DEVELOPING VEHICULAR AND NON-VEHICULAR TRIP GENERATION MODELS FOR MID-RISE RESIDENTIAL BUILDINGS IN KELOWNA, BRITISH COLUMBIA: ASSESSING THE IMPACT OF BUILT ENVIRONMENT, LAND USE, AND NEIGHBORHOOD CHARACTERISTICS

Developing vehicular and non-vehicular trip generation models for mid-rise residential buildings in Kelowna, British Columbia: Assessing the impact of built environment, land use, and neighborhood characteristics

Developing vehicular and non-vehicular trip generation models for mid-rise residential buildings in Kelowna, British Columbia: Assessing the impact of built environment, land use, and neighborhood characteristics

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This study develops vehicular and non-vehicular trip generation models for mid-rise, multi-family residential developments.A comparative analysis of observed and Instiutue of Transportation Engineers (ITE) trip rates suggests that ITE rates consistently overestimate.A latent segmentation-based negative binomial (LSNB) model is developed to improve the methodology viva la juicy la fleur notes for estimating vehicular and non-vehicular trips.One of the key features of an LSNB model is to capture heterogeneity.

Segment allocation results for the vehicular and non-vehicular models suggest that one segment includes suburban developments, whereas the other includes urban developments.Results reveal that a higher number of dwelling units is likely to be associated with increased vehicle trips.For non-vehicular trips, a higher number of dwelling units and increased recreational opportunities are more likely to increase trip generation.The LSNB model confirms the existence of significant heterogeneity.

For instance, higher land-use mix has a higher probability to deter vehicular trips in urban areas, whereas trips in the suburban areas are likely to continue increasing.Higher density of bus 15-1 shampoo routes and sidewalks are likely to be associated with increased non-vehicular trips in urban areas, yet such trips are likely to decrease in suburban areas.An interesting finding is that higher bikeability in suburban areas is more likely to increase non-vehicular trips.The findings of this study are expected to assist engineers and planners to predict vehicular and non-vehicular trips with higher accuracy.

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