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<p>Rapid growth of technology-based transportation services has drastically altered the nature of transportation networks as well as individuals’ travel behaviour and lifestyle. People generally rely on two transportation networks such as public and private for travel. However, the existing transportation network faces a lot of crises such as traffic congestion, environmental impact and cost consumption. So, an effective study must be conducted to analyse the access and egress mode choice of travellers to solve these above mentioned issues and to improve the transit accessibility and comfort of the travellers. Most of the existing mode choice analysis studies are conducted in the main cities of India. However, the accessibility of transit in other cities of India is not known to the people. Thus, this current research target is to analyse the access and egress mode choice of travellers using the MNP-INL regression model in Bhopal city. Initially, questionnaires are framed to conduct surveys from respondents. Based on the responses collected from the respondents the dataset needed for analysis is prepared. After that, the correlation prevailing between traveller mode choice and variable factor is found by calculating the correlation coefficient. The variable factors include the user and trip characteristics. Then, based on the correlation the choice of access and egress mode used by the traveller is estimated using regression models such as the Multinomial Probit Model (MNP) and Improved Nested Logit (INL) model. The nested logit model is improved through optimizing inclusive parameters using Honey Badger Optimization (HBO). The behaviour of travellers is significantly influenced by various factors. From that, the quality Parameter related to the main mode is essential and has a great influence in analysing the traveller’s mode. Simulation analysis showed that 8.8% RMSE, 0.97% MSE and 91% R squared are achieved using the proposed model for access mode. 7.2% RMSE, 0.76% MSE and 94% R squared is achieved for egress mode. Compared to the current approaches, MNP-INL can attain better performance. Based on this study it is suggested that many travellers prefer private and public modes for their convenience and it consumes less time. Whereas on considering cost city bus is found to be more convenient.</p>

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Multinomial Probit-Improved Nested Logit Regression Model for Examining Travellers Choices of Access and Egress Modes in Bhopal City

  • 期刊论文

  • 发表日期：

    2025年3月11日

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  • Rahul Tanwar,
  • Pradeep Kumar Agarwal

摘要

Rapid growth of technology-based transportation services has drastically altered the nature of transportation networks as well as individuals’ travel behaviour and lifestyle. People generally rely on two transportation networks such as public and private for travel. However, the existing transportation network faces a lot of crises such as traffic congestion, environmental impact and cost consumption. So, an effective study must be conducted to analyse the access and egress mode choice of travellers to solve these above mentioned issues and to improve the transit accessibility and comfort of the travellers. Most of the existing mode choice analysis studies are conducted in the main cities of India. However, the accessibility of transit in other cities of India is not known to the people. Thus, this current research target is to analyse the access and egress mode choice of travellers using the MNP-INL regression model in Bhopal city. Initially, questionnaires are framed to conduct surveys from respondents. Based on the responses collected from the respondents the dataset needed for analysis is prepared. After that, the correlation prevailing between traveller mode choice and variable factor is found by calculating the correlation coefficient. The variable factors include the user and trip characteristics. Then, based on the correlation the choice of access and egress mode used by the traveller is estimated using regression models such as the Multinomial Probit Model (MNP) and Improved Nested Logit (INL) model. The nested logit model is improved through optimizing inclusive parameters using Honey Badger Optimization (HBO). The behaviour of travellers is significantly influenced by various factors. From that, the quality Parameter related to the main mode is essential and has a great influence in analysing the traveller’s mode. Simulation analysis showed that 8.8% RMSE, 0.97% MSE and 91% R squared are achieved using the proposed model for access mode. 7.2% RMSE, 0.76% MSE and 94% R squared is achieved for egress mode. Compared to the current approaches, MNP-INL can attain better performance. Based on this study it is suggested that many travellers prefer private and public modes for their convenience and it consumes less time. Whereas on considering cost city bus is found to be more convenient.