01662998

Component

In an effort to reduce circling and cruising in cities’ central business districts (CBDs), a number of cities began implementing pricing programs that modify parking rates based on observed occupancy levels. The authors improve on this pricing mechanism by developing a forward-looking policy instrument. The instrument employs a two-stage panel data regression and optimization model that influences demand for parking spaces by changing parking rates via computed price elasticities of parking demand measures. An application of the approach is presented using SFpark, a federal government-funded demonstration program in San Francisco as a case study. The authors evaluate the effectiveness of the modified pricing mechanism by comparing actual occupancy and parking rate tuples with the optimized result to ascertain the potential improvement in SFpark’s performance. Policy scenarios are subsequently explored by carrying out sensitivity analysis primarily through by SFpark pricing rules.The authors' findings highlight the importance of moving towards a predictive regime that allows for proactively managing the parking program compared to a reactive approach based on observed parking occupancy. Relative to SFpark’s figures, the authors' model yielded approximately 16% improvement in systems performance when measured by the number of blocks that deviate from the 60 to 80% occupancy target. Of importance are the directional guidelines provided by the policy-related scenarios. The scenarios enrich the analysis by providing an advocacy tool and by generating insights on key policy levers that can point the agency managing the program in the right direction.

This paper was sponsored by TRB committee ABE50 Standing Committee on Transportation Demand Management.

18-02643

English

7p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; References; Tables

Case studies; Central business districts; Optimization; Parking; Parking demand; Performance measurement; Prices; Prices; Pricing

San Francisco (California)

Finance; Highways; Planning and Forecasting

Transportation Research Board Annual Meeting 2018 Paper #18-02643

TRIS, TRB, ATRI

Jan 8 2018 10:38AM