Bibliografías temáticas / Ridesplitting

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Literatura académica sobre el tema "Ridesplitting"

Autor: Grafiati
Publicado: 25 de mayo de 2024

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Artículos de revistas sobre el tema "Ridesplitting"

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Cahyo, Anggit, Nahry, and Helen Burhan. "Mode choice model analysis between ridesouring and ridesplitting service in DKI Jakarta." MATEC Web of Conferences 270 (2019): 03013. http://dx.doi.org/10.1051/matecconf/201927003013.

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Beside the ridesoucing service, ridesplitting service is also offered by Transport Network Companies (TNC). The ridesplitting service have more benefit than ridesourcing because it is using the concept of carsharing. The current condition for ridesplitting service is not popular and only have small demand than ridesourcing service. This study aims to establish a mode choice model between ridesourcing and ridesplitting service in DKI Jakarta and to estimate the potential of demand shifting from ridesourcing to ridesplitting service in DKI Jakarta. The mode choice model is developed from binary
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Li, Xiaomei, Yiwen Zhang, Zijie Yang, Yijun Zhu, Cihang Li, and Wenxiang Li. "Modeling Choice Behaviors for Ridesplitting under a Carbon Credit Scheme." Sustainability 15, no. 16 (2023): 12241. http://dx.doi.org/10.3390/su151612241.

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Ridesplitting, a form of shared ridesourcing service, has the potential to significantly reduce emissions. However, its current adoption rate among users remains relatively low. Policies such as carbon credit schemes, which offer rewards for emission reduction, hold great promise in promoting ridesplitting. This study aimed to quantitatively analyze the choice behaviors for ridesplitting under a carbon credit scheme. First, both the socio-demographic and psychological factors that may influence the ridesplitting behavioral intention were identified based on the theory of planned behavior, tech
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Wang, Jincheng, Qunqi Wu, Zilin Chen, Yilong Ren, and Yaqun Gao. "Exploring the Factors of Intercity Ridesplitting Based on Observed and GIS Data: A Case Study in China." ISPRS International Journal of Geo-Information 10, no. 9 (2021): 622. http://dx.doi.org/10.3390/ijgi10090622.

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Ridesplitting, a form of ridesourcing in which riders with similar origins and destinations are matched, is an effective mode of sustainable transportation. In recently years, ridesplitting has spread rapidly worldwide and plays an increasingly important role in intercity travel. However, intercity ridesplitting has rarely been studied. In this paper, we use observe intercity ridesplitting data between Yinchuan and Shizuishan in China and building environment data based on a geographic information system (GIS) to analyse temporal, spatial and other characteristics. Then, we divide the study ar
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Li, Xinghua, Feiyu Feng, Wei Wang, Cheng Cheng, Tianzuo Wang, and Pengcheng Tang. "Structure Analysis of Factors Influencing the Preference of Ridesplitting." Journal of Advanced Transportation 2021 (February 24, 2021): 1–8. http://dx.doi.org/10.1155/2021/8820701.

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Ridesplitting is a new form of for-hire service that riders with similar origins and destinations are matched to the same vehicle in real-time via Internet. However, the market share of ridesplitting only accounts for a small fraction of total travel. Understanding cognitive factors affecting ridesplitting preference would be helpful in designing its market measures, regulations, and incentives to achieve high-level customer attractions. This paper identifies the cognitive determinants affecting ridesplitting preference and their inner relationships via the structural equation model. The data
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Du, Mingyang, Lin Cheng, Xuefeng Li, Qiyang Liu, and Jingzong Yang. "Spatial variation of ridesplitting adoption rate in Chicago." Transportation Research Part A: Policy and Practice 164 (October 2022): 13–37. http://dx.doi.org/10.1016/j.tra.2022.07.018.

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Beojone, Caio Vitor, and Nikolas Geroliminis. "A dynamic multi-region MFD model for ride-sourcing with ridesplitting." Transportation Research Part B: Methodological 177 (November 2023): 102821. http://dx.doi.org/10.1016/j.trb.2023.102821.

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Li, Wenxiang, Lei Wang, Ziyuan Pu, Long Cheng, and Linchuan Yang. "What determines the real-world CO2 emission reductions of ridesplitting trips?" Travel Behaviour and Society 35 (April 2024): 100734. http://dx.doi.org/10.1016/j.tbs.2023.100734.

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Tu, Meiting, Wenxiang Li, Olivier Orfila, Ye Li, and Dominique Gruyer. "Exploring nonlinear effects of the built environment on ridesplitting: Evidence from Chengdu." Transportation Research Part D: Transport and Environment 93 (April 2021): 102776. http://dx.doi.org/10.1016/j.trd.2021.102776.

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Zhu, Zheng, Xiaoran Qin, Jintao Ke, Zhengfei Zheng, and Hai Yang. "Analysis of multi-modal commute behavior with feeding and competing ridesplitting services." Transportation Research Part A: Policy and Practice 132 (February 2020): 713–27. http://dx.doi.org/10.1016/j.tra.2019.12.018.

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Chen, Xiqun (Michael), Majid Zahiri, and Shuaichao Zhang. "Understanding ridesplitting behavior of on-demand ride services: An ensemble learning approach." Transportation Research Part C: Emerging Technologies 76 (March 2017): 51–70. http://dx.doi.org/10.1016/j.trc.2016.12.018.

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Tesis sobre el tema "Ridesplitting"

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Tu, Meiting. "Optimisation des services de "ridesourcing" pour le déploiement futur des véhicules autonomes et connectés en milieu urbain." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASG048.

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Les services de transport à la demande sont de plus en plus populaires en raison de leur commodité. Cependant, certaines études font apparaitre que ces services pourraient augmenter les congestions et le niveau de pollution. Le ridesplitting, un nouveau service de mobilité partagée, est un moyen plus durable de se déplacer pour améliorer l'efficacité des transports et réduire les émissions de polluants. Dans ce contexte, ce travail propose un cadre d'optimisation pour un Système de Mobilité Partagée (SMP). L'originalité et les aspects innovants développés dans cette thèse sont aussi bien théor
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Actas de conferencias sobre el tema "Ridesplitting"

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Zhu, Jiangtao, Dong Mo, and Xiqun (Michael) Chen. "A Grouping Approach to Ridesplitting Optimization." In 20th COTA International Conference of Transportation Professionals. American Society of Civil Engineers, 2020. http://dx.doi.org/10.1061/9780784482933.394.

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Chen, Zilin, Yilong Ren, Xinrui Zheng, and Xiang Fu. "Impact of COVID-19 on Spatiotemporal Factors Affecting Ridesplitting Demand." In 22nd COTA International Conference of Transportation Professionals. American Society of Civil Engineers, 2022. http://dx.doi.org/10.1061/9780784484265.084.

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Zhang, Fangda, Shannon Roberts, and Claudia Goldman. "A Survey Study Measuring People's Preferences Towards Automated and Non-Automated Ridesplitting." In Driving Assessment Conference. University of Iowa, 2019. http://dx.doi.org/10.17077/drivingassessment.1680.

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TU, Meiting, Ye LI, Wenxiang LI, et al. "Improving Ridesplitting Service Using Optimization Procedures on Shareability Network: A Case Study of Chengdu, China." In 2019 IEEE Intelligent Transportation Systems Conference - ITSC. IEEE, 2019. http://dx.doi.org/10.1109/itsc.2019.8917402.

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Chen, Zilin, Haiyang Yu, and Runkun Liu. "Exploring the Spatiotemporal Factors of Ridesplitting Demand Based on the Geographically and Temporally Weighted Regression." In 2021 IEEE Conference on Telecommunications, Optics and Computer Science (TOCS). IEEE, 2021. http://dx.doi.org/10.1109/tocs53301.2021.9688587.

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