Research Article

A Dynamic Information-Based Parking Guidance for Megacities considering Both Public and Private Parking

Table 1

Weight factor configuration.

Preference typeUtility function for reservationUtility function for suggestionDescription
Weight factorValueWeight factorValue

Base preference(α1, α2, α3, α4)(0, 3, 0, 0)(β1, β2, β3, β4, β5, β6)(0, 3, 0, 0, 0, 0)Drivers choose the nearest parking to destinations without parking guidance
Weighted personally by each driver
(individual preference)
 I(α1, α2, α3, α4)((1–3) for all weight factors)(β1, β2, β3, β4, β5, β6)((1–3) for all weight factors)Random weight on each factor by each driver
Weighted identically by system for all drivers
(central control)
 II(α1, α2, α3, α4)(2, 2, 2, 2)(β1, β2, β3, β4, β5, β6)(2, 2, 2, 2, 2, 2)Equal weights of all factors
 III(α1, α2, α3, α4)(1, 3, 1, 1)(β1, β2, β3, β4, β5, β6)(1, 3, 1, 1, 1, 1)Strong emphasis on the walking distance from parking to destination
 IV(α1, α2, α3, α4)(3, 1, 1, 1)(β1, β2, β3, β4, β5, β6)(3, 1, 1, 1, 1, 1)Strong emphasis on the driving distance/duration from current location to parking
 V(α1, α2, α3, α4)(1, 1, 3, 1)(β1, β2, β3, β4, β5, β6)(1, 1, 3, 1, 1, 1)Strong emphasis on reducing parking cost
 VI(α1, α2, α3, α4)(1, 1, 1, 3)(β1, β2, β3, β4, β5, β6)(1, 1, 1, 3, 1, 1)Strong emphasis on the avoidance of traffic congestion
 VII(α1, α2, α3, α4)(1, 1, 1, 1)(β1, β2, β3, β4, β5, β6)(1, 1, 1, 1, 3, 1)Strong emphasis on the degree of availability to reduce parking failure
 VIII(α1, α2, α3, α4)(1, 1, 1, 1)(β1, β2, β3, β4, β5, β6)(1, 1, 1, 1, 1, 3)Strong emphasis on regional possibility of reducing parking failure