Parking infrastructure design for repositioning autonomous vehicles

Levin, Michael W.; Wong, Eugene; Nault-Maurer, Benjamin; Khani, Alireza

doi:10.1016/j.trc.2020.102838

Cited by 37 publications

(11 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Su and Wang (2020) extended this model to a many-to-one network and investigated the morning commute pattern considering AVs' distant parking and parking-sharing schemes. For network-wide analysis, Zhang, Liu, and Waller (2019) developed the equilibrium flow pattern for AVs considering self-driving for parking purpose, and Levin et al (2020) extended their results to a logit model for parking choice and optimized parking costs. However, these models are limited to lowering the construction cost for parking infrastructure or reducing the system-level travel time of occupied AV trips.…”

Section: Network Design Problem (Ndp)mentioning

confidence: 99%

Analysis on Braess paradox and network design considering parking in the autonomous vehicle environment

Zhang,

Waller,

Lin

2023

Computer aided Civil Eng

View full text Add to dashboard Cite

This study is the first in the literature to examine the Braess paradox considering parking behavior in the autonomous vehicle (AV) environment, based on which the network design problem for the autonomous transportation system (NDP‐ATS) is modeled. First, we introduce the AV commuting pattern considering the self‐driving process for the parking purpose. We then illustrate the existence of two distinct Braess paradoxes that can occur in AV traffic networks with regards to parking space addition and network capacity expansion. They show that these two types of “improvement” measures might deteriorate the network system performance in an AV situation. Second, motivated to avoid the deterioration due to the introduced Braess paradoxes, we develop a bi‐level programming model for NDP‐ATS. The lower‐level program addresses the network‐equilibrium traffic assignment for AVs. The upper‐level program aims to minimize the network‐wide travel cost considering both occupied and empty AV trips by selecting the optimal design option accounting for road capacity enhancement and parking facility deployment simultaneously. To solve the developed bi‐level model, the simplicial homology global optimization algorithm is employed along with the Frank–Wolfe algorithm and the CPLEX. Finally, the efficacy of the modeling framework is validated through case studies on the Sioux Falls city network and the Anaheim network. The results show that the developed methodology is capable of producing high‐quality solutions with respect to savings in system‐level travel costs for AV traffic. The results also highlight the impacts of parking fees on the system performance for the optimized network. Additionally, it is found that the two objectives, which minimize the total system travel cost and minimize that for empty AV trips only, are conflicting for certain scenarios. The methodological approach introduced in this work serves as a critical modeling device for infrastructure development and policy assessment for AV traffic.

show abstract

Section: Network Design Problem (Ndp)mentioning

confidence: 99%

Analysis on Braess paradox and network design considering parking in the autonomous vehicle environment

Zhang,

Waller,

Lin

2023

Computer aided Civil Eng

View full text Add to dashboard Cite

show abstract

“…This is because SAVs can drop off passengers at their convenient locations (e.g., homes, offices, locations with usually high land price) and then park at distant location with low land price, and this phenomenon may change land use pattern of a city [22]. To solve this problem, approaches similar to that for the road network design problem have been used, such as continuous traffic assignment [32] and microscopic agentbased simulation [33]. More macroscopic approaches based on spatial economics have also been used [7], [34].…”

Section: B Strategic Aspects Of Sav Systemsmentioning

confidence: 99%

Multi-Objective Linear Optimization Problem for Strategic Planning of Shared Autonomous Vehicle Operation and Infrastructure Design

Seo

Asakura

2022

IEEE Trans. Intell. Transport. Syst.

View full text Add to dashboard Cite

This study proposes a unified optimization framework for strategic planning of shared autonomous vehicle (SAV) systems that explicitly and endogenously considers their operational aspects based on macroscopic dynamic traffic assignment. Specifically, the proposed model optimizes fleet size, road network design, and parking space allocation of an SAV system with optimized SAVs' dynamic routing with passenger pickup/delivery and ridesharing. It is formulated as a multi-objective optimization problem that simultaneously minimizes total travel time of travelers, total distance traveled by SAVs, total number of SAVs, and infrastructure construction cost; thus, both the user-side cost and the system-side cost are taken into account, and their trade-off relations can be explicitly investigated. Furthermore, the problem is formulated as a linear programming problem, making it easy to solve. By leveraging the linearity, we mathematically derive a useful property of the problem: introduction of ridesharing can weakly monotonically and simultaneously decrease the user-side cost and system-side cost. The proposed model is evaluated by applying it to actual travel records obtained from New York City taxi data.

show abstract

“…This allows households to reduce vehicle ownership without compromising overall household mobility. Working household members may economize on out-of-pocket curbside parking costs at work location when programing the FAV for returning home or riding to nonchargeable/cheaper and safer parking areas (Levin et al , 2020; Tscharaktschiew et al , 2022). They can be dropped off right at the company site without having to search for a parking spot or having to walk from that spot to the office or factory.…”

Section: The Role Of Self-driving Carsmentioning

confidence: 99%

“…When account is taken of the fact that each shared autonomous vehicle has the potential to replace around ten privately owned vehicles (Fagnant and Kockelman, 2015), it comes not as a surprise that this eventually translates into reduction in car parking spaces. In contrast, Zakharenko (2016), Liu (2018), Millard-Ball (2019), Zhang et al (2019a), Su and Wang (2020), Levin et al (2020) and Bahrami et al (2021) deal explicitly with the case of privately owned FAVs. They show that it could be a cost-effective option – for travelers and/or the society as a whole – not to park close to their destination, instead letting the FAV return home, seek out (free) on- or off-street parking elsewhere or just cruise (circle around).…”

Section: Introductionmentioning

confidence: 99%

Less workplace parking with fully autonomous vehicles?

Tscharaktschiew

Reimann

2022

JICV

View full text Add to dashboard Cite

Purpose Recent studies on commuter parking in an age of fully autonomous vehicles (FAVs) suggest, that the number of parking spaces close to the workplace demanded by commuters will decline because of the capability of FAVs to return home, to seek out (free) parking elsewhere or just cruise. This would be good news because, as of today, parking is one of the largest consumers of urban land and is associated with substantial costs to society. None of the studies, however, is concerned with the special case of employer-provided parking, although workplace parking is a widespread phenomenon and, in many instances, the dominant form of commuter parking. The purpose of this paper is to analyze whether commuter parking will decline with the advent of self-driving cars when parking is provided by the employer. Design/methodology/approach This study looks at commuter parking from the perspective of both the employer and the employee because in the case of employer-provided parking, the firm’s decision to offer a parking space and the incentive of employees to accept that offer are closely interrelated because of the fringe benefit character of workplace parking. This study develops an economic equilibrium model that explicitly maps the employer–employee relationship, considering the treatment of parking provision and parking policy in the income tax code and accounting for adverse effects from commuting, parking and public transit. This study determines the market level of employer-provided parking in the absence and presence of FAVs and identifies the factors that drive the difference. This study then approximates the magnitude of each factor, relying on recent (first) empirical evidence on the impacts of FAVs. Findings This paper’s analysis suggests that as long as distortive (tax) policy favors employer-provided parking, FAVs are no guarantee to end up with less commuter parking. Originality/value This study’s findings imply that in a world of self-driving cars, policy intervention related to work commuting (e.g. fringe benefit taxation or transport pricing) might be even more warranted than today.

show abstract

Parking infrastructure design for repositioning autonomous vehicles

Cited by 37 publications

References 29 publications

Analysis on Braess paradox and network design considering parking in the autonomous vehicle environment

Analysis on Braess paradox and network design considering parking in the autonomous vehicle environment

Multi-Objective Linear Optimization Problem for Strategic Planning of Shared Autonomous Vehicle Operation and Infrastructure Design

Less workplace parking with fully autonomous vehicles?

Contact Info

Product

Resources

About