Abstract
Sustainability has been a challenging issue in the transportation industry, which necessitates obtaining a better measurement of transport sustainability performance. To appropriately measure performance, this paper presents a hybrid approach based on the hierarchical Bayesian network model (BNM) and Principal Component Analysis (PCA). The proposed BNM encompasses social, economic, environmental, and technological dimensions, where each dimension consists of various subdivisions. The Conditional Probability Table of the model is determined by PCA. Twenty-three sustainable transportation indicators involved in the different stages of traffic management are used to kick off the calculation and probability propagation. The results show that the overall transport sustainability of the selected cities is generally at a medium level, indicating that there is much room for further improvement. The sustainability-economic coupling analysis exhibits the nonlinear relationship between sustainability and economic level, revealing that economic growth does not necessarily lead to the enhancement of the transport sustainability. Additionally, the sensitivity analysis reveals that “Accessibility,” “Serviceability,” “Reliability,” and “Innovation” demonstrate an upward trend, indicating their great effect on transportation sustainability. Last, the policy implications of this study can not only offer a solution for the current needs of transportation systems but also serve as more transparent decision-making to develop a sustainable transportation system in the future.
Highlights
Socioeconomic progress, dramatic population growth, and urbanization in recent decades have led to continually growing demand for travel and freight in transportation worldwide, imposing a huge burden and significant challenges on transportation systems [1, 2]
Increasing transport volumes have resulted in the degradation of both human habitat and the environment; with 103.13 million tons of CO2 emissions in 2018, China was the largest CO2 emitter in the world [3], and transportation was responsible for 25% of the total energy-related CO2 emissions and 65% of the liquid fuel consumption in 2016. e degree of haze pollution suggested to be related to vehicle emissions has been considerably aggravated, especially in the Beijing
With input data prepared for root nodes, we can compute the probability of sustainability positive as yearly evaluation
Summary
Socioeconomic progress, dramatic population growth, and urbanization in recent decades have led to continually growing demand for travel and freight in transportation worldwide, imposing a huge burden and significant challenges on transportation systems [1, 2]. Chronic stresses such as severe congestion and inadequate accessibility critically affect social efficiency and quality of life and affect the sustainability of our transport systems and society as a whole [4]. In response to these disturbances, the United Nations introduced Sustainable Development Goals [5], and promoting sustainable industrialization was identified as one of the key factors to support economic development and human wellbeing [6]. To reach a sustainable transportation system, policy-makers are required to comprehensively and appropriately measure the current conditions and continuously monitor the sustainability performance of a transportation system [11]. Meaningful decision-making and proper action taking can lead to a more sustainable transportation system
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.