Abstract
Driving trucks in a queue behind each other and in close proximity, called platooning, has been recently under consideration as a novel and promising approach to reduce fuel consumption, which provides environmental and financial benefits. This method works since driving in the slipstream of another vehicle reduces the aerodynamic drag, and as a result, less energy or fuel is consumed. This paper addresses this problem with the realistic assumptions of existing time constraints for trucks to depart from the origin and arrive at their destination, and waiting as well as detour possibility. As this problem is NP-hard even in its very simplified forms, a new meta-heuristic solution methodology inspired from ant colony optimisation is proposed to deal with it. Some sample problems of small to large size are generated and solved with our solution approach. The analysis of results shows the satisfactory performance of this meta-heuristic and its superiority over the exact and our previous approach with genetic algorithm. In addition, we analyse how the final result is affected by changing the main inputs and configurations of the problem.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Alam A, Mårtensson J, Johansson KH (2015) Control engineering practice experimental evaluation of decentralized cooperative cruise control for heavy-duty vehicle platooning. Control Eng Pract 38:11–25
Al-kaisy A, Durbin C (2011) Platooning on two-lane two-way highways : an empirical investigation. Proc Soc Beh Sci 16:329–339
Baskar LD, De Schutter B, Hellendoorn H (2013) Optimal routing for automated highway systems. Transp Res Part C Emerg Technol 30:1–22
Bergenhem C, Hedin E, Skarin D (2012) Vehicle-to-vehicle communication for a platooning system. Proc Soc Behav Sci 48:1222–1233
Bhoopalam AK, Agatz N, Zuidwijk R (2018) Planning of truck platoons: a literature review and directions for future research. Transp Res Part B Methodol 107:212–228
Bonnet C, Fritz H (2000) Fuel consumption reduction in a platoon: experimental results with two electronically coupled trucks at close spacing. In: Intelligent vehicle technology, SP-1558
Box GEP, Wilson KB (1951) On the experimental attainment of optimum conditions. J R Stat Soc Ser B XIII(1):1–45
Dafflon B, Gechter F, Gruer P, Koukam A (2013) Vehicle platoon and obstacle avoidance: a reactive agent approach. IET Intell Transp. Syst 7(3):257–264
Davis LC (2013) The effects of mechanical response on the dynamics and string stability of a platoon of adaptive cruise control vehicles. Physica A 392(17):3798–3805
Dorigo M (1992) Optimization, learning and natural algorithms. Ph.D. thesis, Politecnico di Milano, Italy (April)
European Comission (2011) Roadmap to a single european transport area towards a competetive and resource efficient transport system. Transport white paper, Brussels, 2011
Gao S, Lim A, Bevly D (2016) An empirical study of DSRC V2V performance in truck platooning scenarios. Digit Commun Netw 2(4):233–244 Next Generation Wireless Communication Technologies
Haupt RL, Haupt Sue Ellen (2004) Practical genetic algorithms. Wiley interscience electronic collection. Wiley, Hoboken
Heikoop DD, de Winter JCF, van Arem B, Stanton NA (2017) Effects of platooning on signal-detection performance, workload, and stress: a driving simulator study. Appl Ergon 60:116–127
https://cran.r-project.org/web/packages/rsm/rsm.pdf. Accessed 10 Feb 2016
https://www.gams.com/latest/docs/S_LINDO.html. Accessed 2 Jan 2015
http://www.gams.com. Accessed 10 May 2010
http://www.hollywoodreporter.com/news/earthquake-twitter-users-learned-tremors-226481. Accessed 5 May 2017
Kammer C (2013) Coordinated heavy truck platoon routing using global and locally distributed approaches. Master’s degree project, KTH Electrical Engineering, Stockholm, Sweden (April)
Kianfar R, Falcone P, Fredriksson J (2015) A control matching model predictive control approach to string stable vehicle platooning. Control Eng Pract 45:163–173
Larsson E, Sennton G, Larson J (2015) The vehicle platooning problem: computational complexity and heuristics. Transp Res Part C 60:258–277
Li B (2017) Stochastic modeling for vehicle platoons (i): dynamic grouping behavior and online platoon recognition. Transp Res Part B: Methodol 95:364–377
Li B (2017) Stochastic modeling for vehicle platoons (ii): statistical characteristics. Transp Res Part B Methodol 95:378–393
Liang K-Y (2014) Coordination and routing for fuel-efficient heavy-duty vehicle platoon formation. Licentiate thesis in Electrical Engineering Stockholm, Sweden
Liang KY, Deng Q, Mrtensson J, Ma X, Johansson KH (June 2015) The influence of traffic on heavy-duty vehicle platoon formation. In: Intelligent vehicles symposium (IV), 2015. IEEE, pp 150–155
Linsenmayer S, Dimarogonas DV (July 2015) Event-triggered control for vehicle platooning. In: 2015 American control conference (ACC), pp 3101–3106
Liotta G (2006) Graph algorithms and applications 5. World Scientific Publishing Company, Singapore
Nourmohammadzadeh A, Hartmann S (2016) The fuel-efficient platooning of heavy duty vehicles by mathematical programming and genetic algorithm. In Martín-Vide C, Mizuki T, Vega-Rodríguez MA (eds) Theory and practice of natural computing: proceedings of 5th international conference, TPNC 2016, Sendai, Japan, December 12–13, 2016. Springer, pp 46–57
Omae M, Honma N, Usami K (2012) Flexible and energy-saving platooning control using a two-layer controller. Int J Intell Transp Syst Res 10(3):115–126
Schroten A, Warringa G, Bles M (2012) Marginal abatement cost curves for heavy duty vehicles. In: Background report. CE Delft, Delft
van de Hoef S, Johansson KH, Dimarogonas DV (2016) Computing feasible vehicle platooning opportunities for transport assignments**this work was supported by the companion eu project, the knut and alice wallenberg foundation, and the swedish research council. IFAC-PapersOnLine 49(3):43–48
van de Hoef S, Johansson KH, Dimarogonas DV (Sept 2015) Coordinating truck platooning by clustering pairwise fuel-optimal plans. In: 2015 IEEE 18th international conference on intelligent transportation systems, pp 408–415
Wang D, Pham M, Phampt CT (2005) Simulation study of vehicle platooning maneuvers with full-state tracking control. In: Simulation study of vehicle platooning maneuvers with full-state tracking control, pp 539–548
Wilcoxon F (1945) Individual comparisons by ranking methods. Biom Bull 1(6):80–83
Zaher ME, Gechter F, Hajjar M, Gruer P (2016) An interaction model for a local approach to vehicle platoons. J Auton Syst 13:91–113
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The Authors declare that they have no conflict of interest.
Human and animals participants
This article does not contain any studies with human participants or animals performed by any of the authors.
Additional information
Communicated by M. A. V. Rodríguezand.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Nourmohammadzadeh, A., Hartmann, S. Fuel-efficient truck platooning by a novel meta-heuristic inspired from ant colony optimisation. Soft Comput 23, 1439–1452 (2019). https://doi.org/10.1007/s00500-018-3518-x
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00500-018-3518-x