Towards sustainable dynamic traffic management

Towards Sustainable Dynamic Traffic Management

L.J.J. Wismans

Goudappel Coffeng and University of Twente

Dynamic traffic management (DTM) measures are potentially powerful measures to not only

improve network efficiency, but also to reduce externalities of traffic (e.g. emissions of

substances, noise and safety). In current practice the deployment of DTM measures (or

DTM-strategies) focuses on improving efficiency on a local level. Further the assessment of

DTM is concerned with a number of predefined strategies where not always behavioral

responses are taken into account. However, because of spatial correlations DTM has network

wide impact, and the predefined set may not contain well performing strategies. So ideally the

assessment and selection of a DTM strategy should be based on several network performance

measures, including externalities, where potentially all possible strategies are considered. This

can be achieved by optimizing multiple objectives on a network level, where decision

variables are DTM measures. Previously no research has been done on how these objectives

relate and what strategies can be effective, taking traffic dynamics and route choice behavior

into account.

The Pareto optimal set of solutions, which is the outcome of a multi-objective optimization,

can be used to attain this knowledge. Formulating a single objective function that contains

elements of all individual objectives (i.e. a weighted sum of all objectives) does not provide

such knowledge and assumes that the compensation principle is known in advance, which is

not trivial. Therefore, the optimization problem is formulated as a multi-objective network

design problem. In this bi-level optimization problem road management authorities try to

optimize certain system objectives at the upper level. At the lower level, road users optimize

their own objectives. Both levels are interdependent, resulting in a difficult optimization

problem (NP-hard), identified as one of the most complex optimization problems in traffic

and transport to solve. A framework is developed, connecting the Streamline dynamic traffic

assignment model with externality models for emissions (ARTEMIS), noise (RMV and

AR-INTERIM-CM) and an accident risk based model for safety. An efficient method is developed

to model the dynamic traffic management measures time dependent. To solve the

optimization problem, various solution approaches are developed and compared,

incorporating response surface methods within multi-objective genetic algorithms to

accelerate the solution approach.

Applications show that the objectives efficiency, air quality (NO

emissions) and climate

(greenhouse gas emissions) are aligned, and are opposed to traffic safety and noise. Because

objectives in general are conflicting, there is not one single solution that optimizes all

objectives simultaneously, an optimization results in finding Pareto optimal solutions. To

choose the best compromise solution, a compensation principle is needed. Pruning methods to

reduce the Pareto optimal set retaining its main characteristics and ranking methods like cost

benefit analysis, analytical hierarchy process and ELECTRE III have been applied and

compared. Both types of methods may be useful to circumvent the possible difficulties in

analyzing the large Pareto optimal set in the decision making process. The availability of the

Pareto optimal solutions also offers the possibility to investigate the consequences of using a

certain method and the sensitivity of the weights per objective used within the multi criteria

decision making methods. Using cost benefit analysis shows for example that efficiency is the

dominant objective. Other multi criteria decision making methods are potentially more useful

*

Correspondence to: Luc J.J. Wismans, Transport Innovation and Modelling, Goudappel Coffeng BV, P.O. box 217, 7400 AD Deventer, T: +31570 666840, F: +31570 666888, E: lwismans@goudappel.nl

as a basis for an interactive decision support tool. Analyzing the Pareto optimal solutions

further shows that metering traffic on the right locations may be an effective strategy to

reduce externalities and further that lowering the speed limit not necessarily reduces

externalities on a network level.

Author’s publications

Journal publications

Wismans, L. J. J., E.C. van Berkum & M. C. J. Bliemer (2012). Optimization of externalities as objectives for dynamic traffic management, choices necessary. Submitted for EJTIR (under review).

Possel, B., Wismans, L.J.J., E.C. Van Berkum & M.C.J. Bliemer (2012). The multi-objective network design problem using minimizing externalities as objectives: comparison of a genetic algorithm and simulated annealing framework. Submitted for the Journal of advanced transportation (under review).

Brands, T., L.J.J. Wismans & E.C. van Berkum (2012). Application of pruning techniques on a Pareto front from a practical multi-objective optimization problem in traffic engineering. Submitted for Transportation Research A (under review).

Wismans, L.J.J., T. Brands, E.C. Van Berkum & M.C.J. Bliemer (2012). Pruning and ranking the Pareto optimal set, application for the dynamic multi-objective network design problem. Journal of advanced transportation Article first published online: 2 OCT 2012, DOI: 10.1002/atr.1212

.Wismans, L. J. J., E.C. van Berkum & M. C. J. Bliemer (2012). Accelerating solving the dynamic multi-objective network design problem using response surface methods. Journal of ITS (in press).

Wismans, L. J. J., E.C. van Berkum & M. C. J. Bliemer (2012). Effects of optimizing externalities using cooperating DTM measures on network level. Journal of ITS, accepted author version posted online: 01 Aug 2012, DOI:10.1080/15472450.2012.716639.

Wismans, L. J. J., E.C. van Berkum & M. C. J. Bliemer (2011). Comparison of multiobjective evolutionary algorithms for optimization of externalities using dynamic traffic management Measures. Transportation Research Record: Journal of the Transportation Research Board, No. 2263, pp. 163-173.

Wismans, L. J. J., E.C. van Berkum & M. C. J. Bliemer (2011). Modelling Externalities using Dynamic Traffic Assignment Models: a review. Transport Reviews, Volume 31, Issue 4, July 2011, pages 521-545 (ISSN 0144-1647). DOI:10.1080/01441647.2010.544856.

Wismans, L. J. J., E.C. van Berkum & M.C.J. Bliemer (2010). Wisselwerking tussen bereikbaarheid en externe effecten bij de optimalisatie van DVM maatregelen in verkeersnetwerken [Interaction between accessibility and external effects when optimizing DTM measures on network level (in Dutch)]. Tijdschrift Vervoerswetenschap, (ISSN 0040-7623), 46(2), 44-54

Books or bookchapters

Wismans, L.J.J. (2012). Towards sustainable dynamic traffic management. PhD thesis, ISBN: 978-90-5584-155-4, University of Twente, Enschede.

Wismans, L. J. J., E.C. van Berkum & M. C. J. Bliemer (2011). Dynamic Traffic Management Measures to Optimize Air Quality, Climate, Noise, Traffic Safety and Congestion: Effects of a Single Objective Optimization. Bookchapter (ed. J.A.EE. van Nunen, P. Huijbregts and P. Rietveld) Transitions towards sustainable mobility, chapter 16, Part 4, pp. 297-313, DOI: 10.1007/642-21192-8_16 (ISBN 978-3-642-21191-1, e-ISBN 978-3-642-21192-8), Springer, Heidelberg, Dordrecht London New York.

E.C. van Berkum & L.J.J. Wismans (2000). Network impact of dynamic traffic management measures. Bookchapter (ed. M.F.A.M. van Maarseveen) The African touch of transportation engineering & Management, Part 2: Road traffic information and control, pp. 111-120, (ISBN 90-365-1474-6), Civil Engineering, University of Twente, Enschede, The Netherlands.

Peer reviewed conference proceedings

Wismans, L.J.J., R.M.M. van den Brink, L.J.N Brederode, K.J. Zantema & E.C. van Berkum (2013). Comparison of estimation of emissions based on static and dynamic traffic assignment. In proceedings 92th Annual Meeting of the Transportation Research Board, January 2013, Washington, D.C., USA.

Bliemer, M, L. Brederode, L. Wismans & E.S Smits (2012). Quasi-dynamic traffic assignment: static traffic assignment with queueing and spillback. In proceedings 91th Annual Meeting of the Transportation Research Board, January 22-26, Washington, D.C., USA.

Wismans, L. J. J., E.C. van Berkum & M. C. J. Bliemer (2011). Accelerating solving the dynamic multi-objective network design problem using response surface methods. In proceedings Models and technologies for intelligent transportation systems conference (on CD-ROM), June 22-24, Leuven, Belgium.

Wismans, L. J. J., E.C. van Berkum & M. C. J. Bliemer (2011). Comparison of evolutionary multiobjective algorithms for the dynamic network design problem. In proceedings IEEE-ICNSC, 8th international conference on networking, sensing and control, April 11-13, Delft, The Netherlands, pp. 275-280 (on CD-rom). IEEE Catalog Number CFP11NSC-CDR (ISBN 978-1-4244-9572-6)

Wismans, L. J. J., E.C. van Berkum & M. C. J. Bliemer (2011). Comparison of multiobjective evolutionary algorithms for optimization of externalities using dynamic traffic management Measures. In proceedings 90th Annual Meeting of the Transportation Research Board, January 23-27, Washington, D.C., USA. Wismans, L. J. J., E.C. van Berkum & M. C. J. Bliemer (2010). Optimization of externalities using DTM

measures. A Pareto optimal multi objective optimization using the evolutionary algorithm SPEA2+. In T.P. Allkim, B. van Arem & T. Arentze e.a. (Eds.), 11th TRAIL Congress Connecting People - Integrating Expertise. (on CD-ROM). Delft: TRAIL (ISBN 978-90-5584-139-4).

Wismans, L. J. J., E.C. van Berkum & M. C. J. Bliemer (2010). Multi-objective network design problem: minimizing externalities using dynamic traffic management measures. In M. Bierlaire & C. Osorio (Eds.), Extended abstracts. Seventh triennial symposium on transportation analysis. Tristan Conference, June 2010, Tromso, Norway. (CD-rom). (pp. 808-811).

Wismans, L.J.J., E.C. van Berkum & M.C.J. Bliemer (2009) Multi-objective optimization of traffic systems using dynamic traffic management measures. In: G. Fusco (ed.) Models and technologies for intelligent transportation systems, proceedings of the international conference Models and technologies for intelligent transportation systems, Rome, Italy, pp. 29-34 (ISBN 978-88-548-3025-7).

Wismans, L. J. J. & E.C. van Berkum (2008). Multi-objective optimization of traffic systems. Modelling external effects. In proceedings 10th TRAIL Congress – TRAIL in perspective, October 14-15, Rotterdam, the Netherlands, (on CD-ROM, ISBN: 978-90-5584-107-3).