An Evaluation of Information Sharing Parking Guidance Policies Using a Bayesian Approach

16 Pages Posted: 17 Nov 2016

See all articles by Xinyi Wu

Xinyi Wu

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering

Kartik Balkumar

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering

Qi Luo

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering

Robert Hampshire

University of Michigan at Ann Arbor - Transportation Research Institute

Romesh Saigal

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering

Date Written: November 2, 2016

Abstract

Real-time parking occupancy information is critical for a parking management system to facilitate drivers to park more efficiently. Recent advances in connected and automated vehicle technologies enable sensor-equipped cars (probe cars) to detect and broadcast available parking spaces when driving through parking lots. In this paper, we evaluate the impact of market penetration of probe cars on the system performance, and investigate different parking guidance policies to improve the data acquisition process. We adopt a simulation-based approach to impose four policies on an offstreet parking lot influencing the behavior of probe cars to park in assigned parking spaces. This in turn effects the scanning route and the parking space occupancy estimations. The last policy we propose is a near-optimal guidance strategy that maximizes the information gain of posteriors. The results suggest that an efficient information gathering policy can compensate for low penetration of connected and automated vehicles. We also highlight the policy trade-off that occur while attempting to maximize information gain through explorations and improve assignment accuracy through exploitations. Our results can assist urban policy makers in designing and managing smart parking systems.

Keywords: Transportation, Parking

JEL Classification: R40

Suggested Citation

Wu, Xinyi and Balkumar, Kartik and Luo, Qi and Hampshire, Robert and Saigal, Romesh, An Evaluation of Information Sharing Parking Guidance Policies Using a Bayesian Approach (November 2, 2016). Available at SSRN: https://ssrn.com/abstract=2869942 or http://dx.doi.org/10.2139/ssrn.2869942

Xinyi Wu (Contact Author)

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering ( email )

1205 Beal Avenue
Ann Arbor, MI 48109
United States

Kartik Balkumar

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering ( email )

1205 Beal Avenue
Ann Arbor, MI 48109
United States

Qi Luo

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering ( email )

1205 Beal Avenue
Ann Arbor, MI 48109
United States

Robert Hampshire

University of Michigan at Ann Arbor - Transportation Research Institute ( email )

2901 Baxter Road
Ann Arbor, MI 48109
United States

Romesh Saigal

University of Michigan at Ann Arbor - Department of Industrial and Operations Engineering ( email )

1205 Beal Avenue
Ann Arbor, MI 48109
United States

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