A Linear Program for System Optimal Parking Reservation Assignment
Most studies on traffic assignment ignore the substantial effects of searching for parking on travel times and congestion. Recent work on parking reservation systems provide an alternative to searching for parking by allocating parking spaces while travelers are en-route, or before they depart. The necessary technologies are well-established and generally available, but the network effects of parking reservation are not yet well understood. Using parking reservation systems, system optimal traffic assignment can be combined with parking space allocation to minimize the combination of in-vehicle travel time and time spent walking from parking to the destination. This paper modifies the linear program for system optimal dynamic traffic assignment of round-trip travel to include parking assignment. The parking location, and time spent at the destination, affect the departure time and origin for the return trip. The model is further extended to trip chains for travelers visiting multiple zones before returning to their residence. Numerical results quantify increases in walking time and in-vehicle travel time when primary parking is unavailable.
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Supplemental Notes:
- This paper was sponsored by TRB committee ADB30 Standing Committee on Transportation Network Modeling.
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Corporate Authors:
Transportation Research Board
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Authors:
- Levin, Michael W
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Conference:
- Transportation Research Board 98th Annual Meeting
- Location: Washington DC, United States
- Date: 2019-1-13 to 2019-1-17
- Date: 2019
Language
- English
Media Info
- Media Type: Digital/other
- Features: References;
- Pagination: 6p
Subject/Index Terms
- TRT Terms: Linear programming; Parking; Parking demand; Reservation systems; Traffic assignment; Traffic congestion; Travel time
- Subject Areas: Highways; Operations and Traffic Management; Planning and Forecasting;
Filing Info
- Accession Number: 01698221
- Record Type: Publication
- Report/Paper Numbers: 19-00591
- Files: TRIS, TRB, ATRI
- Created Date: Mar 1 2019 3:51PM