开发区域间公共交通模式选择行为模型--印度案例研究

IF 0.2 Q4 MULTIDISCIPLINARY SCIENCES Suranaree Journal of Science and Technology Pub Date : 2023-12-15 DOI:10.55766/sujst-2023-03-e0113
Pinakkumar Ramanuj, Harishkumar Varia, Ami Shah, Arvindkumar M Jain
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引用次数: 0

摘要

区域间公共交通乘客的模式选择行为对于发展中国家交通系统的有效规划和运营非常重要。当局有责任通过提供高效的公共交通服务来满足乘客大量流动的长距离区域旅行需求。大多数关于乘客出行方式选择行为的研究都是针对城市群内的城市公共交通进行的。本研究旨在进一步了解影响印度地区间公共交通乘客出行方式决策的因素。针对印度古吉拉特邦苏拉特市和巴夫纳加尔地区之间的旅行,开发了古吉拉特邦道路交通公司(GSRTC)公交车、铁路和私人运营公交车之间的多项式对数(MNL)模型和人工神经网络(ANN)模型。最终的 ANN 模型反映了属性差异,其模式预测能力为 90.52%,而 MNL 模型为 70.11%。所开发的模型为改善该地区的交通设施提供了正确的见解。结果表明,提高服务水平和出口参数对吸引旅客更为重要。在旅客选择出行方式的思考过程中,卧铺供应、较低的旅行成本、较短的出口距离和夜间旅行的可 用性被认为是重要因素。随着服务水平的提高,旅客选择海沙铁路运输公司巴士和火车的概率分别提高了 13.1%和 20.1%。此外,GSRTC 巴士应改善其连接性。
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DEVELOPMENT OF MODE CHOICE BEHAVIOR MODEL FOR INTER-REGIONAL PUBLIC TRANSPORT– A CASE STUDY OF INDIA
Mode choice behavior of the inter-regional public transport passengers is important for proficient planning and operation of transport systems in developing countries. It is the responsibility of the authority to satisfy the demand for long regional trips having a significant movement of passengers by providing efficient public transport services. Most of the studies for the mode choice behavior of the passengers have been done for the urban mass transport within the urban conglomerate. The study aims to improve knowledge of the factor affecting passengers' decisions on the mode of travel for inter-regional public transportation in India. The Multinomial Logit (MNL) model and Artificial Neural Network (ANN) models among Gujarat State Road Transport Corporation (GSRTC) buses, Railways, and privately operated buses were developed for the trips between Surat city and Bhavnagar region of Gujarat, India. The final ANN model reflects a difference of attributes has 90.52% mode prediction capability against 70.11% of the MNL model. The developed model gives the proper insight for improving the transportation facilities in the region. It is revealed that the improvement in the service level and egress parameters are more important to attract travelers. The sleeper seat availability, lesser travel cost, lesser egress distance, and availability of night journey have been found important during travelers' thinking process to select the traveling mode. There are 13.1% and 20.1% rises in the probability of choosing GSRTC bus and train mode, respectively, with the improvement in the service level. Moreover, the GSRTC bus should improve its connectivity.
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Suranaree Journal of Science and Technology
Suranaree Journal of Science and Technology MULTIDISCIPLINARY SCIENCES-
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