Parking Demand Prediction Method of Urban Commercial-Office Complex Buildings Based on the MRA-BAS-BP Algorithm

Table 1

Construction of the parking demand prediction index system.

Influence factors	Composition indices	Symbols	Specific meaning and calibration method
Building location factors	Proportion of car trips	x1	The proportion of small- and medium-sized car trips in the total traffic volume generated by buildings
	Car ownership rate per 1,000 people	x2	The average number of cars per 1,000 people in the subdistrict where the building is located, unit: vehicle/1,000 people
	Location index	x3	The location index is measured by the real GDP per capita () in the subdistrict where the building is located, unit: yuan/person
	Road network capacity	x4	The standard vehicle equivalent that can be accommodated by the road network within the enclosed area of the first trunk road around the building in peak hours, unit: pcu/h
	Transit accessibility	x5	An indicator to measure the convenience of people from a building to complete a trip through public transportation
Building development factors	Commercial area of the building	x6	Area of the commercial part of the building, unit: m^2
	Number of posts per building	x7	Maximum number of posts that can be provided in the office area of the building, unit: person
	Parking charging standard	x8	Price of hourly parking charge for the building, unit: yuan/h
	Number of shared parking spots	x9	Number of berths provided by the building of common use for travelers with commercial and office purposes, unit: PCs
	Building development intensity	x10	The building floor area ratio is used to measure the development intensity of the building, which refers to the ratio of the total building area on the building ground to the net land area