Investigating boundary effects of congestion charging in a single bottleneck scenario
Abstract
Many congestion charging projects charge traffic only within part of a day with predetermined congestion tolls. Demand peaks have been witnessed just around the time when the charge jumps up or down. Such peaks may not be desirable, in particular (a) when the resulting peaks are much higher than available capacities; (b) traffic speeding up to get into the charging zone causes more incidents just before the toll rises up to a higher level; or (c) traffic slowing down or parking on the roadside decreases road traffic throughput just before the toll falls sharply. We term these types of demand peaks ‘boundary effects’ of congestion charging. This paper investigates these effects in a bottleneck scenario and aims to design charging schemes that reduce undesired demand peaks. For this purpose, we observe and analyse the boundary effects utilising a bottleneck model under three types of toll profiles that are indicative of real charging schemes. The first type maintains a constant toll across the charging period, the second type allows the toll to increase from zero to a given maximum level and then decrease back to zero and the third type allows the toll to rise from zero to a given maximum level, remain at this level for a fixed period and then fall down to zero. This investigation shows that all three types of toll profiles can produce greater boundary peak demands than the bottleneck capacity. A significant contribution of this work is that instead of designing an optimal traffic congestion pricing scheme we analyse how existing sub-optimal congestion pricing schemes could be improved and suggest how observed problems may be overcome. Hence, we propose a set of extra requirements to supplement existing principles or requirements for design and implementation of congestion charging, which aim to reduce the adverse consequences of boundary effects. Concluding remarks are made on implications of this investigation for the improvement of existing congestion charging projects and for future research.
First published online 13 July 2015
Keyword : bottleneck models, congestion charging, boundary issues
How to Cite
Ge, Y.-E., Stewart, K., Liu, Y., Tang, C., & Liu, B. (2018). Investigating boundary effects of congestion charging in a single bottleneck scenario. Transport, 33(1), 77-91. https://doi.org/10.3846/16484142.2015.1062048
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Ge, Y. E.; Sun, B. R.; Zhang, H. M.; Szeto, W. Y.; Zhou, X. 2014. A comparison of dynamic user optimal states with zero, fixed and variable tolerances, Networks and Spatial Economics. http://dx.doi.org/10.1007/s11067-014-9243-9
Ge, Y. E.; Zhou, X. 2012. An alternative definition of dynamic user optimum on signalised road networks, Journal of Advanced Transportation 46(3): 236–253. http://dx.doi.org/10.1002/atr.207
Hau, T. D. 2006. Congestion charging mechanisms for roads, part I – conceptual framework, Transportmetrica 2(2): 87–116. http://dx.doi.org/10.1080/18128600608685658
Hendrickson, C.; Kocur, G. 1981. Schedule delay and departure time decisions in a deterministic model, Transportation Science 15(1): 62–77. http://dx.doi.org/10.1287/trsc.15.1.62
Laih, C.-H. 2004. Effects of the optimal step toll scheme on equilibrium commuter behaviour, Applied Economics 36(1): 59–81. http://dx.doi.org/10.1080/0003684042000177206
Laih, C.-H. 1994. Queueing at a bottleneck with single- and multi-step tolls, Transportation Research Part A: Policy and Practice 28(3): 197–208. http://dx.doi.org/10.1016/0965-8564(94)90017-5
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Lin, J.; Ge, Y. E. 2006. Impacts of traffic heterogeneity on roadside air pollution concentration, Transportation Research Part D: Transport and Environment 11(2): 166–170. http://dx.doi.org/10.1016/j.trd.2005.12.001
Lindsey, R. 2010. Reforming road user charges: a research challenge for regional science, Journal of Regional Science 50(1): 471–492. http://dx.doi.org/10.1111/j.1467-9787.2009.00639.x
Lindsey, R. 2006. Do economists reach a conclusion on road pricing? The intellectual history of an idea, Econ Journal Watch 3(2): 292–379.
Lindsey, C. R.; Van den Berg, V. A. C.; Verhoef, E. T. 2012. Step tolling with bottleneck queuing congestion, Journal of Urban Economics 72(1): 46–59. http://dx.doi.org/10.1016/j.jue.2012.02.001
Lo, H. K.; Szeto, W. Y. 2002. A cell-based variational inequality formulation of the dynamic user optimal assignment problem, Transportation Research Part B: Methodological 36(5): 421–443. http://dx.doi.org/10.1016/S0191-2615(01)00011-X
Long, J.; Gao, Z.; Szeto, W. Y. 2011. Discretised link travel time models based on cumulative flows: formulations and properties, Transportation Research Part B: Methodological 45(1): 232–254. http://dx.doi.org/10.1016/j.trb.2010.05.002
LTA. 2013. ONE.MOTORING Services. Land Transport Authority (LTA). Available from Internet: http://www.onemotoring.com.sg/publish/onemotoring/en/imap.html
Mahmassani, H.; Herman, R. 1984. Dynamic user equilibrium departure time and route choice on idealized traffic arterials, Transportation Science 18(4): 362–384. http://dx.doi.org/10.1287/trsc.18.4.362
Mounce, R.; Carey, M. 2011. Route swapping in dynamic traffic networks, Transportation Research Part B: Methodological 45(1): 102–111. http://dx.doi.org/10.1016/j.trb.2010.05.005
Newell, G. F. 1993a. A simplified theory of kinematic waves in highway traffic, part I: general theory, Transportation Research Part B: Methodological 27(4): 281–287. http://dx.doi.org/10.1016/0191-2615(93)90038-C
Newell, G. F. 1993b. A simplified theory of kinematic waves in highway traffic, part II: queueing at freeway bottlenecks, Transportation Research Part B: Methodological 27(4): 289–303. http://dx.doi.org/10.1016/0191-2615(93)90039-D
Newell, G. F. 1993c. A simplified theory of kinematic waves in highway traffic, part III: multi-destination flows, Transportation Research Part B: Methodological 27(4): 305–313. http://dx.doi.org/10.1016/0191-2615(93)90040-H
Newell, G. F. 1988. Traffic flow for the morning commute, Transportation Science 22(1): 47–58. http://dx.doi.org/10.1287/trsc.22.1.47
Nie, Y. 2012. Transaction costs and tradable mobility credits, Transportation Research Part B: Methodological 46(1): 189–203. http://dx.doi.org/10.1016/j.trb.2011.10.002
Ramadurai, G.; Ukkusuri, S. V.; Zhao, J.; Pang, J.-S. 2010. Linear complementarity formulation for single bottleneck model with heterogeneous commuters, Transportation Research Part B: Methodological 44(2): 193–214. http://dx.doi.org/10.1016/j.trb.2009.07.005
Richards, P. I. 1956. Shock waves on the highway, Operations Research 4(1): 42–51. http://dx.doi.org/10.1287/opre.4.1.42
Salmon, F. 2010. The Congestion Pricing Debate. 4 June 2010. Available from Internet: http://blogs.reuters.com/felixsalmon/2010/06/04/the-congestion-pricing-debate-cont
Seik, F. T. 1997. An effective demand management instrument in urban transport: the area licensing scheme in Singapore, Cities 14(3): 155–164. http://dx.doi.org/10.1016/S0264-2751(97)00055-3
Small, K. A. 1982. The scheduling of consumer activities: work trips, The American Economic Review 72(3): 467–479.
Small, K. A.; Verhoef, E. T. 2007. The Economics of Urban Transportation. Routledge. 296 p.
STA. 2013. Congestion taxes in Stockholm and Gothenburg. Swedish Transport Agency (STA). Available from Internet: http://www.transportstyrelsen.se
Szeto, W. Y.; Lo, H. K. 2004. A cell-based simultaneous route and departure time choice model with elastic demand, Transportation Research Part B: Methodological 38(7): 593–612. http://dx.doi.org/10.1016/j.trb.2003.05.001
Teodorović, D.; Triantis, K.; Edara, P.; Zhao, Y.; Mladenović, S. 2008. Auction-based congestion pricing, Transportation Planning and Technology 31(4): 399–416. http://dx.doi.org/10.1080/03081060802335042
TfL. 2013. Congestion Charge. Transport for London (TfL). Available from Internet: http://www.tfl.gov.uk/roadusers/congestioncharging
TfL. 2008. Central London Congestion Charging: Impacts Monitoring. Sixth Annual Report. Transport for London (TfL). 227 p. Available from Internet: https://www.tfl.gov.uk/cdn/static/cms/documents/central-london-congestion-charging-impacts-monitoring-sixth-annual-report.pdf
Tian, L.-J.; Yang, H.; Huang, H.-J. 2013. Tradable credit schemes for managing bottleneck congestion and modal split with heterogeneous users, Transportation Research Part E: Logistics and Transportation Review 54: 1–13. http://dx.doi.org/10.1016/j.tre.2013.04.002
Tsekeris, T.; Voß, S. 2009. Design and evaluation of road pricing: state-of-the-art and methodological advances, Netnomics: Economic Research and Electronic Networking 10(1): 5–52. http://dx.doi.org/10.1007/s11066-008-9024-z
Van den Berg, V. A. C. 2014. Coarse tolling with heterogeneous preferences, Transportation Research Part B: Methodological 64: 1–23. http://dx.doi.org/10.1016/j.trb.2014.03.001
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