| As congestion on transportation infrastructure during peak periods continues to increase, there is a growing need for solutions that do not require large scale investments in infrastructure but rather manage the demand for travel through altering the travel behavior choices of residents. The primary objective of this study was to investigate one proposed remedy, the working environment where employees are allowed to work from home, known as telecommuting, and to examine its influence on personal trip generation. Furthermore, a secondary objective of this study was to investigate the adequacy of current trip generation practices in calculating control trip totals within an urban region.;The estimated binary logit models of telecommuting choice for both Nashville and Minneapolis showed that telecommuting is a decision influenced by amongst others a variety of socio-economic, demographic, and work-related factors. The model estimation results also showed unspecified factors to be influential on whether or not to telecommute. The models of the number of trips made daily by a worker show telecommuting to be a significantly influential factor in how many trips are made. Further, telecommuting actually exhibited a positive relationship with the number of trips made daily by a worker indicating that telecommuting may not hold much promise as a transportation demand management measure if the objective is to reduce daily travel demand.;With regard to determining the control total of trips from trip generation to be used in trip distribution modeling, it was found that the current practice of assuming greater accuracy in the trip production data hence to rely solely on it to derive the control trip total for a region may not necessarily result in the most accurate estimate. Instead, a method developed in this research, which blends the forecast regional trip production and regional trip attraction based on their respective reliability was proposed as offering a statistically sounder approach to estimating the control trip total. In the single empirical test of the methods, the proposed method gave a more accurate estimate of the control total. |
