Cordon Pricing Scheme Based on Macroscopic Fundamental Diagram and Distance

Abstract
Figure/Table
References (0)
Related Citation (15)

Abstract To alleviate traffic congestion in key areas, such as city centers, this study proposes an optimal pricing strategy that is based on the distance that users travel in a given cordon. The proposed strategy is derived from the theory of the macroscopic fundamental diagram (MFD). In this strategy, a non-negative, non-decreasing, and nonlinear distance-toll function is defined by a piecewise linear approximation method. A bi-level programming model is then constructed on the basis of the toll charge function and the characteristics of the MFD. The upper model considers the overall operating efficiency of the system and aims to maximize the outflow of the road network. The lower model assumes that users' route choice behavior complies with Wardrop's first principle to formulate a user equilibrium model under a fixed demand. In view of the non-additive property of path cost imposed by the nonlinear distance-toll function, the network transformation technique is used to realize the conversion between real networks and virtual networks. The Frank-Wolfe algorithm based on road segments is then used to solve the lower model. The verification of the reasonable feasibility of the pricing model and algorithm reveals that the implementation of cordon pricing schemes based on distance can make the outflow of the border area maintain the best level. Moreover, the obtained optimal charge function makes the system run efficiently. These results prove that the nonlinear optimal toll charge function is realistic and effective.

Key words： traffic engineering distance-based toll charge schemes macroscopic fundamental diagram bi-level programming model outflow

Received: 16 September 2020

Fund:Supported by the National Natural Science Foundation of China(No.61873216)

Corresponding Authors: LI Ru-xue E-mail: jianan_l@swjtu.edu.cn

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	LI Ru-xue
	LIU Lan

Cite this article:

LI Ru-xue,LIU Lan. Cordon Pricing Scheme Based on Macroscopic Fundamental Diagram and Distance[J]. Journal of Highway and Transportation Research and Development, 2021, 15(1): 81-88.

URL:

http://journal10.magtechjournal.com/Jwk_gljtkj_en/EN/ OR http://journal10.magtechjournal.com/Jwk_gljtkj_en/EN/Y2021/V15/I1/81

[1] PRUD'HOMME R, BOCAREJO J P. The London Congestion Charge:A Tentative Economic Appraisal[J]. Transport Policy, 2005, 12(3):279-287.
[2] TAN W H L, SUBRAMANIAM R. Congestion Control of Heavy Vehicles Using Electronic Road Pricing:The Singapore Experience[J]. International Journal of Heavy Vehicle Systems, 2006, 13(1/2):37-55.
[3] ELIASSON J, MATTSSON L G. Equity Effects of Congestion Pricing:Quantitative Methodology and a Case Study for Stockholm[J]. Transportation Research Part A:Policy & Practice, 2006, 40(7):602-620.
[4] VERHOEF E T. Second-best Congestion Pricing in General Networks. Heuristic Algorithms for Finding Second-best Optimal Toll Levels and Toll Points[J]. Transportation Research Part B:Methodological, 2002, 707-729.
[5] MAY A D, MILNE D S. Effects of Alternative Road Pricing Systems on Network Performance[J]. Transportation Research Part A:Policy and Practice, 2000, 34(6):407-436.
[6] MITCHELL G, NAMDEO A, MILNE D S, et al. The Air Quality Impact of Cordon and Distance Based Road User Charging:An Empirical Study of Leeds[J]. Atmospheric Environment, 2005, 39(33):6231-6242.
[7] HENSHER D A, PUCKETT S M. Assessing the Influence of Distance-based Charges on Freight Transporters[J]. Transport Reviews, 2008, 28(1):1-19.
[8] LAWPHONGPANICH S, YIN Y. Nonlinear Pricing on Transportation Networks[J]. Transportation Research Part C:Emerging Technologies, 2012, 20(1):218-235.
[9] MENG Q, LIU Z, WANG S. Optimal Distance Tolls Under Congestion Pricing and Continuously Distributed Value of Time[J]. Transportation Research Part E:Logistics & Transportation Review, 2012, 48(5):937-957.
[10] SUN Xin. Research on Distance-based Congestion Pricing Model and Algorithm[D]. Nanjing:Southeast University, 2015. (in Chinese)
[11] CHENG Qi-xiu. Research on Optimal Toll Rate of Distance-based Urban Road Dynamic Congestion Pricing[D]. Nanjing:Southeast University, 2016. (in Chinese)
[12] NAN Z, WARAICH R A, AXHAUSEN K W, et al. A Dynamic Cordon Pricing Scheme Combining the Macroscopic Fundamental Diagram and an Agent-based Traffic Model[J]. Transportation Research Part A:Policy & Practice, 2012, 46(8):1291-1303.
[13] SUN Yu-yan, SUN Li-min, ZHU Hong-song, et al. Activity Anomaly Detection Based on Vehicle Trajectory of Automatic Number Plate Recognition System[J]. Journal of Computer Research and Development, 2015, 52(8):1921-1929. (in Chinese)
[14] LIAO Da-bin, MA Wan-jing. Review of Macroscopic Fundamental Diagram of Network Traffic Flow[C]//Proceedings of the 7th China ITS Conference:Intelligent Transportation Technology. Beijing:Electronic Industry Press, 2012. (in Chinese)
[15] LI Xin. Study on Regional Road Network Perimeter Control Based on MFD[D].Chengdu:Southwest Jiaotong University, 2018. (in Chinese)
[16] DAGANZO C F, GONZALES E J, GAYAH V. Traffic Congestion in Networks, and Alleviating It with Public Transportation and Pricing[R]. Berkeley:University of California, 2011.
[17] DAGANZO C F. Urban Gridlock:Macroscopic Modeling and Mitigation Approaches[J]. Transportation Research B:Methodological, 2007, 41(1):49-62.
[18] YANG H, ZHANG X, MENG Q. Modeling Private Highways in Networks with Entry-exit Based Toll Charges[J]. Transportation Research Part B:Methodological, 2004, 38(3):191-213.