On the morning commute problem with carpooling behavior under parking space constraint

Morning commuters choose their departure times and travel modes based on a combinational evaluation of factors associated with the chances of running into bottleneck congestion, likely schedule delays, parking space availability as well as monetary costs of traveling and parking. This study investigates a morning commute problem with carpooling behavior under parking space constraint at destination. We consider such a scenario that as a competing mode of the transit line, the highway contains a carpool lane only used by carpoolers while all solo drivers are forced to use a general purpose (GP) lane. Unlike the standard bottleneck model, the rush-hour dynamic departure patterns with a binding parking supply vary with the relative proportion of the two lanes’ capacities. The possible departure pattern domain with different parking supply and lane capacity allocation is explored in terms of the relative extra carpool cost and distinguished between the bi-mode and multi-mode equilibria. It is found that compared with solo drivers, carpoolers have shorter rush hour in order to smooth the extra carpool cost. With the decrease of parking spots, the number of solo drivers cuts down gradually, whilst the number of carpoolers climbs up firstly and then declines in the multi-mode system. Under mild assumptions, the best system performance can be realized with the joint consideration of total travel cost and vehicle emission cost through optimizing the lane capacity allocation and the parking supply.     

Dynamic pricing and reservation for intelligent urban parking management

Despite rapid advances of information technologies for intelligent parking systems, it remains a challenge to optimally manage limited parking resources in busy urban neighborhoods. In this paper, we use dynamic location-dependent parking pricing and reservation to improve system-wide performance of an intelligent parking system. With this system, the parking agency is able to decide the spatial and temporal distribution of parking prices to achieve a variety of objectives, while drivers with different origins and destinations compete for limited parking spaces via online reservation. We develop a multi-period non-cooperative bi-level model to capture the complex interactions among the parking agency and multiple drivers, as well as a non-myopic approximate dynamic programming (ADP) approach to solve the model. It is shown with numerical examples that the ADP-based pricing policy consistently outperforms alternative policies in achieving greater performance of the parking system, and shows reliability in handling the spatial and temporal variations in parking demand.     

Parking space management via dynamic performance-based pricing

In congested urban areas, it remains a pressing challenge to reduce unnecessary vehicle circling for parking while at the same time maximize parking space utilization. In observance of new information technologies that have become readily accessible to drivers and parking agencies, we develop a dynamic non-cooperative bi-level model (i.e. Stackelberg leader–follower game) to set parking prices in real-time for effective parking access and space utilization. The model is expected to fit into an integrated parking pricing and management system, where parking reservations and transactions are facilitated by sensing and informatics infrastructures, that ensures the availability of convenient spaces at equilibrium market prices. It is shown with numerical examples that the proposed dynamic parking pricing model has the potential to virtually eliminate vehicle circling for parking, which results in significant reduction in adverse socioeconomic externalities such as traffic congestion and emissions.     

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.     

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 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.     

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.     

Equilibrium analysis and route guidance in large-scale networks with MFD dynamics

Recent studies have demonstrated that Macroscopic Fundamental Diagram (MFD), which provides an aggregated model of urban traffic dynamics linking network production and density, offers a new generation of real-time traffic management strategies to improve the network performance. However, the effect of route choice behavior on MFD modeling in case of heterogeneous urban networks is still unexplored. The paper advances in this direction by firstly extending two MFD-based traffic models with different granularity of vehicle accumulation state and route choice behavior aggregation. This configuration enables us to address limited traffic state observability and to scrutinize implications of drivers’ route choice in MFD modeling. We consider a city that is partitioned in a small number of large-size regions (aggregated model) where each region consists of medium-size sub-regions (more detailed model) exhibiting a well-defined MFD. This paper proposes a route guidance advisory control system based on the aggregated model as a large-scale traffic management strategy that utilizes aggregated traffic states while sub-regional information is partially known. In addition, we investigate the effect of equilibrium conditions (i.e. user equilibrium and system optimum) on the overall network performance, in particular MFD functions.     

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.     

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.     

System dynamics of urban traffic based on its parking-related-states

The urban parking and the urban traffic systems are essential components of the overall urban transportation structure. The short-term interactions between these two systems can be highly significant and influential to their individual performance. The urban parking system, for example, can affect the searching-for-parking traffic, influencing not only overall travel speeds in the network (traffic performance), but also total driven distance (environmental conditions). In turn, the traffic performance can also affect the time drivers spend searching for parking, and ultimately, parking usage. In this study, we propose a methodology to model macroscopically such interactions and evaluate their effects on urban congestion.The model is built on a matrix describing how, over time, vehicles in an urban area transition from one parking-related state to another. With this model it is possible to estimate, based on the traffic and parking demand as well as the parking supply, the amount of vehicles searching for parking, the amount of vehicles driving on the network but not searching for parking, and the amount of vehicles parked at any given time. More importantly, it is also possible to estimate the total (or average) time spent and distance driven within each of these states. Based on that, the model can be used to design and evaluate different parking policies, to improve (or optimize) the performance of both systems.A simple numerical example is provided to show possible applications of this type. Parking policies such as increasing parking supply or shortening the maximum parking duration allowed (i.e., time controls) are tested, and their effects on traffic are estimated. The preliminary results show that time control policies can alleviate the parking-caused traffic issues without the need for providing additional parking facilities. Results also show that parking policies that intend to reduce traffic delay may, at the same time, increase the driven distance and cause negative externalities. Hence, caution must be exercised and multiple traffic metrics should be evaluated before selecting these policies.Overall, this paper shows how the system dynamics of urban traffic, based on its parking-related-states, can be used to efficiently evaluate the urban traffic and parking systems macroscopically. The proposed model can be used to estimate both, how parking availability can affect traffic performance (e.g., average time searching for parking, number of cars searching for parking); and how different traffic conditions (e.g., travel speed, density in the system) can affect drivers ability to find parking. Moreover, the proposed model can be used to study multiple strategies or scenarios for traffic operations and control, transportation planning, land use planning, or parking management and operations.     

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.     

How to restrain participants opt out in shared parking market? A fair recurrent double auction approach

We propose a fair recurrent double VCG (FRD-VCG) auction mechanism to approach the emerging shared parking management problem. In a given shared parking environment with a parking management platform and a double-side perspective, the proposed mechanism considers how to restrain the potential participants (parking slot demanders and slot suppliers) opt out, which is based on the participants’ priority attributes and are calculated with respect to historic auction records provided by the parking platform. Participants’ fairness bids are then generated combining their priority attributes and their submitted bids (bid price and parking time) with the support of a novel evaluation function, which integrates priority attributes, bid price and parking time into an output value. The parking slot allocation rule and transaction payment rule are further designed to dealing with these issues include winner determination and price setting, respectively. Simulations show advantages of the proposed FRD-VCG mechanism, i.e., comparing with the double VCG (D-VCG) mechanism for the shared parking management problem where priority attributes and evaluation function are not considered, the proposed FRD-VCG mechanism has the potential to persuade participants to remain in the market whilst it improves the market’s retention rate, the parking slot’s utilization rate and the participants’ utilities.     

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.     

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.     

Incorporating time and income constraints in dynamic agent-based models of activity generation and time use: Approach and illustration

Existing theories and models in economics and transportation treat households’ decisions regarding allocation of time and income to activities as a resource-allocation optimization problem. This stands in contrast with the dynamic nature of day-by-day activity-travel choices. Therefore, in the present paper we propose a different approach to model activity generation and allocation decisions of individuals and households that acknowledges the dynamic nature of the behavior. A dynamic representation of time and money allocation decisions is necessary to properly understand the impact of new technologies on day to day variations in travel and activity patterns and on performance of transportation systems. We propose an agent-based model where agents, rather than acting on the basis of a resource allocation solution for a given time period, make resource allocation decisions on a day-by-day basis taking into account day-varying conditions and at the same time respecting available budgets over a longer time horizon. Agents that share a household interact and allocate household tasks and budgets among each other. We introduce the agent-based model and formally discuss the properties of the model. The approach is illustrated on the basis of simulation of behavior in time and space.     

Parking permits management and optimal parking supply considering traffic emission cost

Given a many-to-one bi-modal transportation network where each origin is connected to the destination by a bottleneck-constrained highway and a parallel transit line, we investigate the parking permit management methods to minimize traffic time cost and traffic emission cost simultaneously. More importantly, the optimal supply of parking spots is also discussed in the policies of parking permit. First, we derive the total travel costs and emission costs for the two cases of sufficient and insufficient parking spot provisions at the destination. Second, we propose a bi-objective model and solve the Pareto optimal parking permit distribution, given a certain level of parking supply. Third, we investigate the optimal parking supply in the policy of parking permit distribution, with the objectives of minimizing both total travel cost and traffic emission. Fourth, we provide a model of optimizing parking supply, in the policy of free trading of parking permits. Finally, the numerical examples are presented to illustrate the effectiveness of these schemes, and the numerical results show that restricting parking supply at the city center could be efficient to reduce traffic emission.     

Optimal cordon pricing in a non-monocentric city

This paper examines the effect of cordon pricing based on an urban spatial model of a non-monocentric city where trips may occur between any pair of locations in the city. The model describes the spatial distribution of trip demand and traffic congestion under alternative pricing schemes. We evaluate the efficiency of resource allocation by comparing three schemes: no-toll equilibrium, first-best optimum, and optimal cordon pricing. Optimal cordon pricing is defined as a combination of cordon location and toll level that maximizes the social surplus in a city. Simulations show that cordon pricing is not always effective for congestion management: cordon pricing tends to be effective as the urban structure is more monocentric.     

Stochastic Poisson game for an online decentralized and coordinated parking mechanism

This paper proposes a decentralized and coordinated online parking mechanism (DCPM), which seeks to reduce parking congestion at multiple parking facilities in a central business district (CBD) through guiding the parking decisions of a parking coordination group. To establish this DCPM, this study develops a stochastic Poisson game to model the competitions among parking vehicles en route at multiple parking facilities. The equilibrium condition for the proposed stochastic Poisson game is formulated through involving travelers’ parking choice behavior described by multinomial logit model. Furthermore, we prove that the stochastic Poisson game is a potential game with a unique equilibrium. A simultaneously updating distributed algorithm is developed to search the equilibrium solution of the DCPM. Its convergence is proved by both mathematical analysis and numerical experiments. The numerical experiments are conducted to test the efficiency of the DCPM, based on a real-world CBD covering Guicheng Community, Nanhai District at Foshan in China. The performance of the DCPM is compared to three greedy strategies following the nearest first, cheapest first, and least cruise first policies, respectively. The experimental results demonstrate that the DCPM significantly reduces cruise vehicles and average cruise distance per vehicle from all other three greedy strategies; the least cruise first strategy, which takes advantage of the real-time open spots information at parking facilities, performs better than the nearest first and the cheapest first strategies without the access to real-time information. The DCPM can further improve the benefit of the real-time information. Additionally, in terms of walking distance and parking cost, the DCPM provide a trade-off solution between the nearest first and the cheapest first strategies.     

Parking difficulty and parking information system technologies and costs

Before the implementation of a parking information system, it is necessary to evaluate the parking difficulty, technology choice, and system costs. In this study, the parking problem was quantified by asking parkers to express their parking difficulties in five scaled levels from the least to the most difficult. An ordered Probit model was developed to identify the factors that influence a parker to feel the parking difficulty. The results indicate that the amount of parking information parkers had before their trips was directly related to their parking search time, which in turn, influenced their perceptions of parking difficulty. Parkers' preferences to parking information technologies were identified based on developing binary and multinomial probit models. The results indicate that personal business trips and older persons would like to use the kiosk, while the more educated and males would not. Trips with shopping and social/recreation purposes and the drivers who had visited the destination areas frequently would like to choose roadside display. Drivers who had planned their parking and had Internet access would use in‐vehicle device. The system cost was estimated based on the cost for each component of the system. The results show that providing en‐route parking search information through roadside displays is more expensive than providing pre‐trip information through a web site.