Mode shift behaviour and user willingness to adopt the electric two-wheeler:A study based on Indian road user preferences  

作　　者：Manivel Murugan Sankaran Marisamynathan 

机构地区：[1]Department of Civil Engineering,National Institute of Technology,Tiruchirappalli,Tamil Nadu,India [2]Department of Civil Engineering,Pandit Deendayal Energy University,Gandhinagar,Gujarat,India

出　　处：《International Journal of Transportation Science and Technology》2023年第2期428-446,共19页交通科学与技术(英文)

摘　　要：As per statistics,two-wheeler(TW)alone shares the highest number of vehicle registrations in India,which develops the various transportation-related issues such as traffic conflicts,congestions,and pollutions.Electric two-wheelers(E-TW)are a better alternative to conventional two-wheelers because of their significant advantage in mitigating environmental impacts.But E-TWs are less attractive among road users due to unawareness of the benefits of E-TW.In addition,the traditional methods are less accurate in predicting users’mode choice behavior because of their limitations.Therefore,there is a need to conduct a study to understand the road user’s willingness to adopt E-TW and find a suitable method for predicting mode choice behavior accurately.This study analyzes the Indian road users encouraging and discouraging factors to adopt E-TW and investigates the application of non-traditional models for estimating mode shift behaviour towards E-TW.Based on the literature review and expert opinion,a detailed questionnaire form was framed,and a total of 522 samples were collected from four states of India.The data findings show that Indian road users prefer TW compared to public transport,private four-wheeler,paratransit,and non-motorized transport because of its easy to ride,low maintenance,fast and convenient travel nature.The environmental concern of reducing air pollution and lower vehicle operating costs are significant factors that encourage E-TW adoption.However,the non-availability of charging infrastructure,lower speed,higher initial purchase cost,and lack of awareness about EVs are the significant discouraging factors in adopting ETW in India.Further,Machine Learning(ML)methods were adopted to predict the mode shift behaviour from the fuel based TW to E-TW,and the results were compared with the Binary Logit(BL)method.The model results indicated that Support vector machine predicted the mode shift behavior with the highest accuracy rate compared with other methods such as Artificial Neural Network,K-Nearest N

关 键 词：Mode shift Support vector machine Artificial neural network Electric two-wheeler Machine learning 

分 类 号：TN9[电子电信—信息与通信工程]