Integrated Departure Time and Parking Location Choices in a Morning Commute Problem under a Partially Automated Environment
This study formulates the joint decisions of commuters on departure time and parking location choices in a morning commute problem where the commuters travel with autonomous vehicles (AVs) or human-driven vehicles (HVs). Under a mixed traffic environment, we aim to explore the impacts of parking cap...
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| Format: | Article |
| Language: | English |
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MDPI AG
2024-02-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/14/4/1502 |
| _version_ | 1797299000558223360 |
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| author | Zhanzhi Liao Jian Wang Yuanyuan Li |
| author_facet | Zhanzhi Liao Jian Wang Yuanyuan Li |
| author_sort | Zhanzhi Liao |
| collection | DOAJ |
| description | This study formulates the joint decisions of commuters on departure time and parking location choices in a morning commute problem where the commuters travel with autonomous vehicles (AVs) or human-driven vehicles (HVs). Under a mixed traffic environment, we aim to explore the impacts of parking capacity and parking pricing on the equilibrium travel pattern and the system performance. We build a dynamic equilibrium model for the morning commute problem by assuming that the parking slots can be grouped into central and peripheral clusters based on the distance between the parking location and the workplace. We first analyze the parking location preferences of commuters towards the two parking clusters under a mixed traffic environment. We then examine the equilibrium conditions and identify all the equilibrium travel patterns. We further analyze the system performance measured by the total travel cost with respect to the parking prices and the capacity of the central cluster. The optimal parking pricing scheme is also derived to minimize the total travel cost. We conduct numerical analysis to demonstrate the change in the total travel cost against the parking capacity of the central cluster and its parking price. Sensitivity analysis is performed to show the impacts of the network configuration on the total travel cost. |
| first_indexed | 2024-03-07T22:43:13Z |
| format | Article |
| id | doaj.art-06f62efd2d6443a59302cd769052e21f |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-07T22:43:13Z |
| publishDate | 2024-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-06f62efd2d6443a59302cd769052e21f2024-02-23T15:06:12ZengMDPI AGApplied Sciences2076-34172024-02-01144150210.3390/app14041502Integrated Departure Time and Parking Location Choices in a Morning Commute Problem under a Partially Automated EnvironmentZhanzhi Liao0Jian Wang1Yuanyuan Li2School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Management, Harbin Institute of Technology, Harbin 150001, ChinaSchool of Management, Harbin Institute of Technology, Harbin 150001, ChinaThis study formulates the joint decisions of commuters on departure time and parking location choices in a morning commute problem where the commuters travel with autonomous vehicles (AVs) or human-driven vehicles (HVs). Under a mixed traffic environment, we aim to explore the impacts of parking capacity and parking pricing on the equilibrium travel pattern and the system performance. We build a dynamic equilibrium model for the morning commute problem by assuming that the parking slots can be grouped into central and peripheral clusters based on the distance between the parking location and the workplace. We first analyze the parking location preferences of commuters towards the two parking clusters under a mixed traffic environment. We then examine the equilibrium conditions and identify all the equilibrium travel patterns. We further analyze the system performance measured by the total travel cost with respect to the parking prices and the capacity of the central cluster. The optimal parking pricing scheme is also derived to minimize the total travel cost. We conduct numerical analysis to demonstrate the change in the total travel cost against the parking capacity of the central cluster and its parking price. Sensitivity analysis is performed to show the impacts of the network configuration on the total travel cost.https://www.mdpi.com/2076-3417/14/4/1502autonomous vehicleshuman-driven vehiclesbottleneck modelparking locationparking prices |
| spellingShingle | Zhanzhi Liao Jian Wang Yuanyuan Li Integrated Departure Time and Parking Location Choices in a Morning Commute Problem under a Partially Automated Environment Applied Sciences autonomous vehicles human-driven vehicles bottleneck model parking location parking prices |
| title | Integrated Departure Time and Parking Location Choices in a Morning Commute Problem under a Partially Automated Environment |
| title_full | Integrated Departure Time and Parking Location Choices in a Morning Commute Problem under a Partially Automated Environment |
| title_fullStr | Integrated Departure Time and Parking Location Choices in a Morning Commute Problem under a Partially Automated Environment |
| title_full_unstemmed | Integrated Departure Time and Parking Location Choices in a Morning Commute Problem under a Partially Automated Environment |
| title_short | Integrated Departure Time and Parking Location Choices in a Morning Commute Problem under a Partially Automated Environment |
| title_sort | integrated departure time and parking location choices in a morning commute problem under a partially automated environment |
| topic | autonomous vehicles human-driven vehicles bottleneck model parking location parking prices |
| url | https://www.mdpi.com/2076-3417/14/4/1502 |
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