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<p>Understanding how passengers distribute their route choices in transit networks is critical for promoting route diversity and optimizing system performance. While traditional route choice models focus on utility maximization, they often overlook the actual distributional patterns of behavior across routes. Base on this, we present a framework for analyzing route choice evenness at individual and group levels, inspired by biological evenness indices. Using real-world transit data from Xi’an, China, we developed the Evenness Index, a specific metric to quantify route choice evenness, and employed ordinary least squares regression to explore influencing factors. We find that only 9.6% of passengers have multiple observed routes between a given origin–destination (OD) pair during the observed period. Regression results show that route length, headway variability, OD distance, trip frequency, and network density significantly impact evenness, with groups being more sensitive than individuals. These impacts also vary significantly across geographic areas and passenger types. Compared to occasional passengers (infrequent travelers), stable passengers show relatively lower evenness and experience a threshold effect where evenness decreases when route length differences exceed 500&#xa0;m. This threshold varies across demographics like the elderly and students. Notably, evenness distributions conform to power-law functions, indicating complex and interconnected passenger dynamics. These findings not only deepen our understanding of public transit passenger behavior, but also offer actionable insights for designing equitable and efficient transit systems.</p>

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Analyzing passenger route evenness: distance difference threshold effects and systemic trends

  • 期刊论文

  • 发表日期：

    2025年10月3日

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  • Hongchang Liu,
  • Yajuan Deng,
  • Liangbing Cui

摘要

Understanding how passengers distribute their route choices in transit networks is critical for promoting route diversity and optimizing system performance. While traditional route choice models focus on utility maximization, they often overlook the actual distributional patterns of behavior across routes. Base on this, we present a framework for analyzing route choice evenness at individual and group levels, inspired by biological evenness indices. Using real-world transit data from Xi’an, China, we developed the Evenness Index, a specific metric to quantify route choice evenness, and employed ordinary least squares regression to explore influencing factors. We find that only 9.6% of passengers have multiple observed routes between a given origin–destination (OD) pair during the observed period. Regression results show that route length, headway variability, OD distance, trip frequency, and network density significantly impact evenness, with groups being more sensitive than individuals. These impacts also vary significantly across geographic areas and passenger types. Compared to occasional passengers (infrequent travelers), stable passengers show relatively lower evenness and experience a threshold effect where evenness decreases when route length differences exceed 500 m. This threshold varies across demographics like the elderly and students. Notably, evenness distributions conform to power-law functions, indicating complex and interconnected passenger dynamics. These findings not only deepen our understanding of public transit passenger behavior, but also offer actionable insights for designing equitable and efficient transit systems.