Research on the Prospects of Intelligent Transportation Market from the Perspective of Energy Conservation and Emission Reduction

Shuli Tang; Meng He; Wenting Ai

doi:10.54691/fhss.v3i11.5751

Authors

Shuli Tang
Meng He
Wenting Ai

DOI:

https://doi.org/10.54691/fhss.v3i11.5751

Keywords:

Energy Saving and Emission Reduction; Intelligent Transportation; Structural Equation Model; Grey Prediction.

Abstract

In the context of energy conservation and emission reduction, transportation has become a key area of attention, and intelligent transportation plays an important role in it because of its function of effectively reducing emissions and saving resources. As a new mode of transportation, intelligent transportation still has some problems and challenges. Therefore, it is of great significance to study the future market development prospect of intelligent transportation. In this regard, this study takes Hefei City, Anhui Province as the research site, and permanent residents in four municipal districts of Hefei as the research object. First, structural equation model is used to analyze the influencing factors and paths of residents' perception norms, acceptance attitudes, subjective norms, government trust and acceptance willingness about intelligent transportation. And according to the data of intelligent transportation market size from 2011 to 2021, the grey prediction model is used to forecast the market development prospect of intelligent transportation in the next five years. The results show that the perception norm has an indirect positive impact on the residents' acceptance intention, and the intelligent transportation market has a good prospect. Finally, based on the research results, this paper puts forward some countermeasures and suggestions for the development of intelligent transportation.

Downloads

Download data is not yet available.

References

Huang Kaining. The role of computer vision technology in promoting the development of intelligent transportation systems, Journal of Huanghe University of Science and Technology, vol.24(2022),59-63.

Liu Na. Application of 5G based IoT technology in smart city construction, Journal of Cangzhou Normal University, vol.38(2022),54-57+83.

Li Jian. Intelligent Transportation Technology in Expressway Safety Management, Electronic Technology and Software Engineering, vol.07(2018),252.

Yue Ping. The Application of Intelligent Transportation in Urban Roads, Architecture Science, vol.38(2022), 190.

Qin Yuanyuan. Application Analysis of Big Data Technology in Intelligent Transportation, Volkswagen Standardization, vol.41(2022), 26-28.

Duan Peiyu. Analysis of the Development Status and Future Trends of Urban Intelligent Transportation Systems, Communication World, vol.24(2017), 352.

Yao Qiqi. Exploration and Practice of Intelligent Transportation Systems, Qinghai Transportation Technology, vol.32(2019), 11-15.

Song Like, Zhao Guochuan, Liu Ximan. Discussion on the Construction Strategy of Intelligent Transportation System in Small and Medium sized Towns, Intelligent Buildings and Smart Cities, vol.30(2023), 150-153.

Yang Xudong. Intelligent Transportation: A New Path for Urban Congestion Management, Smart China, vol.06(2020), 64-66.

Hamadeh Nizar, Karouni Ali and Farhat Zeinab. Intelligent transportation systems to mitigate road traffic congestion, Intelligenza Artificiale, vol.15(2022),91-104.

Aouedi Ons, Piamrat Kandaraj and Parrein Benoit. Intelligent Traffic Management in Next Generation Networks, Future Internet, vol.14(2022), 44-44.

Vikrant Mishra, Manish Kumar Yadav. IoT based Smart Transportation System: Implementation and Security Challenges, International Journal of Vehicle Structures & Systems, vol.14(2022), 567-571.

Tomaszewska Ewelina Julita. Barriers related to the implementation of intelligent transport systems in cities -the Polish local government's perspective, Engineering Management in Production and Services, vol.13(2021), 131-147.

Zhiyong Jing, Huanlong Zhang. Intelligent traffic assignment method of urban traffic network based on deep reinforcement learning, International Journal of Information and Communication Technology, vol.22(2023), 60-72.

Li Yang, Chu Chunchao, Chen Jianying. Research on Evaluation Index System of Energy Conservation and Emission Reduction in Highway Transportation and Its Application, Highway Transportation Science and Technology, vol.30(2013), 141-145+158.