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Impact of the supply of parking spaces on parking lot choice
Abstract
A model for predicting parking occupation in a park 'n ride situation is presented. The demand side of this model uses a maximum entropy formulation and the supply side considers explicit capacity constraints on parking space. Therefore the impact of a change in the supply of parking capacity can be easily predicted. This methodology is applied on data gathered for the Lindenwold High Speed Line Study. The approach can be extended to other problems which involve the interaction between direct demand zonal aggregate functions and supply constraints on the discrete alternatives chosen.
... The network-based approach, which explores travelers' choice behavior in a network-based framework, has been carried out by using a linear programming approach [9,16], an entropy maximization approach [13,14,38,39], and an equilibrium assignment approach [6,17,23,24,31,36,41]. All these network-based models explicitly take the topological structure of transport networks into account. ...
... where λ r s , λ au r s , πa, and µ i are the Lagrange multipliers associated with Equations (9), (10)- (12), respectively. Therefore, we can easily derive that the first-order optimality conditions of the model (8)-(14) comprise the original constraints (9)- (14) and the following Equations (16)- (19): ...
... Equation (21) implies that C r s,i p = λ au r s , if f rs, ip ≥ 0 and C r s,i p ≥ λ au r s , otherwise, ∀p ∈ P ri , i ∈ Irs, r ∈ R, s ∈ S. Therefore, the optimal solution of the mathematical programming model (8)- (14) corresponds to a user equilibrium state of the simultaneous route and parking location choice: For each OD pair, the used route-parking alternative has the minimal travel disutility, and the travel disutility of any unused route-parking alternative is greater than or equal to the minimum. ...
This paper presents a model for evaluation of transport policies in multimodal networks with road and parking capacity constraints.
The proposed model simultaneously considers choices of travelers on route, parking location and mode between auto and transit.
In the proposed model, it is assumed that auto drivers make a simultaneous route and parking location choice in a user equilibrium
manner, and the modal split between auto and transit follows a multinomial logit formulation. A mathematical programming model
with capacity constraints on road link and parking facilities is proposed that generates optimality conditions equivalent
to the requirements for multimodal network equilibrium. An augmented Lagrangian dual algorithm embedded by partial linearization
approach is developed to solve the proposed model. Numerical results on two example networks are presented to illustrate the
proposed methodology. The results show that the service level of transit, parking charges, road link and parking capacities,
and addition of a new parking location may bring significant impacts on travelers’ behavior and network performance. In addition,
transport policies may result in paradoxical phenomenon.
... Some papers have lower infrastructural requirements, e.g., [7,36], while others heavily depend on external data, e.g., [102]. ...
... Allocating parking facilities to vehicles has been studied by the OR community for more than 40 years. One of the first surveys appeared in Florian & Los [36]. Although the problem of allocating cars to parking facilities is clearly combinatorial, there is no uniform MP model for it, and no standardized formulation. ...
This thesis focuses on the problem of urban parking, especially in peak traffic hours. One of the main objectives is to explore the solution methods from operational research perspective and to provide practical solutions through mathematical programming and heuristics.We first consider a simplified, static version of the problem in which all the necessary data is fixed and deterministic over a one-day planning horizon. A 0-1 programming model derived from the generalized assignment problem is proposed and tested on a randomly generated set of instances. Extensions that include different objective functions and other modes of transport are also examined. In addition, we proposed a heuristic based on variable neighborhood search to quickly obtain a good quality solutions.The dynamic nature of the problem has led us to adapt this model so that it can take into account the continuous data updates. We have proposed and evaluated several policies and scenarios, with the goal of developing a system that is as adaptive and robust as possible. The proposed system should be able to guide users to a parking lot assigned to them when possible, or to their destination when their is no parking slot available.Our approach is corroborated via simulation over a set of real data collected from three major European cities.
... Multiple attributes influence the choice of a driver for a given parking alternative. The parking price, availability and accessibility, the three components of parking facilities, considerably affect the driver's parking activity and decision-making (Florian 1980; Zhen (Sean) Qian 2013).Particularly, the number of available parking spaces is an important attribute in the driver's parking decision-making process (Caicedo 2009). Available parking space is defined as parking spaces which are not occupied by vehicles or other goods and could be used to park in an opening parking facility (Thompson 1989). ...
... The key National Natural Science Foundation of China (No.51338003) and the financial support from the National Key Basic Research Program of China (No. 2012CB725402) is gratefully acknowledged. The authors would also like to thank for the support from the School of Civil Engineering and Geosciences at 12 Newcastle University and Tyne and Wear 'Urban Traffic Management Control' (UTMC) System. ...
The technique to forecast available parking spaces (APSs) is the foundation theory of parking guidance information systems (PGISs). This study utilises data collected on parking availability at several off-street parking garages in Newcastle upon Tyne, England, to investigate the changing characteristics of APS. Using these baseline data the research reported here aims to build up a short-term APS forecasting model and applies the wavelet neural network (WNN) method to the PGIS problem. After selecting optimal preferences, including training set size, delay time and embedding dimension, the APS short-term forecasting model based on WNN is built and tested using the real-world dataset. By experimental tests conducted using the same dataset, WNN's prediction performance is compared with the largest Lyapunov exponents (LEs) method in the aspects of accuracy, efficiency and robustness. It is found that WNN prevails through a more efficient structure and employs, barely half of the computational cost compared to the largest LEs method, which could be significant if applied to real-time operation. Moreover, WNN enjoys a more accurate performance, for its prediction average mean square error (MSE) is 6.4 +/- 3.1 (in a parking building with 492 parking lots) for workdays and 8.5 +/- 6.2 for weekends, compared to the MSE of largest LEs method, 18.7 and 29.0, respectively.
... Previous studies considered the parking space demand as the main impact factors. Regarding the parking space demand, various studies have been conducted worldwide [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21]. First, international studies on the parking space demand of the ESA were conducted as follows. ...
... Based on the national research, other studies focused on the demand for truck parking space, the impact of the truck parking space on truck parking facilities, parking location, transportation infrastructure, safety, local economy, and environment. There were also several studies related to parking space, location and pricing, and rest area facility design [16][17][18][19][20][21]. As such, international previous studies mainly dealt with the truck parking space demand, of which focus was different from the ESAs in South Korea in terms of the type of ESA. ...
... Florian and Los (8,9) included the concept of entropy-based trip distribution to account for the dispersion of destination choice due to behavioral aspects. The major innovation of this work was to explicitly consider parking lot capacities in the formulation. ...
... By analyzing the Lagrangian function of problem (4), it can be verified that the solution of problem (4) is almost identical to Equation (2) but the dual variable s λ is associated with lot s. This term could be viewed as the additional disutility imposed by the capacity of parking lot s as described by Florian and Loss (8,9). Moreover, it can be shown that if the parking lot s is not used at its capacity, i.e. constraint (4c) is inactive, s λ becomes zero; ...
Research was conducted to evaluate parking lot choice in the context of special events. Three major factors - driving time, parking cost, and walking time - are considered as the principal components of utility associated with the choice of a parking lot. The lot choice model is derived by using the logit function, while the joint parking lot destination choice and assignment model is formulated from the concepts of user equilibrium traffic assignment and entropy maximization for trip distribution. Parking lot choices by University of Wisconsin men's basketball game attendees at the Kohl Center in Madison are used as a case study for model calibration and application. The parameter calibration was conducted both for all lots and for public and private lots separately. Parking lot choice was also analyzed by direction of approach. Two distinct assignment scenarios were evaluated by using the user equilibrium assignment methodology. The impact of the system optimal and minimum-cost assignments on total network costs was evaluated. The parking lot choice model was applied to estimate the impact of opening a new private parking lot to season permit parking.
... Allocating parking facilities to vehicles has been studied for more than 40 years, and one of the first surveys appeared in Florian and Los (1980). Although the problem of allocating parking facilities to cars is clearly combinatorial, there is no uniform mathematical programming (MP) model for it. ...
Cities suffer from high traffic c ongestion of which one of the main causes is the unorganized pursuit for available parking. Apart from traffic congestion, the blind search for a parking slot causes financial and environmental losses. We consider a general parking allocation scenario in which the GPS data of a set of vehicles, such as the current locations and destinations of the vehicles, are available to a central agency which will guide the vehicles toward a designated parking lot, instead of the entered destination. In its natural form, the parking allocation problem is dynamic, i.e., its input is continuously updated. Therefore, standard static allocation and assignment rules do not apply in this case. In this paper, we propose a framework capable of tackling these real-time updates. From a methodological point of view, solving the dynamic version of the parking allocation problem represents a quantum leap compared with solving the static version. We achieve this goal by solving a sequence of 0-1 programming models over the planning horizon, and we develop several parking policies. The proposed policies are empirically compared on real data gathered from three European cities: Belgrade, Luxembourg, and Lyon. The results show that our framework is scalable and can improve the quality of the allocation, in particular when parking capacities are low.
... Both of the above studies take into account the parking lot capacity explicitly but the trip makers' behaviour has not been accounted aptly due to extreme point solutions in the model. A model based on entropy maximization methodology has been developed by (Florian and Los, 1980) which can measure the impact of alterations in parking policies such as supply of parking space, addition or suppression in parking lots, change in parking fees -on parking lot choice. (Asakura and Kashiwadani, 1994) identified effect of parking availability information system on a driver's choice behaviour for parking space. ...
In modern era, population and economic growth as well as increasing living standard of people are to blame for the rising number of private vehicles in the cities. With increasing rate of private car usage in the urban areas as a result of fast-growing economy, derelict policies and subsidies, car parking became one of the main concerns for transport and traffic management all over the world. The need for parking space is directly in nexus of demand associated with the upsurge in the vehicle plying on the roads. Hence, at planning and development stage, it is must to address the infrastructural and sometimes technological demands which has limited resources to supply. It is necessary to understand the parking behaviour and actual demand of parking space for particular area. Due to increasing parking demand, the overall parking capacity cannot satisfy it which creates problems having noticeable impact on traffic congestion. As noted by De Cerreño (2004), parking is one of the critical elements in forming transportation policy and management of traffic in large cities. Indeed, he found that many cities lack basic information about their parking resources. So, it becomes necessary to study the parking behavior and performance of existing facility in the direction of making a firm policy for parking. At strategic level of planning, it is important to evaluate the existing parking facilities to develop LOS in order to better future plan and operation.
To comprehend the above objectives, Delhi-NCR was selected as study area and data was collected for 16 different parking lots for three different land-uses using different parking surveys and questionnaire survey. After carrying out preliminary analysis, parking behavioral model has been developed using artificial intelligence technique like artificial neural networks. This new modelling methodology stems from its apparent relevance to problems requiring large scale, high dimensional data analysis such as parking and travel behavior. The approach of neural networks is non-parametric and capable of identifying complex relationship between dependent and independent variable. The importance of each parameters has been evaluated using partition of weights algorithm. The results show high R-squared value indicating good fitting and lower mean squared error (MSE) showing better applicability of adopted methodology.
Moreover, the study was also focused on developing a methodology which can efficiently evaluate the parking system performance based on the score assignment. Six key criteria namely, parking charge, occupancy, ease time, walk time, management level and sufficiency of capacity have been selected for evaluation. In this study, a multi-criteria decision-making tool, analytical hierarchy process (AHP) and clustering technique have been used to define the ranges for five categories of level of service (LOS)- A, B, C, D and E. AHP experts survey has been carried out and weights (importance) of each parameter has been found out to realistically assign the score to each ranges of each parameter based on their importance. The developed methodology can be used for any parking facility located in similar kind of study area. In addition, the fuzzy technique has been approached to simulate the human brain in evaluating any facility. The fuzzy evaluation matrix has been developed based on the selected parking parameters and pre-defined cluster-based evaluation criteria. The evaluation model can help us to understand the current situation of parking lots, and to provide advices to urban traffic managers on the improvement of parking lots. Moreover, it also assists drivers to choose appropriate parking lots.
... Both above studies considered the parking lot capacity explicitly, but the trip makers' behaviour has not been accounted aptly due to extreme point solutions in the model. A model based on entropy maximization methodology has been developed by Florian and Los (1980), which can measure the impact of alterations in parking policies, such as supply of parking space, addition or suppression in parking lots, change in parking fees, on parking lot choice. Asakura and Kashiwadani (1994) identified the effect of parking availability information system on a driver's choice behaviour for parking space. ...
The increasing rate of private car usage in the urban areas as a result of fast-growing economy, derelict policies and subsidies are the main causes making car parking one of the main concerns for transport and traffic management all over the world. The coordination between parking policies and traffic management revealed how parking is becoming a barrier to the through-traffic operation. Also, it is responsible for the inefficient use of available resources, even the decisions are made on an ad-hoc basis while making policy. Hence, it is necessary to understand the parking choice behaviour and actual demand of parking space. In the last three decades, ample studies have been done to evaluate parking characteristics, to estimate the demand for parking and on driver’s behaviour while choosing the parking space. This paper integrates all these aspects and presents the state-of-the-art review of models and studies on the parking system. Problems related to and due to the parking, various parking characteristics and their applications, parking choice behaviour of drivers, development of demand models considering various factors and review of parking policies as an integral part of the urban transport system are discussed in detail. Whilst underdeveloped, authors found the literatures suggest that greater attention should be given to metrics like ease of access, walk time, parking charges, parking guidance and information system, management, etc., at all stages of planning and policy formulation. Taken together, mentioned studies demonstrate useful information concerning the entire parking system. It also provides useful information to the planners and policy makers for planning, designing and evaluating parking system.
... Hossinger and others [11] developed a real-time occupancy model of short-term parking zones. Florian and others [8] presented a model for predicting parking occupation. ...
In China, more and more families own cars, and parking is also undergoing a revolution from manual to automatic charging. In the process of parking revolution, understanding parking behavior and making an effective prediction is important for parking companies and municipal policymakers.
... The model is trained through data from 344 interviews in the CBD of Edmonton, Canada. Finally, a similar model for parking choice is formulated in Florian and Los (1980) . The aim is to predict the occupation of a number of park 'n ride lots co-located with stations of a commuters' rail transit line in Philadelphia, US. ...
The search for parking space in busy urban districts is one of those routine human activities that are expected to benefit from the widespread adoption of pervasive sensing and radio communication technologies. Proposed parking assistance solutions combine sensors, either as part of fixed infrastructure or onboard vehicles, wireless networking technologies and mobile social applications running on smartphones to collect, share and present to drivers real-time information about parking demand and availability.
One question that arises is how does (and should) the driver actually use such information to take parking decisions, e.g., whether to search for on-street parking space or drive to a parking lot and, in the latter case, which one. The paper is, hence, a performance analysis study that seeks to capture the highly behavioral and heuristic dimension of drivers’ decisions and its impact on the efficiency of the parking search process. To this end, and in sharp contrast with the existing literature, we model drivers as agents of bounded rationality and assume that their choices are directed by lexicographic heuristics, an instance of the fast and frugal heuristics developed in behavioral sciences such as psychology and biology. We analyze the performance of the search process under these heuristics and compare it against the predictions of normative game-theoretic models that assume fully rational strategically acting agents. We derive conditions under which the game-theoretic norms turn out to be more pessimistic than the simpler heuristic choice rules and show that these are fulfilled for a broad range of scenarios concerning the fees charged for the parking resources and their distance from the destinations of the drivers’ trips. The practical implications of these results for parking assistance solutions are identified and thoroughly discussed.
... Nevertheless, mobility, as a central factor in the liveability of urban milieus, has produced for transporting of people and goods a pressure on the environment which is not compatible with the sustainability of anthropogenic flows (Bettini, 1990; Chen & Graedel, 2012). Urban mobility presents some types of problems contrary to each other that the city should be able to resolve in order to ensure a high level of standard of living: a multi-directional mobility (Fuckan & Petrov, 2006), i.e. centrifugal and centripetal which are alternative for spaces (Florian & Los, 1980) and containers or simultaneous for times/schedules (Bettini, 2004). So that it is difficult if not impossible to answer in a satisfactory way, but almost never optimizing, to the relevant requirements of moving through the existing road infrastructure and public transport networks, local road. ...
This paper surveys the most recent advances in the context of decisional processing, with an emphasis on the parking behavior in entropic setting, including the measures and the necessary mechanisms for the interaction of the actors-players, and their connection to decisional processing theory. During the last years of research in this field a number of major techniques have emerged. The aim of this article is to provide a critical review of the most fashionable models and methods in parking lot financial design: the first class of methods covers the approach of analysis with the random entropic model; the second class of methods is the decisional processing through rational choise models as rational individual evaluations, for a best feasible solution for parking lot economic and financial design. Thus, each section of the article concentrates on one technique; we illustrate it using the well-known and easy multimodal problem approach starting from entropic scenario, and then we present advanced applications: Because of a close equivalence between the aggregate approach of entropy maximization and disaggregated microeconomic approach of discrete choice models based on random utility theory, we try to provide a critical approach of it, through rational choise models. Keyword: urban entropic parking lot – discrete choice models-decision making models JEL code: R4-R11-R41-R48
... With respect to parking supply, we introduce two sets of constraints which provide a more realistic model: (i) parking occupancy cannot exceed the capacity of parking lots; let us call it parking capacity constraint (PCC); (ii) some parking spaces may have been assigned to serve specific demand such as VIP parking space, parking permits, different parking duration (short term, long terms), disabled parking, and private parking lots; let us call this category of constraints parking rationing constraint (PRC). Some studies have addressed the former constraint (PCC) [8,[10][11][12][13][14][15][16][17]. Considering the latter PRC constraint in the presence of the PCC constraint is a unique feature of this study. ...
Different types of drivers and parking spaces delineate a heterogeneous parking market for which the literature has yet to provide a model applicable to the real world. The main obstacle is computational complexities of considering various parking restrictions along with traffic congestion on the road network. In this study, the heterogeneity aspects are considered within a Logit parking choice model. A mathematical programming problem was introduced to explicitly consider parking capacities and parking rationing constraints. The parking rationing is defined as any arrangement to reserve parking space for some specific demand such as parking permit, private parking, VIP parking, and different parking durations. Introduction of parking rationing in the presence of other constraints is a unique factor in this study which makes the model more realistic. The algorithm was tested on a central business district case study. The results prove that the algorithm is able to converge rapidly. Among the algorithm’s output are shadow prices of the parking capacity and parking rationing constraints. The shadow prices contain important information which is key to addressing a variety of parking issues, such as the location of parking shortages, identification of fair parking charges, viability of parking permits, and the size of reserved parking.
... (2) the probability based approach (Wong et al., 2000;Dell' Orco et al., 2003); and (3) the network based approach (Florian and Los, 1980;Bifulco, 1993;. However, these studies mainly focus on time-stationary (static) equilibrium analysis, and little attention has been paid to time-dependent analysis. ...
Transportation and Traffic Theory (ISTTT16)
... In one of the earliest studies, Florian and Los (1980) studied the impact of parking supply for 1 park and ride on overall transportation system performance. They considered the interaction 2 between demand and supply using maximum entropy formulations and the explicit consideration 3 of the capacity constraints on parking spaces. ...
The objective of this study was to investigate the effect of increasing parking charges at park-and-ride stations on mode choice for current park-and-ride users. To address this objective, a stated preference (SP) survey was designed to study commuters' willingness to pay for parking at park-and-ride transit stations. The SP survey was conducted at the 14 busiest park-and-ride transit stations in Greater Vancouver in British Columbia, Canada. The survey data were then used to model mode choice for longer-distance commuting trips by considering three major options: automobile all-way, transit all-way, and park-and-ride. A heteroscedastic multinomial logit model for stated preference of modal choices was estimated. The model included several major factors that were found to influence mode choice at park-and-ride stations. The estimated model parameters were then used to investigate direct and cross elasticities of parking charges at park-and-ride stations to mode choices. The model results show that an increase in parking charges at park-and-ride stations is more likely to divert current park-and-ride users to the transit all-way option compared with the private car all-way option.
... Here we highlight a few examples. Florian and Los (1980) proposed an entropy maximization-based model for predicting parking occupation in a park-and-ride network. Parking capacity was explicitly considered as a side constraint in their model. ...
In many countries across the world, fossil fuels, especially petroleum, are the largest energy source for powering the socio-economic system, and the transportation sector dominates the consumption of petroleum in these societies. As the petroleum price continuously climbs and the threat of global climate changes becomes more evident, the world is now facing critical challenges in reducing petroleum consumption and exploiting alternative energy sources. A massive adoption of plug-in electric vehicles (PEVs), especially battery electric vehicles (BEVs), offers a very promising approach to changing the current energy consumption structure and diminishing greenhouse gas emissions and other pollutants. Understanding how individual electric vehicle drivers behave subject to the technological restrictions and infrastructure availability and estimating the resulting aggregate supply–demand effects on urban transportation systems is not only critical to transportation infrastructure development, but also has determinant implications in environmental and energy policy enactment. This paper presents an equilibrium-based analytical tool for quantifying travel choice patterns in urban transportation networks with both gasoline and electric vehicular flows. Specifically, a network equilibrium problem with combined destination, route and parking choices subject to the driving range limit and alternative travel cost composition associated with BEVs are formulated, solved, and numerically analyzed under different network settings and scenarios. The defined problem introduces a new dimension of modeling network equilibrium problems with side constraints. The practical significance of the developed tool lies in its solution tractability and extension capability and its ease of being embedded into the existing urban travel demand forecasting framework.
... Goyal and Gomes 1984;Tsukaguchi and Jung 1989), distribution models (e.g. Ellis and Rassam 1970;Florian and Los 1980;Young, et al. 1991) and assignment models (e.g. Nour Eldin et al. 1981;Gur and Beimborn 1984). ...
This paper proposes two types of parking choice models, a static game theoretic model and a dynamic neo-additive capacity model, to capture the competition among drivers for limited desirable parking spaces. The static game assumes that drives make decisions simultaneously and with perfect knowledge about the characteristics of the parking system and the strategies of their fellow drivers in the system; the model thus captures only the rational aspect of parking choice behavior and pays no attention to modeling individual drivers’ psychological characteristics. The dynamic model, on the other hand, considers individual drivers’ psychological characteristics under uncertainty (i.e. optimistic and pessimistic attitudes) and thus captures the impacts of the irrational side of parking behavior in addition to the rational aspect. Following the formulation of the two models, they are both used to predict parking behavior as observed on a set of parking lots on the University at Buffalo north campus. Specifically for the dynamic model, the model is first calibrated based on real data collected from video recorded observations for a pair of parking lots, and then used to predict behavior on another pair. Validation results show higher predictive accuracy for the dynamic neo-additive capacity model compared to the static game theoretic model. This in turn suggests that the psychological characteristics of drivers play an important role in the parking lot choice decision process, and points to the potential for parking information systems to eliminate the unnecessary additional traffic generated by the parking search process.
With the significant increase of e-commerce, freight transportation demand has surged significantly over the past decade. Most of the demand has been served by trucks in the United States. One major problem commonly identified across the country is the worsening truck parking availability because the increase of truck parking facilities has lagged behind the growth of trucking activities. The lack of parking spaces and real-time parking availability information greatly exacerbate the uncertainty of trips, and often results in illegal and potentially dangerous parking or overtime driving. This paper elaborates on pilot research on improving truck parking facilities cooperated with the Washington State Department of Transportation (WSDOT), building and testing the advanced Truck Parking Information and Management System (TPIMS) with the real-time user visualization and prediction function empowered by artificial intelligence. Furthermore, by analyzing the activities of truck drivers, the researchers aggregated the regularity of truck parking patterns by a customized sequential similarity methodology. A Truck Parking Occupancy Prediction (TPOP) neural network for time-variant occupancy prediction by deep learning and attributes embedding is proposed and integrated into the TPIMS. The TPOP achieves 5.82%, 5.07%, 4.84%, and 4.19% mean average percentage error (MAPE) for 16, 8, 4, and 2 minutes ahead of occupancy prediction respectively, significantly outperforms other state-of-the-art methods. Clearly, the proposed solutions can benefit both the truck drivers and government agencies by a more efficient and smart TPIMS.
The digitalization process is essential for the competitiveness of companies. For this reason, the application of the concept of Internet of Things (IoT) technology and telematics has led to Industry 4.0 in logistics. Thanks to IoT and telematics systems, data and information in transport and logistics are sent and received in real time thus enabling vehicle and other systems to be fully monitored. To this end, various applications based on telematics and IoT are being developed to optimize and support logistics processes. Volkswagen Truck & Bus GmbH, in cooperation with MAN, has produced a cloud-based RIO platform, the basic task of which is to integrate digital applications and provide data from a complete logistics system. The RIO platform enables the connection and networking of all participants in logistics and transport systems. The aim of this paper is to present impact of IoT, telematics and
Industry 4,0 on logistics and supply chain management with applications based on cloud. We present the RIO platform and its support to transport companies. In addition to a detailed description of applications, the paper also presents the implementation of certain applications on the transport vehicles with the aim of logistical support and the possibility of optimizing logistics and business processes.
As the sharing economy is booming in China, many intelligent shared parking lots appear. Since more and more Chinese households own cars, it is necessary to study the payment behavior of shared parking lots, which may represent the entire sharing economy. In detail, we analyze the factors that influence users’ payment and predict users’ payment behavior of whether and when users will deliver parking bills after parking. We use 29,733 real parking records provided by Huaching Tech, a top smart parking company in China, in our study. After a comprehensive statistical analysis, we use decision tree model to predict users’ payment behavior. Experiments show that the decision tree model can reach 79% accuracy.
As the sharing economy is booming in China, many intelligent shared parking lots appear. Since more and more Chinese households own cars, it is necessary to study the payment behavior of shared parking lots, which may represent the entire sharing economy. In detail, we analyze the factors that influence users' payment and predict users' payment behavior of whether and when users will deliver parking bills after parking. We use 29,733 real parking records provided by Huach-ing Tech, a top smart parking company in China, in our study. After a comprehensive statistical analysis, we use decision tree model to predict users' payment behavior. Experiments show that the decision tree model can reach 79% accuracy.
Objectives:To estimate the on-street parking demand in the urban Central Business Districts (CBDs). Methods/Statistical Analysis: To achieve the goal, the study formulates two parking demand estimation models i.e., the fee index (FI) model and the cost factor (CF) model, based on regression analysis using SPSSStatistical Package for the Social Science. FI Model estimates the on-street parking demand where the transit system is absent. On the other hand CF model estimates the demand by considering the mode shift from the private vehicle (PV) users to the public transit (PT). Findings: Priority wise requirements for selecting PT are found out in this survey. The existing demand in the both selected CBDs of Kolkata, viz. Dalhousie and Gariahat is found to be much higher than the present parking supply. FI Model shows that, the demand will satisfy the existing supply if unit FI can be achieved. CF model explain that, the transit fare need to be increased by 52% and 26% for Dalhousie and Gariahat area respectively to meet the demand with the existing supply. It is also found out that, the on-street demand is less in transit oriented CBDs. The forecasted demand is reduced by 69% and 71% and by 63% and 59% than the present demand using CF model and the FI model respectively. In this study, it has been attempted to evaluate the on-street parking demand and such type of works has not been found out by the authors particularly in India which make it a pioneer study for others. Application/Improvements: The users need to be shifted from PV to PT immediately and the government must take necessary actions to introduce sufficient transit service to counter the on-street parking problem.
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Based on travelers via road, the trip distribution and traffic assignment model was developed for planned special events parking. Logit-based utility model was employed to present travelers' parking choice behavior, which taking into account driving time, parking fees, bus costs, bus time and walk time as main factors. By transferring link cost between parking and stadium to parking attraction, the single destination network became a multi destination network. The equivalent mathematical programming model was developed to describe the equilibrium assignment, and its equivalence was proved. The experiment indicates the proposed model can describe road travelers' parking behavior.
The spatial structure of parking behavior is analyzed and a basic parking behavior model is established to represent the parking problem in downtown. In addition, a parking pricing model is set up to analyze the parking equilibrium with a positive parking fee. Employing a paired combinatorial logit model, the effect of parking integrative cost on parking behavior is analysed. It is concluded from empirical results that the parking behavior model performs well.
Based on an available parking space occupancy (APSO) survey conducted in Nanjing, China, an APSO forecasting model is proposed. The APSO survey results indicate that the time series of APSO with different time-sections are periodical and self-similar, and the fluctuation of the APSO increases with the decrease in time-sections. Taking the short-time change behavior into account, an APSO forecasting model combined wavelet analysis and a weighted Markov chain is presented. In this model, an original APSO time series is first decomposed by wavelet analysis, and the results include low frequency signals representing the basic trends of APSO and several high frequency signals representing disturbances of the APSO. Then different Markov models are used to forecast the changes of low and high frequency signals, respectively. Finally, integrating the predicted results induces the final forecasted APSO. A case study verifies the applicability of the proposed model. The comparisons between measured and forecasted results show that the model is a competent model and its accuracy relies on real-time update of the APSO database.
The paper provides a novel network model of parking and route choice. Parking supply is represented by parking type, management strategy including the fare, capacity and occupancy rate of parking lot, and network location, in relation to access routes along the roadway network. Trip demand is segmented according to origin–destination pair, the disposal of private parking facilities and the individual preferences for parking quality of service. Each traveller is assumed to make a two stage choice of, first, network route on the basis of the expected cost of route and parking and, second, local diversion on the basis of a discrete choice model. Search circuits are explicitly considered on the basis of the success probability to get a slot at a given lot and of the transition probabilities between lots in case of failure.
The basic endogenous model variables are the route flows, the lot success probabilities and the transition probabilities between lots. These give rise to the cost of a travel route up to a target lot and to the expected cost of search and park from that lot to the destination. Traffic equilibrium is defined in a static setting. It is characterized by a mixed problem of variational inequality and fixed point. Equilibrium is shown to exist under mild conditions and a Method of Successive Averages is put forward to solve for it. Lastly, a planning instance is given to illustrate the effects of insufficient parking capacity on travel costs and network flows.
It can be expected, recently, that the traffic congestion grows worse because the 48% of passenger cars are concentrated in the metropolitan area. However, there is an enforcement regulation that must limit onsite parking lot establishment in some downtown, so it is forecasted that parking lot supply is insufficient. Therefore, this study concentrate upon the subject that solves the problem which drivers are difficult to find parking lots because of increasing demand for parking. This study includes the concept about walking distance because the choice of parking lots is happened within walking distance. The algorithm of this study applies to toy-network, and then this study analyze the result of toy-network. It is proper to consider user's preference because the patterns of choice are different. Moreover, this study suggests the vision that will can offer drivers more correct information by real time information sharing in course of ubiquitous age.
Car parking is an issue of significance both at the local and at the strategic level of planning. Parking policy and supply play a major role in the management of transportation systems in dense urban areas. Although the policies that govern the provision and operation of parking facilities are recognized to have an important bearing on the operation of urban transport systems, decisions have often been made on an ad hoc basis, without proper integration with other elements of transport systems analysis. In order for parking policy decisions to be well founded, the analysis of parking behaviour and the effects of parking policies should be fully integrated with the other elements of the transport planning and modelling process. To assist this interaction this paper presents a state‐of‐the‐art review of models of parking as an integral component of urban transport systems. The paper develops model groupings by relating their main objectives: choice, allocation and interaction models. It then discusses the relationship between these structures pointing to a hierarchical suite of models for parking analysis. Models at each level in the hierarchy can be directed at particular policy questions. Taken together as a linked system they can provide a realistic and comprehensive representation of the entire parking system for an area. The hierarchical approach allows the advantages of each model type to be tailored to particular policy scenarios. Les problèmes de stationnement sont très sérieux, tant au plan local que stratégique. La politique de stationnement et celle de l'offre jouent un rôle majeur dans la politique de transport des zones urbaines denses. Certes, les organismes concernés ont conscience de l'incidence des décisions en la matière sur le fonctionnement général des transports urbains; mais, dans le pratique, les décisions sont souvent prises au jour le jour, sans tenir compte des autres aspects du système de transport, comme celà devrait être le cas. C'est pour une meilleure prise en compte de ces interactions que cet article fait le point des modèles disponibles qui font du stationnement un composant à part entière du système de transport. Il classe les modèles en fonction de leur objectif principal et de leur structure, et met en évidence une suite hiérarchique de modèles du point de vue de l'étude du stationnement. De cette façon, chaque modèle, au niveau hiérarchique qui est le sien, peut être situé par rapport à un choix politique particulier. Pris tous ensemble comme un système organisé, ils peuvent offrir une vue globale et réaliste de l'ensemble des capacités de stationnement d'une zone donnée. L'approche hiérarchisée permet d'utiliser au mieux les avantages spécifiques de chaque modèle en fonction de politiques particulières. Der ruhence Verkehr ist sowohl in räumlicher wie strategischer Hinsicht von hoher Bedeutung für die Planung. Die Stellplatzpolitik und das Angebot spielen eine bedeutende Rolle im Verkehrssystem‐Management in dichten städtischen Bereichen. Obwohl bekannt ist, daß Maßnahmen, die die Versorgung mit und den Betrieb von Stellplätzen bestimmen, einen bedeutenden Einfluß auf den Betrieb des gesamten städtischen Verkehrssystems haben, wurden Entscheidungen oft ad‐hoc getroffen, ohne bei dieser Analyse die übrigen Elemente des Verkehrssystems einzubeziehen. Um Entscheidungen über Stellplatzmaßnahmen auf solider Basis treffen zu können, muß die Analyse des Parkverhaltens und der Wirkungen von Maßnahmen im ruhenden Verkehr umfassend in die übrigen Elemente des Prozesses der Verkehrsplanung und Verkehrsmodellierung einbezogen werden. Um diese Verknüpfung zu unterstützen, stellt dieser Aufsatz den Stand des Wissens über Modelle des ruhenden Verkehrs als eine Komponente des städtischen Verkehrssystems zusammen. Der Artikel entwickelt Modellkategorisierungen in Zusammenhang mit ihren Hauptaufgaben: Wahl‐, Allokations‐ und Interaktionsmodelle. Der Artikel erörtert darauf die Abhängigkeiten zwischen diesen Gliederungen, die auf eine hierarchische Folge von Modellen zur Analyse des ruhenden Verkehrs führt. Modelle auf jeder Stufe dieser Hierarchie können für spezielle Fragestellungen der Politik eingesetzt werden. Zusammengenommen können sie als ein verknüpftes System eine realistische und verständliche Darstellung des gesamten Systems des ruhenden Verkehrs für ein Gebiet geben. Der hierarchische Ansatz erlaubt es, die Vorteile jedes einzelnen Modells gezielt für spezielle Politik‐Scenarien einzusetzen. El estacionamiento de automóviles es un elemento significativo de planificación, tanto a nivel local como estratégico. La política y oferta de estacionamientos juegan un rol importante en la gestión de sistemas de transporte de áreas urbanas densas. Aunque se reconoce que las políticas que gobiernan la provisión y operación de fatilidades de estacionamiento tienen un efecto importante en la operación de los sistemas de transporte urbano, las decisiones en este sentido se toman normalmente de manera ad‐hoc, sin una adecuada integración con otros elementos de análisis de sistemas de transporte. A fin de que las decisiones sobre política de estacionamiento tengan una buena fundamentación, el análisis del comportamiento respecto a estacionamiento y de los efectos de determinadas políticas de estacionamiento, debieran estar totalmente integradas con otros elementos del proceso de planificación y modelación de transporte. Para apoyar esta interacción, este trabajo presenta una revisión del estado del arte en la modelación de estacionamiento como componente integral del sistema de transporte urbano. En base a relacionar sus objetivos fundamentales, se desarrollan agrupaciones de modelos: de elección, de asignación y de interacción. Luego se discute la relación entre estas estructuras, en un intento de definir una sinfonía jerárquica de modelos para el análisis de estacionamiento. Los modelos en cada nivel jerárquico pueden ser utilizados para estudiar determinadas interrogantes de política. En conjunto, como sistema interconectado, pueden permitir una representación realista y completa de todo el sistema de estacionamiento de un área. Este enfoque jerárquico permite aprovechar al máximo las ventajas de cada tipo de modelo en diferentes escenarios de política.
The aim of this article is to give a semi-technical and somewhat journalistic account of the contributions to the methods used for quantitative transportation planning by professors, researchers and graduate students who have been active at the Centre for Research on Transportation (CRT) of the University of Montreal since its inception.
The purpose of this paper is to show the possibility of a co-existence of public and private parking management systems even when all the parking spaces are owned by the government. This study focuses on the issue of collecting parking fees by a private firm that has been used by some local governments in Taiwan. We assume that the government behaves as a leader and a private firm as a follower in a Stackelberg three-stage game. At stage 1, the government selects its parking space. At stage 2, the government and the firm set their parking fees simultaneously. At the final stage, consumers (drivers) choose the parking lot between the space of the government and that of the firm by considering the full costs, consisting of the parking fee and the searching (with congestion) time cost. The objective of the government is to maximize welfare and that of the firm is to maximize profit. The model is constructed at first and a simulation analysis is then made. The result supports the strategy of adopting the franchise of collecting parking fees if the private firm is more efficient than the government. Moreover, the government may keep fewer parking spaces and release more parking spaces to the firm under the goal of maximizing welfare.
This paper proposes a time-dependent network equilibrium model that simultaneously considers a traveler’s choice of departure time, route, parking location and parking duration in road networks with multiple user classes and multiple parking facilities. In the proposed model, travelers are differentiated by their trip purpose and parking duration, parking locations are characterized by facility type and parking charge, and the decision-making process of travelers on travel and parking choices is assumed to follow a hierarchical choice structure. The model is formulated as a variational inequality problem, and is solved by a heuristic solution algorithm. Numerical results for two example networks are presented to show the solution quality and investigate the solution sensitivities to some input data. It is found that parking behavior is significantly affected by travel demand, walking distance, parking capacity, and parking charge. The proposed model provides a useful tool for studying the complex temporal and spatial interaction between road traffic and parking congestion, and can be used to assess the effects of various parking policies and infrastructure improvements at a strategic level.
This paper presents an integrated conceptual framework for the description of the components and interactions of transportation systems. The abstraction presented makes use of the notions of procedures (mappings) and steady-state equilibria. Key elements of the conceptual framework include demand, performance and supply actions procedures. Combinations of the procedures are used to present the distinct but interrelated concepts of demand-performance, demand-performance-supply and demand- supply equilibria.
Parking plays an important role in urban transport systems. However, there is currently a lack of understanding of how motorists choose car parks. This paper presents a model that represents the parking search behaviour of motorists. A search process was defined within a behavioural modelling framework and subsequently represented using analytical procedures. Relationships for estimating the utility of a car park incorporating access, waiting, direct and egress cost components were developed. Parameters were specified to represent the uncertain attributes of car parks, including queue sizes and departure rates. The size and composition of the choice sets of individual motorists were determined endogenously by the model. Searchers' perceptions of car park attributes based on their observations from previous and current searching experiences were represented. Applications of the model showed that long term experience does not necessarily lead to better choices. The effects of reducing duration limits were also investigated.
We develop in this paper a trip distribution, modal split and trip assignment model. As is well known, the entropy type distribution model is equivalent to postulating a travel demand function where trips are proportional to a negative exponential function of the travel cost. We show that when two distribution models of this type are linked with route choice models based on Wardrop's “user optimized” principle, the mode choice is given by a logit model. We develop a solution algorithm that computes the resulting trip interchanges and route flows.
An application of an equilibrium trip assignment method to the 1970 road network of the City of Winnipeg, Manitoba, Canada is described. The validity of the method is discussed in detail. The results presented show that the differences between predicted and observed values of the relevant parameter are attributable in part to limitations of the model to explain all route choice behavior as a function of time alone and in part to the way in which observed temporal values relate to predictions made by a static model.
In the practice of transportation planning the distribution and assignment computations are treated sequentially as independent problems, although ideally they should be solved simultaneously. A case has been made by many practitioners for repeating the distribution and assignment computations in order to obtain more consistent results. An approach to solving the distribution and assignment problem simultaneously and relate it to other methods that were proposed for this problem is developed. A numerical example illustrates the conclusions drawn.
This paper presents an in-depth computational comparison of the basic solution algorithms for solving transportation problems. The comparison is performed using “state of the art” computer codes for the dual simplex transportation method, the out-of-kilter method, and the primal simplex transportation method (often referred to as the Row-Column Sum Method or M O D I method). In addition, these codes are compared against a state of the art large scale LP code, O P H E L I E/LP.
The study discloses that the most efficient solution procedure arises by coupling a primal transportation algorithm (embodying recently developed methods for accelerating the determination of basis trees and dual evaluators) with a version of the Row Minimum start rule and a “modified row first negative evaluator” rule. The resulting method has been found to be at least 100 times faster than OPHELIE, and 9 times faster than a streamlined version of the SHARE out-of-kilter code. The method's median solution time for solving 1000 × 1000 transportation problems on a CDC 6600 computer is 17 seconds with a range of 14 to 22 seconds.
Some of the unique characteristics of this study are (1) all of the fundamental solution techniques are tested on the same machine and the same problems, (2) a broad spectrum of problem sizes are examined, varying from 10 × 10 to 1000 × 1000; (3) a broad profile of nondense problems are examined ranging from 100 percent to 1 percent dense; and (4) additional tests using the best of the codes have been made on three other machines (IBM 360/65, UNIVAC 1108, and CDC 6400), providing surprising insights into conclusions based on comparing times on different machines and compilers.
In this paper we address the methodology of the equilibrium traffic assignment on congested networks. The paper presents a unified approach to a class of iterative solution procedures within a general mathematical programming framework. A preliminary comparative analysis of three basic algorithms for the equilibrium traffic assignment is reported.
Using two independent data sets, alternative binary station choice models were successfully calibrated and tested. The regression and probit models are based on a two stage decision process: first the commuter selects his mode of travel, and then, given the use of rapid transit, he chooses a station. The station choice models focus on the second stage of the decision process. The models estimate the relative frequency a station will be selected by commuters from a Census block group, given a modal choice of rapid transit. This proportion is a function of the trip cost difference between that station and the next least cost station.
A gravity model for trip distribution describes the number of trips between two zones as a product of three factors; one is associated with the zone in which a trip begins, one with the zone in which it ends and the third with the separation between the zones. The separation or deterrence factor is usually a decreasing function of the generalized cost of travelling between the zones, where generalized cost is usually some combination of the time of travel, the distance travelled and the actual monetary costs. If the deterrence factor is of the exponential form exp (-αc) and if the total numbers of origins and destinations in each zone are known, then the resulting trip matrix depends solely on α. In this paper it is shown that as α tends to infinity, this trip matrix tends to a limit in which the total cost of trips is the least possible allowed by the given origin and destination totals. That is to say the limit is a cost-minimizing solution to the linear programming transportation problem having the same origin and destination totals. If this transportation problem has many cost-minimizing solutions then it is shown that the limit is one particular solution in which each non-zero flow from an origin i to a destination j is of the form risj. A numerical example is given.
This paper compares the practical considerations in implementing different techniques for calibrating doubly constrained gravity type models with an exponential cost function. The comparisons are carried out under the headings of speed, accuracy, computer storage required and ease of implementation. Three techniques, due to Hyman, Evans and Hathaway, respectively, are initially considered. Various modifications and improvements to these methods are suggested and the most efficient versions of each are compared. A modified form of the method due to Hyman is found to be the fastest and most accurate for most practical situations and is recommended for general use.
For the unique determination of the parameters in the doubly constrained gravity model with exponential friction function two approaches are common: (1) entropy maximization and (2) application of a travel cost budget. This paper shows by making use of geometric programming that both of these approaches are equivalent with another natural criterion: the minimization of the deviation between the observed [t1j] and the estimated [x1j] table for a base year. By means of calculating the derivative of total cost as a function of σ the construction of an efficient algorithm for estimation of σ is made possible.
This paper discusses a simultaneous model of transport mode choice and optimal parking location for the auto mode. In developing this model, four extensions of disaggregate choice theory are made that should be useful in other applications. These extensions are: (1) the formulation of an econometric model that allows for continous endogenous attributes in discrete choice decisions; (2) the use of an econometric estimation technique that is implementable using existing computer programs; (3) the development of an explicit reduced form expansion path cost model of location decisions; and (4) the extension of aggregation procedures to predict both transit demand and the spatial distribution of parking.
Methods are described and results presented for greatly reducing the computation time for long narrow problems of the transportation problem of linear programming. The code builds on known methods with two principal innovations: a substantial reduction in the size of the tree representation of shipments, and a set of methods for calculating improved starting solutions.
Thesis (Ph. D.)--University of Pennsylvania. Includes bibliographical references (leaves xix-xx). Photocopy. Ann Arbor, Mich. : University of Microfilms, 1973. 21cm.
Typescript. Vita: leaf 143. Thesis(PhD)--Northwestern University, 1973. Bibliography: leaves 137-139. Photocopy.
This paper examines a variety of issues within the context of two main themes: the formation of travel demand models and economic evaluation measures which are mutually consistent within a theory of rational choice; and a consideration of the structure of models which are representations of the trip decision process over several dimensions: location, mode, and route. Random utility theory is invoked to explore both the role and properties of composite costs or index prices in the ‘recursive’ approach to the structuring of travel choice models, and their significance in the economic evaluation problem. It is shown that the specification of these costs must be made very precisely, with respect to the demand model form chosen, in order to retain the underlying assumption that the traveller is an optimal decisionmaker. It is argued that the structure of ‘simultaneous’ models currently in use is inconsistent with the form of utility function assumed to generate those models. Furthermore, it is shown that the ‘simultaneous’ and ‘recursive’ forms are special cases of a more general choice model structure which takes specific account of correlation or ‘commonality’ of trip attributes.
A number of applications are discussed in which consistent demand models and perceived user benefit measures are constructed. These include the formation of strategic transport planning models and of models for mixed-mode, multimode, and multiroute systems. The formalism allows definitive answers to be given to a number of problems of current interest in transportation planning, which have been incorrectly or incompletely treated.
We consider in this paper the problem of determining intermediate origin-destination matrices for composite mode trips that involve a trip by private car to a parking facility and the continuation of the trip to the destination either by walking or by a transit mode. The intermediate origin-destination matrices relate to each component of the composite mode trip: a matrix from the trip origins to intermediate destinations which are parking lots and a matrix from the parking lots to the final destinations. The approach that we propose to solve this problem is to modify the entropy based trip distribution models to consider inequality constraints related to parking lot capacities. Such models may be easily calibrated by using well known calibration methods or generalization of these methods and may be easily solved by applying a primal feasible direction method of nonlinear programming.
Impact of suburban rapid transit station location, fare and parking availability on users' station choice behavior
- Boyce
Effects of changes in parking prices and parking restrictions in urban transport demands and congestion levels
- Gillen
Parking location and transit demand: a case study of endogenous attributes in disaggregate mode choice models
- Westin
Use of linear programming to evaluate alternative parking sites
- Whitlock