Analysis of parking behavior and the mechanism of parking decisions is essential for balancing the spatial–temporal distribution of parking and formulating parking management policies. Using parking ...information from Beijing China, in 2014, a structural equation model was established to analyze the impacts of travelers’ personal/family attributes, the trip purpose and parking rates on parking decisions. The one-way and two-way relationships between three parking decisions, namely, the parking period, parking location, and parking duration were examined. The results indicate that there is a two-way relationship between on-street parking and parking duration. The reason for this relationship is that the layout of free and legal on-street parking spaces does not combine the surrounding land use properties and trip purpose, resulting in an uneven spatial and temporal distribution of parking options. The results also show that the increase of parking fees will promote shortening the parking duration; travelers with the purpose of work will have longer parking duration; and the greater the number of passengers, the higher the probability of on-street parking will be. These findings can be used to help developing measures to regulate parking behavior by controlling relevant factors. By applying a structural equation model, this study also makes a methodological contribution to testing the correlation among related parking decisions and graphically visualizing the parking decision-making process.
•A structural equation model was established to analyze parking decisions.•The data used in the study come from parking information in Beijing City.•The relationships between three parking decisions were examined.•The results indicate two-way correlation between on-street parking and duration.•The findings can be used in developing measures to regulate parking behavior.
Parking regulation is seen as a good option to encourage modal shift in order to tackle congestion and pollution in metropolitan areas. Market-clearing curbside pricing is rarely implemented and ...policy makers have tended to make off-street parking provision their main tool to address excessive curbside demand. Research devoted to garage parking is far less well developed, even though public authorities provide both curbside and garage parking that compete with privately operated facilities.
In this paper the impact of garage fare and curbside regulation characteristics (fare and type of dedicated spaces) on garage parking demand are investigated. Aggregate occasional and subscribers parking demand is analyzed by means of two different econometric models estimated using a panel from Barcelona’s public parking authority (BSM) that covers 34 garage facilities with yearly data for the period 2006–2012.
We find that both demand segments show a negative elasticity to garage fare. Only occasional parkers show a clear substitution effect with a curbside premium (€0.55/h). Our finding suggests that the actual pricing efficiency gap in Barcelona can range between €0.45 and €1.05 due to the mismatch between curbside and garage pricing regimes; for which we propose some policy alternatives. This stresses the need for a single integrated market approach to parking management, in order to overcome market distortions and achieve efficiency. Additionally, our results show that the characteristics of curbside parking spaces (allowance and time limits) play a role in garage demand determination, yet pricing is much more efficient trigger for behavioral change.
•Occasional parkers and subscribers show a negative elasticity to garage fares.•Curbside and garage parking are substitutes (curb premium €0.55/h).•The pricing efficiency gap in Barcelona ranges between €0.45 and €1.05/h.•The type of space has an impact on demand (different for each segment).•Curbside and garage parking should be integrated into a single management approach.
Abstract
The traditional parking generation rate model can no longer forecast the demand of parking slots accurately under the pattern of shared parking. Shared parking, which can make full use of ...the free time of private or non-private parking slots, has become an effective way to ease the pressure of urban parking. Therefore, shared parking behavior selection generation (SPBSG) model is established, based on the analysis of residents’ shared parking selection behavior. The SPBSG model fully simulates residents’ parking choice preferences, shared slots management, parking time differences between different land types, and walking distance after parking. Experiment shows that the SPBSG model can reduce parking slots by 24.45% compared with the traditional parking demand prediction method.
In rapidly growing cities, on-street parking spaces consistently serve as a supplement to urban parking supply. However, prolonged curb occupancy remains a prevalent issue on roadways with limited ...parking management, leading to reduced traffic flow and safety concerns in non-motorized areas. To support the formulation of fine-grained management strategies based on on-street parking duration (OPD), we investigate the distribution of OPD across various roadway segments and explore the factors influencing it at different scales. Real data are obtained from a newly built-up area of Xi'an, China, and the spatial effects of factors influencing OPD are modeled using a multiscale geographically weighted regression (MGWR) method. Results show that the number of parking events, the number of parking spaces, employment buildings, the parking space location, and the distance to adjacent bus stops spatially significantly affect the OPD on both weekdays and weekends. The lowest parking fee level is positively associated with weekday OPD. The estimated coefficients of the variables for on-street parking lots are spatially heterogeneous, which is discussed with the substantial parking policy implications. This study can inform enhanced parking management policies in cities through spatial effects analysis.
•On-street parking duration (OPD) is investigated in newly built-up urban areas.•The multiscale GWR is utilized to capture the spatial effects of OPD influences.•Policy implications for parking management are given with further discussion.
Ride-sourcing services have become increasingly important in meeting travel needs in metropolitan areas. However, the cruising of vacant ride-sourcing vehicles generates additional traffic demand ...that may worsen traffic conditions. This paper investigates the allocation of a certain portion of road space to on-street parking for vacant ride-sourcing vehicles. A macroscopic conceptual framework is developed to capture the trade-off between capacity loss and the reduction of cruising. Considering a hypothetical matching mechanism adopted by the platform, we further materialize the framework and then apply it to study the interactions between the ride-sourcing system and parking provision under various market structures.
•We propose an effective CNN architecture for visual parking occupancy detection.•The CNN architecture is small enough to run on smart cameras.•The proposed solution performs and generalizes better ...than other SotA approaches.•We provide a new training/validation dataset for parking occupancy detection.
A smart camera is a vision system capable of extracting application-specific information from the captured images. The paper proposes a decentralized and efficient solution for visual parking lot occupancy detection based on a deep Convolutional Neural Network (CNN) specifically designed for smart cameras. This solution is compared with state-of-the-art approaches using two visual datasets: PKLot, already existing in literature, and CNRPark-EXT. The former is an existing dataset, that allowed us to exhaustively compare with previous works. The latter dataset has been created in the context of this research, accumulating data across various seasons of the year, to test our approach in particularly challenging situations, exhibiting occlusions, and diverse and difficult viewpoints. This dataset is public available to the scientific community and is another contribution of our research. Our experiments show that our solution outperforms and generalizes the best performing approaches on both datasets. The performance of our proposed CNN architecture on the parking lot occupancy detection task, is comparable to the well-known AlexNet, which is three orders of magnitude larger.
•Microsimulation of freight double parking operations for two 1km2 case-studies.•Measured the impact of double-parking operations on passing traffic.•Freight traffic causes a disproportionate amount ...of externalities.•Re-arranging the bay system configuration can lead to mobility improvements.•Road characteristics influenced the optimization strategy of the bay system.
The role of urban freight vehicle trips in fulfilling the consumption needs of people in urban areas is often overshadowed by externality-causing parking practices (e.g., double-parking associated with traffic delays). Loading/unloading bays are generally viewed as an effective way to avoid freight vehicles double-parking, but are often misused by non-freight vehicles. We assess the potential of reducing freight vehicles double-parking mobility impacts by changing: (a) the spatial configuration (number, location, size) of loading/unloading bays and, (b) the non-freight vehicles parking rules compliance levels.
Parking demand models were created with data from an establishment-based freight survey and a parking observation exercise. Two case studies were defined for 1km2 zones in the city of Lisbon, Portugal. Alternative bay systems were derived from an iterative implementation of the “maximize capacitated coverage” algorithm to a range of bays to be located. Parking operations in current and alternative bay systems were compared using a microsimulation. Bay systems’ ability in reducing double-parking impacts was assessed via a set of indicators (e.g., average speed).
Freight traffic causes a disproportionate amount of externalities and the current bay configuration leads to greater mobility impacts than some of the proposed systems. Enforcement was a crucial element in reducing parking operations impact on traffic flow in one of the case-studies. Road network characteristics were demonstrated to play a role in the adequate strategy of arranging the spatial configuration of bays.
Autonomous parking techniques can be used to tackle the lacking problem of parking spaces. In this paper, a sampling-based motion planner consisting of optimizing bidirectional rapidly-exploring ...random trees* (Bi-RRT*) and parking-oriented model predictive control (MPC) is proposed to properly deal with various parking scenarios. The optimal Bi-RRT* approach aims to improve the common defects of traditional sampling-based motion planners, such as uncertainties of path quality and consistency, and exploring inefficiency in narrow spaces. For this reason, the proposed motion planner is able to overcome strict environments with obstacles and narrow spaces. The parking-oriented MPC is then designed for steering and speed controls simultaneously for accurately and smoothly tracking parking paths. Furthermore, the proposed controller is dedicated to work under the practical scenarios, such as vehicle considerations, real-time control, and signal delay. To verify the effects of the proposed autonomous parking system, extensive simulations and experiments are conducted in common and strict parking scenarios, such as perpendicular parking, parallel parking. The simulation results not only verify the effects of each technical element, but also show the capability to deal with the various parking scenarios. Furthermore, various on-car experiments sufficiently demonstrate that the proposed system can be actually implemented in everyday life.
Finding a parking space is usually challenging in urban areas. The literature shows that 30% of traffic congestion is caused by searching for parking spaces, which results in unnecessary energy ...consumption and environmental pollution. With the development of sensor technologies, smart parking guidance systems provide users with a variety of real-time parking space information. However, users cannot know whether the target parking space remains available upon arrival. Moreover, parking resources may be under competition when multiple users target the same open parking space. In this research, we develop a new framework named prediction-based parking allocation (PPA) that provides smart parking services to users. In PPA, we first construct a prediction model of parking occupancy and predict the subsequent parking availabilities. Then, we design a matching-based allocation strategy to assign users to selected parking spaces. To the best of our knowledge, this is the first study that combines occupancy prediction and space allocation simultaneously to address smart parking issues. Finally, we collect a real dataset from the SFPark on-street parking system for performance evaluation. According to experimental results, PPA can effectively increase the parking success rate and reduce costs, fuel consumption, and carbon emissions.
This paper proposes a vacant parking slot detection and tracking system that fuses the sensors of an Around View Monitor (AVM) system and an ultrasonic sensor-based automatic parking system. The ...proposed system consists of three stages: parking slot marking detection, parking slot occupancy classification, and parking slot marking tracking. The parking slot marking detection stage recognizes various types of parking slot markings using AVM image sequences. It detects parking slots in individual AVM images by exploiting a hierarchical tree structure of parking slot markings and combines sequential detection results. The parking slot occupancy classification stage identifies vacancies of detected parking slots using ultrasonic sensor data. Parking slot occupancy is probabilistically calculated by treating each parking slot region as a single cell of the occupancy grid. The parking slot marking tracking stage continuously estimates the position of the selected parking slot while the ego-vehicle is moving into it. During tracking, AVM images and motion sensor-based odometry are fused together in the chamfer score level to achieve robustness against inevitable occlusions caused by the ego-vehicle. In the experiments, it is shown that the proposed method can recognize the positions and occupancies of various types of parking slot markings and stably track them under practical situations in a real-time manner. The proposed system is expected to help drivers conveniently select one of the available parking slots and support the parking control system by continuously updating the designated target positions.
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