Parking problems have hindered the smooth traffic in cities for a long time. In this paper, we propose reservation-based private parking slots allocation mechanisms from the e-parking platform's perspective in which proximity and parking cost are considered as demand preferences. Two allocation mechanisms are proposed. The advanced FBFS (first-book-first-serve) provides immediate feedback to each user while the PBA (preference-based-allocation) is an overall optimization mechanism which collects demands in a certain period and allocates at one time at a decision point. A binary integer linear programming model aiming at maximizing platform's profits is proposed for PBA. Results show that PBA guarantees the highest profits when the acceptance rates of the original FBFS, the advanced FBFS and PBA are in mere difference. In conclusion, PBA demonstrates unparalleled superiority while the advanced FBFS outstripped the original FBFS and the proposed mechanisms make good use of idle private parking resources.
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