Abstract
Energy is a necessary prerequisite for the operation of road traffic flow. Describing the phenomena of traffic flow from an energy perspective will promote energy conservation and emission reduction technologies. To clarify the application status and trend of traffic flow energy, this paper studies and summarizes the literature on traffic flow energy, classifies the traffic flow energy models into four groups, discusses the benefits and drawbacks and practical scenarios of various models, and suggests future research topics. The research revealed that the ultra-microscopic traffic flow energy model, based on the principle of vehicle energy flow, has high calculation accuracy but is hard to forecast traffic flow energy, which is adequate for estimating the energy of a single vehicle; The microscopic traffic flow energy model, which can predict traffic flow energy but with low calculation accuracy, considers interactions between fleet vehicles and helps evaluate the energy consumption features of various traffic flow states; The average characteristic parameter of the traffic flow is the key to the macroscopic traffic flow energy model, which calculates energy precisely for the uniform traffic flow but lacks the macroscopic traffic flow theoretical underpinnings; The simplified traffic flow energy model of traffic flow has a straightforward structure but the low calculation accuracy, making it suitable for assessing the effectiveness of the traffic flow model. Large-scale vehicle testing, the thorough integration of macro and micro traffic flow theories, and the decrease of computing complexity should be the main focuses of future research on traffic flow energy models.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Data availability
The datasets used and/or analyzed during the current study are available from the corresponding author upon reasonable request.
References
Ahn K, Rakha H, Trani A,Van Aerde M (2002) Estimating vehicle fuel consumption and emissions based on instantaneous speed and acceleration levels. J Transp Eng 128(2):182–190. https://doi.org/10.1061/(ASCE)0733-947X(2002)128:2(182)
Awal T, Kulik L, Ramamohanrao K (2013) A k-leader fuel-efficient traffic model. 2013 IEEE Intelligent Vehicles Symposium 1014–1021. https://doi.org/10.1109/IVS.2013.6629599
Ehsani M, Ahmadi A, Fadai D (2016) Modeling of vehicle fuel consumption and carbon dioxide emission in road transport. Renew Sust Energ Rev 53:1638–1648. https://doi.org/10.1016/j.rser.2015.08.062
Fiori C, Ahn K, Rakha A (2016) Power-based electric vehicle energy consumption model: Model development and validation. Appl Energ 168:257–268. https://doi.org/10.1016/j.apenergy.2016.01.097
Fiori C, Ahn K, Rakha HA (2018) Microscopic series plug-in hybrid electric vehicle energy consumption model: model development and validation. Transp Res D Transp Environ 63:175–185. https://doi.org/10.1016/j.trd.2018.04.022
Ghosh LE, Lu L, Ozer H, Ouyang Y, Al-Qadi IL (2019) Effects of pavement surface roughness and congestion on expected freeway traffic energy consumption. Transport Res Rec 1(2503):10–19. https://doi.org/10.3141/2503-02
Hunt SW, Odhams AMC, Roebuck RL, Cebon D (2011) Parameter measurement for heavy-vehicle fuel consumption modelling. P I Mech Eng D-J Aut 5(225):567–589. https://doi.org/10.1177/204129911039451
IEA (International Energy Agency) (2022a) World Energy Statistics and Balances. IEA, Paris, France
IEA (International Energy Agency) (2022b) Greenhouse Gas Emissions from Energy. IEA, Paris, France
Ivkovic I, Kaplanovic S and Milovanovic B (2017) Influence of road and traffic conditions on fuel consumption and fuel cost for different bus technologies. Therm Sci 1 Part B (21):693–706. https://doi.org/10.2298/TSCI160301135I
Jiménez-Palacios J L (1999) Understanding and quantifying motor vehicle emissions with vehicle specific power and TILDAS remote sensing. Massachusetts Institute of Technology, Boston, Massachusetts, USA
Jin Z, Cheng R, Ge H (2017) Nonlinear density wave and energy consumption investigation of traffic flow on a curved road. Chinese Phys B 11(26):110504. https://doi.org/10.1088/1674-1056/26/11/110504
Jin Z, Li Z, Cheng R, Ge H (2018) Nonlinear analysis for an improved car-following model account for the optimal velocity changes with memory. Physica A 507:278–288. https://doi.org/10.1016/j.physa.2018.05.043
Khallouk A, Binoua H, Lakouari N, Echab H, Marzoug R, Ez-Zahraouy H (2019) The energy dissipation at roundabout system. Int J Mod Phys B 04(33):1950007. https://doi.org/10.1142/S0217979219500073
Laarej A, Karakhi A, Khallouk A, Lakouari N, Ez-Zahraouy H (2021) Dissipation energy and satisfaction rate for a two-lane traffic model with two types of vehicles. Chinese J Phys 71:62–71. https://doi.org/10.1016/j.cjph.2020.05.024
Li Y, Zhong Z, Zhang K, Zheng T (2019) A car-following model for electric vehicle traffic flow based on optimal energy consumption. Physica A 533:122022. https://doi.org/10.1016/j.physa.2019.122022
Liang J, Teng W, Xue Y (2013) Study on the energy dissipation of macroscopic traffic models. Acta Phys Sin 02(62):422–429. https://doi.org/10.7498/aps.62.024706 (in Chinese)
Liebe C, Mahnke R, Kühne R (2011) From traffic breakdown to energy flow analysis. Transp Res Part C Emerg Technol 2(19):172–181. https://doi.org/10.1016/j.trc.2010.05.005
Liu K, Wang J, Yamamoto T, Morikawa T (2018) Exploring the interactive effects of ambient temperature and vehicle auxiliary loads on electric vehicle energy consumption. Appl Energ 227:324–331. https://doi.org/10.1016/j.apenergy.2017.08.074
Luin B, Petelin S, Al-Mansour F (2017) Modeling an impact of road geometric design on vehicle energy consumption. E3S Web Conf 22:107. https://doi.org/10.1051/e3sconf/20172200107
Luin B, Petelin S, Al-Mansour F (2019) Microsimulation of electric vehicle energy consumption. Energy 174:24–32. https://doi.org/10.1016/j.energy.2019.02.034
Lv C, Zhang J, Li Y, Yuan Y (2015) Mechanism analysis and evaluation methodology of regenerative braking contribution to energy efficiency improvement of electrified vehicles. Energ Convers Manage 92:469–482. https://doi.org/10.1016/j.enconman.2014.12.092
Mansour C, Bou Nader W, Breque F, Haddad M, Nemer M (2018a) Assessing additional fuel consumption from cabin thermal comfort and auxiliary needs on the worldwide harmonized light vehicles test cycle. Transp Res D Transp Environ 62:139–151. https://doi.org/10.1016/j.trd.2018.02.012
Mansour C, Haddad M, Zgheib E (2018b) Assessing consumption, emissions and costs of electrified vehicles under real driving conditions in a developing country with an inadequate road transport system. Transp Res D Transp Environ 63:498–513. https://doi.org/10.1016/j.trd.2018.06.012
Marcio DA (2019) Energy use and environmental impacts. Transportation 87https://doi.org/10.1016/B978-0-12-813454-2.00003-9
McNerney J, Needell ZA, Chang MT, Miotti M, Trancik JE (2017) TripEnergy: estimating personal vehicle energy consumption given limited travel survey data. Transport Res Rec 1(2628):58–66. https://doi.org/10.3141/2628-07
Needell ZA, Trancik JE (2018) Efficiently simulating personal vehicle energy consumption in mesoscopic transport models. Transport Res Rec 25(2672):163–173. https://doi.org/10.1177/0361198118798244
Odhams AMC, Roebuck RL, Lee YJ, Hunt SW, Cebon D (2010) Factors influencing the energy consumption of road freight transport. Proc Inst Mech Eng C J Mech Eng Sci 9(224):1995–2010. https://doi.org/10.1243/09544062JMES2004
Segel LA, Jackson JL (1972) Dissipative structure: an explanation and an ecological example. J Theor Biol 3(37):545
Shen HJ (2005) Energy theory and its primary application in the traffic and transportation system. J Shandong Jiaotong Univ 4(13):24–27. https://doi.org/10.3969/j.issn.1672-0032.2005.04.006 (in Chinese)
Sun X, Chen H, Wen Y, Liu Z, Chen H (2021) Congestion prediction based on dissipative structure theory: a case study of Chengdu, China. Math Probl Eng 2021:1–13. https://doi.org/10.1155/2021/6647273
Tan J, Gong L, Qin X (2019) Global optimality under internet of vehicles: strategy to improve traffic safety and reduce energy dissipation. Sustainability-Basel 17(11):4541. https://doi.org/10.3390/su11174541
Tang T, Yu Q, Liu K (2016) Analysis of the traffic running cost under random route choice behavior in a network with two routes. Physica A 449:408–415. https://doi.org/10.1016/j.physa.2016.01.003
Travesset-Baro O, Rosas-Casals M, Jover E (2015) Transport energy consumption in mountainous roads. A comparative case study for internal combustion engines and electric vehicles in Andorra. Transp Res D Transp Environ 34:16–26. https://doi.org/10.1016/j.trd.2014.09.006
Umemura K, Ebina K (2007) Energy dissipation burst on the traffic congestion. J Phys Soc Jpn 6(76):64004. https://doi.org/10.1143/JPSJ.76.064004
Wang J, Ding J, Shi Q, Kühne RD (2015) Lane-changing behavior and its effect on energy dissipation using full velocity difference model. Int J Mod Phys C 02(27):1650013. https://doi.org/10.1142/S0129183116500133
Wang SJ, Gu JJ (2004) Experimental analysis of an automotive air conditioning system with two-phase flow measurements. International Refrigeration and Air Conditioning Conference
Wu L, Ci Y, Chu J, Zhang H (2015) The influence of intersections on fuel consumption in urban arterial road traffic: a single vehicle test in Harbin, china. PLoS One 9(10):e137477. https://doi.org/10.1371/journal.pone.0137477
Xiao H, Huang H, Tang T (2016) An electricity consumption model for electric vehicular flow. Mod Phys Lett B 26(30):1650325. https://doi.org/10.1142/S0217984916503255
Xie Y, Li Y, Zhao Z, Dong H, Wang S, Liu J, Guan J, Duan X (2020) Microsimulation of electric vehicle energy consumption and driving range. Appl Energ 267:115081. https://doi.org/10.1016/j.apenergy.2020.115081
Xu X, Aziz HMA, Liu H, Rodgers MO, Guensler R (2020) A scalable energy modeling framework for electric vehicles in regional transportation networks. Appl Energ 269:115095. https://doi.org/10.1016/j.apenergy.2020.115095
Yang S, Deng C, Tang T, Qian Y (2013) Electric vehicle’s energy consumption of car-following models. Nonlinear Dyn 1–2(71):323–329. https://doi.org/10.1007/s11071-012-0663-0
Yao R, Sun L, Long M (2019) VSP-based emission factor calibration and signal timing optimisation for arterial streets. Iet Intell Transp Sy 1(13):228–241. https://doi.org/10.1049/iet-its.2018.5066
Zhao X, Ma J, Wang S, Ye Y, Wu Y, Yu M (2019) Developing an electric vehicle urban driving cycle to study differences in energy consumption. Environ Sci Pollut R 14(26):13839–13853. https://doi.org/10.1007/s11356-018-3541-6
Zhao X, Ye Y, Ma J, Shi P, Chen H (2020) Construction of electric vehicle driving cycle for studying electric vehicle energy consumption and equivalent emissions. Environ Sci Pollut R 30(27):37395–37409. https://doi.org/10.1007/s11356-020-09094-4
Zhu W, Zhang HM (2018) Analysis of mixed traffic flow with human-driving and autonomous cars based on car-following model. Physica A 496:274–285. https://doi.org/10.1016/j.physa.2017.12.103
Acknowledgements
This work was supported by the National Natural Science Foundation of China (42107114, 42177084), the Tianjin Science and Technology Plan Project (20YFZCSN01000), and the Fundamental Research Funds for the Central University of China (63221411).
Author information
Authors and Affiliations
Contributions
Bin Sun writing—original draft, visualization, and formal analysis, conceptualization, methodology, investigation, and data curation; Qijun Zhang writing—review and editing, supervision, and methodology; Chao Zou resources, conceptualization, and funding acquisition; Hui Tong investigation and methodology; Ning Wei investigation and methodology; Zhenyu Jia investigation, methodology; Hongjun Mao supervision, resources, validation, and funding acquisition.
Corresponding author
Ethics declarations
Ethics approval
Not applicable.
Consent to participate
Not applicable.
Competing interests
The authors declare no competing interests.
Additional information
Responsible Editor: Marcus Schulz
Publisher's note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Sun, B., Zhang, Q., Zou, C. et al. Review and prospect of research on road traffic flow energy model. Environ Sci Pollut Res 29, 81198–81209 (2022). https://doi.org/10.1007/s11356-022-23304-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11356-022-23304-1