A land use policy shift is taking place in a growing number of cities regarding parking, whereby a conventional supplymanagement approach is being replaced with a parking management approach. As part ...of this policy shift, manycities are lowering their parking requirements. This study analysed changes in car use, car ownership, spatial parkingpatterns and the consequences for the everyday life of residents in a housing area with a relatively restrictive parkingrequirement in Gothenburg, the second largest city in Sweden. The housing area, a concrete example of howlowering parking requirements can be used to achieve targets on reduced car use and sustainable urbandevelopment, is used to discuss how parking policy should be applied to achieve the desired effect. The results showthat the consequences of the restrictive requirement was paradoxically small in the study area. In practice, therequirement did not result in a decrease in the number of parking spaces, because e.g. of access to parking inneighbouring residential areas. This shows how important it is to adopt a holistic approach in parking policy, by e.g.introducing more restrictive parking requirements in parallel with other measures, such as raising parking charges anddecreasing the number of public parking spaces. It also shows that planning of parking must be coordinated with otherurban planning functions. Otherwise, the actual contribution of a shift in parking policy to the development of a moreenvironmentally friendly transport system and city risks being small, despite lower parking requirements.
Zum Titelbild Mit dem Parkhaus Rose Lane, Norwich, England gewann HUBER car park systems international den British Parking Award 2017 für das „Best New Car Park”
Cities usually handle residential parking through on-street parking management and off-street parking requirements. The two can impact each other but are frequently strategized independently. This ...paper focuses on residential on-street parking management, which is often dealt with through residential parking permit programs. A survey shows that there are two main types of programs: one that gives precedence to residents and another that restricts residential parking, with mainly the latter being politically explosive. Nevertheless, there is scant literature on the policies implemented in different cities internationally. More research efforts could lead to the formulation of sustainable policies and make the procedures more politically acceptable, in particular given new technologies that help eliminate the high installation and maintenance costs of meters and enforcement. The qualitative and quantitative evidence is analyzed to distill practical real-life solutions.
•We present various residential parking policies from cities worldwide.•We distinguish between different types of residential parking programs.•There is a limited data on the effects of the various policies.•Cities should shift from privileging residents to sustainable residential parking programs.•We review ways to enhance public acceptance of sustainable programs.
Parking lot allocation problem has received much attention in recent years. There have been various works in the literature that target the parking slot allocation problem. However, most of these ...works use algorithms that run on centralized servers and are based on some predictions on historical data. Due to the dynamic nature of vehicular networks, the accuracy of such prediction models is not high which ends up in a chaotic situation for the parking lot owners as well as the vehicle owners. Therefore, a distributed Parking slot Allocation Framework based on Adaptive Pricing Algorithm and Virtual Voting is proposed in this paper. The proposed model is based on virtual voting and hashgraph consensus algorithm. Using the model, all users and parking lot owners can easily come to consensus finality about the allocation of a parking slot with the use of minimal bandwidth. The proposed model provides a fair, fast and cost-optimal parking slot allocation method. The perfect ordering of allocation requests is also maintained based on consensus timestamp. Further, an adaptive pricing model is proposed to enhance the overall revenue of the parking lot owners and comfort of the users. The proposed model is deterministic and can reduce the average parking cost and time. Performance evaluations reveal that the proposed model outperforms its counterparts in terms of accurate parking slot allocation, reduced cost and parking lot resource utilization.
•A deep learning model is adopted for predicting block-level parking occupancy 30 min in advance.•The model takes multi-source data as input, e.g., parking, traffic and weather.•The model outperforms ...baseline methods including multi-layer LSTM and LASSO in the case study.•The prediction model works better for business areas than for recreational locations.•Incorporating traffic speed and weather data can significantly improve prediction performance.
A deep learning model is adopted for predicting block-level parking occupancy in real time. The model leverages Graph-Convolutional Neural Networks (GCNN) to extract the spatial relations of traffic flow in large-scale networks, and utilizes Recurrent Neural Networks (RNN) with Long-Short Term Memory (LSTM) to capture the temporal features. In addition, the model is capable of taking multiple heterogeneously structured traffic data sources as input, such as parking meter transactions, traffic speed, and weather conditions. The model performance is evaluated through a case study in Pittsburgh downtown area. The GCNN-based model outperforms other baseline methods including multi-layer LSTM and LASSO with an average testing MAPE of 10.6% when predicting block-level parking occupancies 30 min in advance. The case study also shows that, in generally, the prediction model works better for business areas than for recreational locations. We found that incorporating traffic speed and weather information can significantly improve the prediction performance. Weather data is particularly useful for improving predicting accuracy in recreational areas.
This study investigates the sensitivity of on-street parking demand using the automatic transaction data from parking pay stations obtained before and after a parking rate change that was implemented ...in Seattle in early 2011. The parking rate implementation is based on performance-based pricing where rates are increased, decreased, or not changed in neighborhoods with occupancy levels higher than, lower than, or within the desired level. We calculated the price elasticity of on-street parking demand, or the percentage change in block-level occupancy in response to a change in pricing, modified by time of day and neighborhood characteristics. This study is the first one that calculates price elasticity by time of day for on-street parking demand on a block level in the U.S. context. This study is also the first one that empirically derives how neighborhood characteristics affect on-street parking demand in response to pricing. Moreover, this study looks into how pricing results in changes in parking turnover rates, parking duration and total revenue generated.
Results confirm our hypotheses—price elasticity of the parking occupancy is inelastic and varies by time of day and neighborhood characteristics. In addition, the results showed that the pricing also affects parking duration: motorists park for a shorter time on average during the day in neighborhoods with increased rates and longer in neighborhoods with decreased rates. Performance based pricing policy seems to be lowering the turnover rates on average during the day in neighborhoods with increased rates, however, it appears working ideally in the peak-hours when the parking demand is the greatest, allowing more motorists to park. The decreased rate seemed to be increasing the parking occupancy during peak-hours when motorists see the benefit in paying lower fees.
The study demonstrated that the estimated elasticities can be used to determine the optimal parking rate to achieve a desired level of parking occupancy on every block in the study area. This method can be easily applied in every city that has similar parking pay stations.
► On-street parking demand varies by time of day and neighborhood characteristics. ► Motorists park for a shorter (longer) time with increased (decreased) rates. ► Performance-based parking increases turnovers during peak hours. ► Optimal parking rates can be calculated based on estimated elasticities of parking occupancy.
Parking guidance and information (PGI) systems are becoming important parts of intelligent transportation systems due to the fact that cars and infrastructure are becoming more and more connected. ...One major challenge in developing efficient PGI systems is the uncertain nature of parking availability in parking facilities (both on-street and off-street). A reliable PGI system should have the capability of predicting the availability of parking at the arrival time with reliable accuracy. In this paper, we study the nature of the parking availability data in a big city and propose a multivariate autoregressive model that takes into account both temporal and spatial correlations of parking availability. The model is used to predict parking availability with high accuracy. The prediction errors are used to recommend the parking location with the highest probability of having at least one parking spot available at the estimated arrival time. The results are demonstrated using real-time parking data in the areas of San Francisco and Los Angeles.
•AV car-parks can have multiple rows of vehicles stacked behind each other.•We present a relocation strategy to retrieve AVs that are blocked in the multi-row design.•We quantify the maximum number ...of AVs that can fit in a car-park with given dimensions.•We show that AV car-parks can decrease parking space by an average of 62%.
Display omitted
Autonomous vehicles will have a major impact on parking facility designs in the future. Compared to regular car-parks that have only two rows of vehicles in each island, future car-parks (for autonomous vehicles) can have multiple rows of vehicles stacked behind each other. Although this multi-row layout reduces parking space, it can cause blockage if a certain vehicle is barricaded by other vehicles and cannot leave the facility. To release barricaded vehicles, the car-park operator has to relocate some of the vehicles to create a clear pathway for the blocked vehicle to exit. The extent of vehicle relocation depends on the layout design of the car-park. To find the optimal car-park layout with minimum relocations, we present a mixed-integer non-linear program that treats each island in the car-park as a queuing system. We solve the problem using Benders decomposition for an exact answer and we present a heuristic algorithm to find a reasonable upper-bound of the mathematical model. We show that autonomous vehicle car-parks can decrease the need for parking space by an average of 62% and a maximum of 87%. This revitalization of space that was previously used for parking can be socially beneficial if car-parks are converted into commercial and residential land-uses.
•We propose a novel approach for parking and congestion control in an area of mixed CVs and AVs.•The MFD model incorporates flow dynamics of normal traffic, cruising-for-parking, and dispatching ...AVs.•MPC is developed to find the optimal dispatch rate and regional route guidance control inputs of AVs.•The results show that the proposed models are effective in reducing intense cruising-for-parking traffic.
The spatio-temporal imbalance of parking demand and supply results in unwanted on-street cruising-for-parking traffic of conventional vehicles. Autonomous vehicles (AVs) can self-relocate to alleviate the shortage of parking supplies at the trip destinations. The extra floating trips of vacant AVs have adverse impacts on traffic congestion and the parking demand–supply imbalance may still exist when they are not distributed optimally. This paper presents a centralized parking dispatch approach to optimize the distribution of floating AVs and provide regional route guidance. We apply the concept of macroscopic fundamental diagram to represent the evolution of traffic conditions, cruising-for-parking, and dispatched AVs in a congested multi-region network. A model predictive control is suggested to optimize the control inputs. Numerical experiments in a four-region network demonstrate that the proposed parking dispatch and regional route guidance of AVs are effective in reducing intense cruising-for-parking traffic, and the integration of both has the best control performance by regulating the network towards under-saturated conditions. The performance of the proposed schemes is evaluated via simulations with noise in measurement errors and compliance rate prediction. Results show substantial improvements in terms of total time spent, even for low levels of AV market penetration or AV compliance rate to parking dispatch and route guidance.
Autonomous parking valet systems improve users' comfort, helping with the task of searching for a parking space and parking maneuvering; and due to the simple infrastructure design and low speeds, ...this maneuver is quite feasible for automated vehicles. Various demonstrations have been performed in both closed parking and in open air parking; scenarios that allow the use of specific technological tools for navigation and searching for a parking space. However, there are still challenges. The purpose of this paper was the integration of perception, positioning, decision-making, and maneuvering algorithms for the control of an autonomous vehicle in a parking lot with the support of a single LiDAR sensor, and with no additional sensors in the infrastructure. Based on a digital map, which was as simplified as possible, the driver can choose the range of parking spaces in which the vehicle must look for a space. From that moment on, the vehicle moves, looking for free places until an available one in the range selected by the driver is found. Then, the vehicle performs the parking maneuver, choosing between two alternatives to optimize the required space. Tests in a real parking lot, with spaces covered with metallic canopies, showed an accurate behavior.
PDF
