• Tanuj Nangia
• Dr. Umesh Sharma

The case study aims to investigate the elements that influence trip generation in Chandigarh City and design a trip generation model. A trip generation model is created which considers all of the influencing characteristics to forecast future travels. The model was created using multiple linear regression analysis with the Statistical Package for the Social Sciences (SPSS), which finds a link between respondents' travel time and Socio-economic characteristics. A general model for trip generation has been developed. The model resulted in a practical value of R2 as 0.385, suggesting that the variables included within the model considered explanatory variables, such as age, occupation, average daily distance traveled, mode of transportation, the purpose of visit, and frequency of visit explains 38.5% of the dependent variable. MAPE value calculated as 44.694% shows that the forecasting is legitimate. The Root Mean Square Error is 0.407, which shows that the model can relatively predict data accurately. Further extensive research is required to apply this model for planning purposes. This model may be used to estimate future journeys accurately.

Trip generation, Multiple Linear Regressions, Statistical Package for the Social Sciences; Mean Absolute Percentage Error, Root Mean Square Error.

"Modeling Of Travel Time Under Heterogeneous Traffic Condition In Chandigarh- A Case Study", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 5, page no.c573-c577, May-2022, Available :http://www.jetir.org/papers/JETIR2205277.pdf

"Modeling Of Travel Time Under Heterogeneous Traffic Condition In Chandigarh- A Case Study", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 5, page no. ppc573-c577, May-2022, Available at : http://www.jetir.org/papers/JETIR2205277.pdf