Macroscopic parking dynamics modeling and optimal real-time pricing considering cruising-for-parking

Gu, Ziyuan; Najmi, Ali; Saberi, Meead; Liu, Wei; Rashidi, Taha H.

doi:10.1016/j.trc.2020.102714

Cited by 56 publications

(32 citation statements)

References 60 publications

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“…is the cruising time function. This is similar to a number of parking studies in the literature (Anderson and De Palma, 2004;Calthrop and Proost, 2006;Rajagopal, 2014, 2015;Liu and Geroliminis, 2016;Arnott and Williams, 2017;Gu et al, 2020). Observe that this study models the recurrent parking sharing problem at the strategic level rather than the operational level.…”

Section: Travelerssupporting

confidence: 80%

Unlock the Sharing Economy: The Case of the Parking Sector for Recurrent Commuting Trips

Liu

Zhang

Wang

et al. 2022

Transportation Science

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This study examines the pricing strategy of a parking sharing platform that rents the daytime-usage rights of private parking spaces from parking owners and sells them to parking users. In an urban area with both shared parking and curbside parking, a choice equilibrium model is proposed to predict the number of shared parking users under any given pricing strategy of the platform. We analytically analyze how the pricing strategy of the platform (price charged on users and rent paid to parking owners or sharers) would affect the parking choice equilibrium and several system efficiency metrics. It is shown that the platform is profitable when some parking owners have a relatively small inconvenience cost from sharing their spaces, but its profit is always negative at minimum social cost. Numerical studies are conducted to illustrate the analytical results and provide further understanding.

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Section: Travelerssupporting

confidence: 80%

Unlock the Sharing Economy: The Case of the Parking Sector for Recurrent Commuting Trips

Liu

Zhang

Wang

et al. 2022

Transportation Science

Self Cite

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“…According to this formula, for φ 99%, the mean search time cannot be significantly longer than 100 T 0 , which is around one minute if spots are adjacent. This result is manifestly at odds with the empirical observation of surging search times long before φ reaches 100% (Arnott and Williams, 2017;Gu et al, 2020;Weinberger et al, 2020); in San Francisco, Weinberger et al (2020) even suggest the blocks where cruising cars eventually park might be occupied only at φ = 59%. In any event, the time to park is drastically underestimated by this approximation and ad hoc corrections to mitigate the discrepancy issue (Belloche, 2015) are devoid of theoretical ground.…”

Section: Real Search Times Elude Common Approachesmentioning

confidence: 78%

Parking search in the physical world: Calculating the search time by leveraging physical and graph theoretical methods

Dutta,

Charlottin,

Nicolas

2022

Preprint

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Parking plays a central role in transport policies and has wide-ranging consequences: While the average time spent searching for parking exceeds dozens of hours per driver every year in many Western cities, the associated cruising traffic generates major externalities. However, the laws governing the parking search time remain opaque in many regards, which hinders any general understanding of the problem and its determinants. Here, we frame the parking problem in a mathematically well posed manner which puts the focus on the role of the street network and the unequal attractiveness of parking spaces. This problem is solved in two independent ways, valid in any street network and for arbitrary behaviours of the drivers. Numerically, this is done by means of a computationally efficient and versatile agent-based model. Analytically, we leverage the machinery of Statistical Physics and Graph Theory to derive a generic mean-field relation giving the parking search time as a function of the occupancy of parking spaces; an expression for the latter is obtained in the stationary regime. We show that these theoretical results are applicable in toy networks as well as in the complex, large-scale case of the city of Lyon, France. Taken as a whole, these findings clarify the factors that directly control the search time and establish formal connections between the parking issue in realistic settings and physical problems.

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“…The first paper to consider parking issues from an economic perspective comes from Arnott and Inci [2]. Through conducting a series of parking experiments, Gu et al [24] found that occupancy information can mitigate aggregate cruising delays and a suitable price strategy can assist in vehicle management. Zheng and Geroliminis [25] developed an aggregated macroscopic method in a multimodal system with parking limitations and cruise for park flow, and they further examined the dynamic pricing adjustment policy.…”

Section: On-street Parking Issuesmentioning

confidence: 99%

Clustering Analysis of the Spatio-Temporal On-Street Parking Occupancy Data: A Case Study in Hong Kong

2022

Sustainability

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Parking plays an essential role in urban mobility systems across the globe, especially in metropolises. Hong Kong is a global financial center, international shipping hub, fast-growing tourism city, and major aviation hub, and it thus has a high demand for parking. As one of the initiatives for smart city development, the Hong Kong government has already taken action to install new on-street parking meters and release real-time parking occupancy information to the public. The data have been released for months, yet, to the best of our knowledge, there has been no study analyzing the data and identifying their unique characteristics for Hong Kong. In view of this, we examined the spatio-temporal patterns of on-street parking in Hong Kong using the data from the new meters. We integrate the t-SNE and k-means methods to simultaneously visualize and cluster the parking occupancy data. We found that the average on-street parking occupancy in Hong Kong is over 80% throughout the day, and three parking patterns are consistently identified by direct data visualization and clustering results. Additionally, the parking patterns in Hong Kong can be explained using land-use factors. Overall, this study can help the government better understand the unique characteristics of on-street parking and develop smart management strategies for Hong Kong.

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Macroscopic parking dynamics modeling and optimal real-time pricing considering cruising-for-parking

Cited by 56 publications

References 60 publications

Unlock the Sharing Economy: The Case of the Parking Sector for Recurrent Commuting Trips

Unlock the Sharing Economy: The Case of the Parking Sector for Recurrent Commuting Trips

Parking search in the physical world: Calculating the search time by leveraging physical and graph theoretical methods

Clustering Analysis of the Spatio-Temporal On-Street Parking Occupancy Data: A Case Study in Hong Kong

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