In classical traffic flow theory, there are two velocities associated with a given level of traffic flow. Following Vickrey, economists have termed travel at the higher speed congested travel and at the lower speed hypercongested travel. Since the publication of Walters. classic paper, there has been an on-going debate concerning whether a steady-state hypercongested equilibrium can be stable. For a particular structural model of downtown traffic flow and parking, this paper demonstrates that a steady-state hypercongested equilibrium can be stable. Some other sensible models of traffic congestion conclude that steady-state hypercongested travel cannot be stable, and that queues develop to ration the demand in steady states. Thus, we interpret our result to imply that, when steady-state demand is so high that it cannot be rationed through congested travel, the trip price increase necessary to ration the demand may be generated either through the formation of steady-state queues or through hypercongested travel, and that which mechanism occurs depends on details of the traffic system.

The Stability of Downtown Parking and Traffic Congestion

This paper describes an equilibrium formulation for incorporating parking search into traffic network assignment models. The proposed model allows general network topologies and reflects uncertainty related to parking availability, including the possibility of cycling behavior as drivers search for parking. The equilibrium framework represents the mutual dependence between the probabilities of finding parking at different locations and the search processes employed by drivers to minimize total expected journey time (or cost). In this framework, network loading is represented by a system of nonlinear flow conservation networks, and feasibility and uniqueness issues are discussed. The equilibrium problem is formulated as a variational inequality and a convex combinations heuristic is proposed. Numerical results show that neglecting parking search can substantially underestimate network flows, and quantitatively demonstrate the relationship between parking duration effects and the cost of time spent walking relative to driving, and the expected driving and walking times.

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Parking Search Equilibrium on a Network

This paper analyzes drivers’ search behavior for parking in a stylized setting where an attraction (destination) is located on a long one-way street and on-street parking spaces are scattered around the destination; drivers are assumed to find a parking space that minimizes their walking time to the destination. Analytical models were established to describe the search outcomes and compare the impacts of parking information and reservation services. An agent-based simulation experiment was then conducted to verify the results drawn from the analytical models. Results show that, compared with the status quo, the reservation service can improve the performance of the parking system, while providing information may not. The former is proved to be a better policy than the latter for the parking competition setting and search behaviors considered in this paper.

Analysis of Advanced Management of Curbside Parking

In this paper we define and formulate the concept of parking search routes (PSR) where a driver visits a sequence of parking locations until the first vacant parking spot is found and in doing so may account for (expected) parking probabilities. From there we define and formulate the stochastic user equilibrium (SUE) traffic assignment in which no driver, by unilaterally changing its PSR, can lower its perceived expected generalized costs. Recognizing the interdependency between PSR flows, travel times and parking probabilities, we propose a queuing model in order to compute endogenous parking probabilities accounting for these factors as well as maximum admissible search times. To solve the SUE assignment with equilibrated PSR we propose a solution algorithm, including a method for PSR choice set generation. The model is implemented and applied both to a number of experimental cases to verify its properties and to a real-life setting to illustrate its usefulness in parking-related studies.

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Stochastic user equilibrium traffic assignment with equilibrated parking search routes

With the increasing popularity of smart phones, Parking Reservation System (PRS) becomes practical to reduce the travel time in cruising for vacant spaces. The aim of this study is to assess the impact of PRS explicitly. This paper was started with analyzing the processes of cruising for vacant spaces and making parking reservation decisions. The vehicles were divided into two categories: the intelligent vehicles and the regular ones. Only the intelligent vehicles have the ability to make a parking reservation beforehand, while the regular ones have to cruise for vacant spaces. All involved components were treated as different agents, including vehicles, parking lots, network, and management center. Based on this, agent-based simulation was introduced to evaluate the performances of the scenarios with different penetration rates. The simulation results indicate the average travel time increases with the improvement of the penetration rates for the regular vehicles. The assessment method presented in this study would assist in promoting the performances of PRS in urban areas.

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Agent-Based Modelling and Simulation to Assess the Impact of Parking Reservation System

A substantial amount of urban traffic is related to drivers searching for parking. This study developed an online stochastic shortest path model to represent the parking search process in which drivers must choose whether to park at an available space or continue searching for a space closer to their destination. Existing online shortest path algorithms had been formulated for the full-reset or no-reset assumptions on revisiting links. As described in this paper, neither assumption was fully suitable for the parking search process. Accordingly, this paper proposes an asymptotic reset model that generalizes the full-reset and no-reset cases and uses the concept of reset rate to characterize the temporal dependence of parking probabilities on earlier observations. In this model, drivers try to minimize their expected travel cost, which includes the driving cost and the cost of walking from a parking spot to the actual destination conditioned on the parking availability on m most recently traversed links. Th...

Reese Hatridge

Papers

Modeling Parking Search on a Network by Using Stochastic Shortest Paths with History Dependence