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<p>The present study examines trip generation dynamics in Surat, Ahmedabad, and Rajkot, emphasizing the influence of household characteristics on urban travel behavior. Primary data collection via interviews analyzed factors like household size, income, vehicle ownership, and trip purposes. Statistical analysis revealed no significant differences in household size and trip rates across cities but noted unique patterns, particularly between Surat-Ahmedabad and Rajkot. Regression models identified earning members and school/college-going students as key predictors for work and education trips, respectively. To address censored data limitations, the Grouped Random Parameter Tobit model was employed, demonstrating superior goodness-of-fit (highest log-likelihood, lowest AIC/BIC). The model highlighted the impact of household size, urban form, and city-specific variations on trip rates, revealing an inverse relationship between household size and per capita trips. These findings underscore the model’s reliability in understanding urban travel behavior and offer valuable insights for transportation planning and policy formulation.</p>

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Unveiling urban dynamics: modeling household characteristics and trip generation in three Indian cities

  • 期刊论文

  • 发表日期：

    2025年4月25日

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  • Aninda Bijoy Paul,
  • Rohit Rathod,
  • Harsh Rabdiya,
  • Gaurang Joshi,
  • Shriniwas Arkatkar

摘要

The present study examines trip generation dynamics in Surat, Ahmedabad, and Rajkot, emphasizing the influence of household characteristics on urban travel behavior. Primary data collection via interviews analyzed factors like household size, income, vehicle ownership, and trip purposes. Statistical analysis revealed no significant differences in household size and trip rates across cities but noted unique patterns, particularly between Surat-Ahmedabad and Rajkot. Regression models identified earning members and school/college-going students as key predictors for work and education trips, respectively. To address censored data limitations, the Grouped Random Parameter Tobit model was employed, demonstrating superior goodness-of-fit (highest log-likelihood, lowest AIC/BIC). The model highlighted the impact of household size, urban form, and city-specific variations on trip rates, revealing an inverse relationship between household size and per capita trips. These findings underscore the model’s reliability in understanding urban travel behavior and offer valuable insights for transportation planning and policy formulation.