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i project characteristic mix (existing population of affordable housing sites) and 20 of those sites to collect on- site parking occupancy data. The final selection was made by the city staff. Sources of data for the study are summarized as follows: • Household surveys — Household characteristics (e.g. size, income, # vehicles, parking behavior) • Management surveys - Project characteristics, details and operations • Field observations — Parking counts, land uses and parking restrictions, A total of 27 80 household surveys were distributed to 34 selected project sites with an overall 40% return. One management survey was returned for every project site. Field observations were conducted at 21 sites that maintained the original sample mix and also had a survey response rate of 20 percent or more. Occupancy data was collected at each site both on and off- street between the hours of 12AM and 4AM to measure peak resident parking demand. Property manager feedback was most helpful in the review of tandem parking and parking assignment practices. fla.rking I7a eland Analysis, The statistical arralysisof the survey and field data provided a step -by -step examination of the primary determinant of resident lal parking demand- household vehicle availability— considering both the level household vehilde avaihbility and factors that affect it. The findings are summarized as l'oilows:; 1) Parking demand for affordable projects is about one half of typical rental units in San Diego; almost half the units surveyed had no vehicle:' 2) Parking demand varies with type of affordable housing (i.e., Family Housing versus SRO); higher 3) the amount of peak overnight parking used was less than the amount Parking Model: A parking model was developed based upon the findings in the statistical analysis. It provided empirically-based rates for four types of affordable housing: Family, Living Unit /SRO, Senior Housing, and Studio - ]. Bedroom. The model's predictions were compared with existing requirements and supply patterns, to understand the alignment of those requirements with actual demand levels. The main conclusion from these tests was that current requirements do not require significantly more parking than the household survey -based parking model would suggest. Overnight parking occupancy in projects (where data was available) was less than the current requirements and the model prediction, but overnight parking counts did not account for visitor parking, overnight trips by residents, and some other aspects of demand. ecomYXI en CIO fl rids it was recommended that the parking modal be used to create a, fool; up table of new affordable housing parking requirements. The parking regNiren, ents are determined based on type of afforefable housing and its context in, terms of transit avaffabilfty and, walkability. The parking, requirements also include provisions for visitor and staff parking and expected vacancy. The recornmen&if parsing reclufrements are summarized in the following table, ES -2 ( 31 D -38