Trip pattern of low density residential area in semi urban industrial cluster: predictive modeling

This research elucidates the trip pattern of the low-density residential zone in a semi-urban industrial cluster of southwestern Nigeria. These sets of dwellers are often times neglected in the transportation planning process. To achieve the aim of this research, domiciliary information gathering procedure was employed with 0.82 return rates. It was backed up with the focus group discussion method. Data on frequency of trips, per capita trip, modal choice, and socioeconomic and demographic data were collected, collated, and analysed. Accordingly, a predictive model was formulated for the trip pattern of the low-density area. This was achieved with the aid of statistical software SPSS version 21.Consequently, the results of the multiple regression models showed that both monthly income and car ownership had a significant positive influence on the work trip while only car ownership positively influences non-work trip. R2 values of 0.729 and 0.739 were obtained for the descriptive model at 95% confidence level. This established the robustness of the model, the analysis showed that monthly income and car ownership had a significant positive influence on the work trip with an Rsquare value of 0.729 and 0.739 for work and non-work trip respectively. This indicated that household will embark on more trips with an increase in car ownership and monthly income. However, effective transportation planning and traffic infrastructural development were recommended to meet the demands of the increased number of trips daily