Determining the travel intention of residents with shared electric vehicles(EVs)is significant for promoting the development of low-carbon transportation,considering that common problems such as high idle rate and lac...Determining the travel intention of residents with shared electric vehicles(EVs)is significant for promoting the development of low-carbon transportation,considering that common problems such as high idle rate and lack of attractiveness still exist.To this end,a structural equation model(SEM)based on the theory of multiple motivations is proposed in this paper.First,the influencing motivations for EV sharing are divided into three categories:consumer-driven,program-driven,and enterprise-driven motivations.Then,the intentions of residents in Shanghai to travel with shared EVs are obtained through a survey questionnaire.Finally,an SEM is constructed to analyze quantitatively the impact of different motivations on the travel intention.The results show that consumer-driven motivations with impact weights from 0.14 to 0.63 have the overwhelming impact on travel intention,compared to program-driven motivations with impact weights from−0.14 to 0.15 and enterprise-driven motivations with impact weights from 0.02 to 0.06.In terms of consumer-driven motivations,the weight of green travel awareness is the highest.The implications of these results on the policy to enable large-scale implementation of shared EVs are discussed from the perspectives of the resident,enterprise,and government.展开更多
In view of the technical difficulties of autonomous navigation in local areas,this paper proposes a high-precision autonomous navigation shared bal-ancing bike system based on EKF-SLAM.This system uses the EKF-SLAM alg...In view of the technical difficulties of autonomous navigation in local areas,this paper proposes a high-precision autonomous navigation shared bal-ancing bike system based on EKF-SLAM.This system uses the EKF-SLAM algorithm in robot localization to achieve simultaneous localization and map con-struction using the extended Kalmanfilter.At the same time,GPS and IMU are also employed for absolute positioning,and point cloud matching is used for rel-ative positioning to achieve multisensor fusion positioning.For the convenience of users,this system uses the RNN-T model for speech recognition destinations.Through experimental verification,the EKF-SLAM-based autonomous naviga-tion technology proposed in this paper can meet the accurate localization service and can realize the function of high precision autonomous navigation and voice recognition of destinations for shared balancing vehicles in a local area.展开更多
基金the National Natural Science Founda-tion of China(Nos.71971139 and 72201172)。
文摘Determining the travel intention of residents with shared electric vehicles(EVs)is significant for promoting the development of low-carbon transportation,considering that common problems such as high idle rate and lack of attractiveness still exist.To this end,a structural equation model(SEM)based on the theory of multiple motivations is proposed in this paper.First,the influencing motivations for EV sharing are divided into three categories:consumer-driven,program-driven,and enterprise-driven motivations.Then,the intentions of residents in Shanghai to travel with shared EVs are obtained through a survey questionnaire.Finally,an SEM is constructed to analyze quantitatively the impact of different motivations on the travel intention.The results show that consumer-driven motivations with impact weights from 0.14 to 0.63 have the overwhelming impact on travel intention,compared to program-driven motivations with impact weights from−0.14 to 0.15 and enterprise-driven motivations with impact weights from 0.02 to 0.06.In terms of consumer-driven motivations,the weight of green travel awareness is the highest.The implications of these results on the policy to enable large-scale implementation of shared EVs are discussed from the perspectives of the resident,enterprise,and government.
文摘In view of the technical difficulties of autonomous navigation in local areas,this paper proposes a high-precision autonomous navigation shared bal-ancing bike system based on EKF-SLAM.This system uses the EKF-SLAM algorithm in robot localization to achieve simultaneous localization and map con-struction using the extended Kalmanfilter.At the same time,GPS and IMU are also employed for absolute positioning,and point cloud matching is used for rel-ative positioning to achieve multisensor fusion positioning.For the convenience of users,this system uses the RNN-T model for speech recognition destinations.Through experimental verification,the EKF-SLAM-based autonomous naviga-tion technology proposed in this paper can meet the accurate localization service and can realize the function of high precision autonomous navigation and voice recognition of destinations for shared balancing vehicles in a local area.
