, drivers use EV spaces for parking, etiquette cards are not understood, and legislation makes it illegal to unplug another’s EV. Improvements include less convenient charger spots, an octopus charger in the middle of the parking lot, modest charging fees to foster turnover, chargers that indicate an EV is charged, education and legislation about etiquette cards, and legislation that allows an individual to unplug another’s charged EV. Improvements to charging should be implemented simultaneously to lessen range anxiety and realize the environmental benefits from reductions in gasoline consumption and mobile source air pollution.     

Truck parking in urban areas: Application of choice modelling within traffic microsimulation

Urban truck parking policies include time restrictions, pricing policies, space management and enforcement. This paper develops a method for investigating the potential impact of truck parking policy in urban areas. An econometric parking choice model is developed that accounts for parking type and location. A traffic simulation module is developed that incorporates the parking choice model to select suitable parking facilities/locations. The models are demonstrated to evaluate the impact of dedicating on-street parking in a busy street system in the Toronto CBD. The results of the study show lower mean searching time for freight vehicles when some streets are reserved for freight parking, accompanied by higher search and walking times for passenger vehicles.     

Generic model for resource allocation in transportation. Application to urban parking management

In this paper, we define the online localized resource allocation problem, especially relevant for modeling transportation applications. The problem modeling takes into account simultaneously the geographical location of consumers and resources together with their online nondeterministic appearance. We use urban parking management as an illustration of this problem. In fact, urban parking management is an online localized resource allocation problem, where the question is how to find an efficient allocation of parking spots to drivers, while they all have dynamic geographical positions and appear nondeterministically. We define this problem and propose a multiagent system to solve it. The objective of the system is to decrease, for private vehicles drivers, the parking spots search time. The drivers are organized in communities and share information about spots availability. We have defined two cooperative models and compared them: a fully cooperative model, where agents share all the available information, and a “coopetitive” model, where drivers do not share information about the spot that they have chosen. Results show the superiority of the first model.     

A study on smart parking guidance algorithm

Parking problem becomes one of major issues in the city transportation management since the spatial resource of a city is limited and the parking cost is expensive. Lots of cars on the road should spend unnecessary time and consume energy during searching for parking due to limited parking space. To cope with these limitations and give more intelligent solutions to drivers in the selection of parking facility, this study proposes a smart parking guidance algorithm. The proposed algorithm supports drivers to find the most appropriate parking facility considering real-time status of parking facilities in a city. To suggest the most suitable parking facility, several factors such as driving distance to the guided parking facility, walking distance from the guided parking facility to destination, expected parking cost, and traffic congestion due to parking guidance, are considered in the proposed algorithm. To evaluate the effectiveness of the proposed algorithm, simulation tests have been carried out. The proposed algorithm helps to maximize the utilization of space resources of a city, and reduce unnecessary energy consumption and CO₂ emission of wandering cars since it is designed to control the utilization of parking facility efficiently and reduce traffic congestion due to parking space search.     

Automated parking surveys from a LIDAR equipped vehicle

Parking surveys provide quantitative data describing the spatial and temporal utilization of parking spaces within an area of interest. These surveys are important tools for parking supply management and infrastructure planning. Parking studies have typically been performed by tabulating observations by hand, limiting temporal resolution due to high labor cost. This paper investigates the possibility of automating the data gathering and information extraction in a proof of concept study using a two-dimensional scanning Light Detection and Ranging (LIDAR) sensor mounted on a vehicle, though the work is compatible with other ranging sensors, e.g., stereo vision. This study examines parallel parking in the opposing direction of travel. The ranging measurements are processed to estimate the location of the curb and the presence of objects in the road. Occlusion and location reasoning are then applied to determine which of the objects are vehicles, and whether a given vehicle is parked or is in the traffic-stream. The occupancy of the parking area, vehicle size, and vehicle-to-vehicle gaps are then measured. The algorithm was applied to an area with unmarked, on-street parking near a large university campus. Vehicle counts from 29 trips over 4 years were compared against concurrent ground truth with favorable results. The approach can also be applied to monitor parking in the direction of travel, eliminating the possibility of occlusions and simplifying the processing.     

A simple reservation and allocation model of shared parking lots

With increasing auto demands, efficient parking management is by no means less important than road traffic congestion control. This is due to shortages of parking spaces within the limited land areas of the city centers in many metropolises. The parking problem becomes an integrated part of traffic planning and management. On the other hand, it is a fact that many private parking spots are available during daytime in nearby residential compound because those residents drive their cars out to work. These temporarily vacant parking lots can be efficiently utilized to meet the parking demand of other drivers who are working at nearby locations or drivers who come for shopping or other activities. This paper proposes a framework and a simple model for embracing shared use of residential parking spaces between residents and public users. The proposed shared use is a winning strategy because it maximizes the use of private resources to benefit the community as a whole. It also creates a new business model enabled by the fast-growing mobile apps in our daily lives.     

A review of the impact of parking policy measures on travel demand

This paper reviews the empirical evidence relating to the impact of parking policy measures on the demand for parking and for travel. Disaggregate modal choice models, disaggregate parking location models and site‐specific studies of parking behaviour are examined. With regard to modal choice models, it is concluded that few studies deal adequately with parking factors, but that there is some support for the view that parking policy measures are a relatively important influence on modal choice. When parking location models are examined parking policy variables are shown to have a substantial impact on choice of parking location. With regard to site‐specific studies, the paper concludes that there is a great variation in the parking price elasticities quoted, which reflects partly the methodological problems associated with such studies. Suggestions to improve model specification are made.     

The residential parking rent price elasticity of car ownership in Japan

By using household-level micro data captured through the National Survey of Family Income and Expenditure for 2004, this study evaluates the residential parking rent price elasticity of car ownership in Japan. It analyzes the number of cars owned by a household, using various attributes including expenditure for renting a parking space on a monthly basis. The estimation results derived from the IV-ordered probit model show that the absolute value of parking rent price elasticity of car ownership is, at most, 0.48, which is fairly small (i.e., inelastic). The elasticity value varies depending on city size; for megacities, elasticity is always negative for car ownership, whereas for middle-sized or small cities, towns, and villages, elasticity is positive for one-car ownership and negative for the ownership of more than one car. Hence, when the price of parking increases, some people may switch from more than one car to one car and some people in megacities may switch from one to zero cars. Indeed, the net effect of a price increase may be that non-car ownership increases in megacities and one-car ownership increases in other cities.     

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%.     

Parking policy,parking location decisions and the distribution of congestion

The paper develops and tests a model which characterizes the parking location decisions of individual tripmakers. The model is designed to offer information concerning the effects of alternative parking policies on parking location decisions and therefore the effects on the distribution of congestion in an urban area.Own price, time price and full price elasticities for alternative parking locations are estimated. The own price elasticity is found to rise with distance from the destination point while the time price elasticity falls with distance. The full price elasticity is found to be relatively stable.One is able to determine from the calculated elasticities, the effects of alternative parking policies such as raising parking fees, time restrictions, or increasing search or transaction costs on the distribution of individuals consuming parking services; from this one can infer the impact on the distribution of congestion.The paper also offers some explanation for the low elasticity of auto use with respect to changes in parking costs found in some modal choice studies.The author is indebted to Adolf Buse, Ken Norrie and Richard Westin for helpful comments and criticism.     

An improved incremental assignment model for parking variable message sign location problem

Operators and planners of parking guidance and information system (PGIS) often encounter the difficulty when and how to provide parking information to drivers in peak hours. The aim of this study was to assign the parking demands onto the urban network, find the positions suitable to locate the parking variable message sign (parking VMS), and try to solve the problem when to provide parking information to drivers. Parking VMS, as the most common forms of the information display terminal of PGIS, becomes critical in designing PGIS. This paper started from analyzing the relationship between the location and the performances of parking VMS. If a parking VMS is placed right along the link approaching to the divarication intersection of the subsequent “shortest path” and the previous one, the travel time declines abruptly, and the guiding compliance ratio becomes superior. Then, the network‐based parking choice model for the parking VMS was proposed. Network modification and incremental assignment were used to find the divarication intersections caused by the changes of space availability. In addition, MATLAB software package (MathWorks, Inc., Natick, MA, USA) was adopted to calculate the entire process mentioned. The proposed model and the algorithm were applied to a numerical example, where the location of parking VMS was obtained. Copyright © 2015 John Wiley & Sons, Ltd.