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Abstract

This paper presents the development of a combined equilibrium model for the simultaneous prediction of the destination and route choices that face suburban or rural automobile travelers. Destination choice is given by a dogit model to take into account the travel behavior of compulsory (work) and discretionary (nonwork) trips. A logit-based route-choice model was employed, with a stochastic user equilibrium principle, to develop route flows between each origin–destination pair. The natural logarithm of the denominator of the logit route-choice model (i.e., log-sum) was computed and fed back into the destination-choice step. Under this iterative process, the destination choice for discretionary trips responded to changing travel-cost conditions, whereas the destination choice for compulsory trips remained fixed in the study time period. The proposed combined destination- and route-choice (CDR) model can itself be reformulated as an equivalent convex programming problem with linear constraints, a great advantage from a computational perspective. The CDR model was applied empirically to a county-level network in New Jersey. The results encourage further applications of the CDR model to large-scale networks.

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References

Gaudry

M. J. I.

, and Dagenais

M. G.

The Dogit Model. Transportation Research Part B: Methodological, Vol. 13B, No. 2, 1979, pp. 105–111.

Sheffi

, and Daganzo

C. F.

Computation of Equilibrium over Transportation Networks: The Case of Disaggregate Demand Models. Transportation Science, Vol. 14, No. 2, 1980, pp. 155–173.

Siegel

J. D.

, de Cea

, Fernandez

J. E.

, Rodriguez

R. E.

, and Boyce

Comparisons of Urban Travel Forecasts Prepared with the Sequential Procedure and a Combined Model. Networks and Spatial Economics, Vol. 6, No. 2, 2006, pp. 135–148.

Wardrop

J. D.

Some Theoretical Aspects of Road Traffic Research. Proc. Institution of Civil Engineers, London, Vol. 2, No. 1, 1952, pp. 325–378.

Beckmann

M. J.

, McGuire

C. B.

, and Winsten

C. B.

Studies in the Economics of Transportation. Yale University Press, New Haven, Conn., 1956.

Evans

S. P.

Derivation and Analysis of Some Models for Combined Trip Distribution and Assignment. Transportation Research, Vol. 10, No. 1, 1976, pp. 37–57.

Erlander

Accessibility, Entropy and the Distribution and Assignment of Traffic. Transportation Research, Vol. 11, No. 3, 1977, pp. 149–153.

Chu

Y.-L.

Combined Trip Distribution and Assignment Model Incorporating Captive Travel Behavior. In Transportation Research Record 1285, TRB, National Research Council, Washington, D.C., 1990, pp. 70–77.

Fisk

, and Nguyen

Existence and Uniqueness Properties of an Asymmetric Two-Mode Equilibrium Model. Transportation Science, Vol. 15, No. 4, 1981, pp. 318–328.

10.

Florian

, and Spiess

On Binary Mode Choice/Assignment Models. Transportation Science, Vol. 17, No. 1, 1983, pp. 32–47.

11.

LeBlanc

, and Abdulaal

Combined Modal Split-Assignment and Distribution-Modal Split-Assignment Models with Multiple Groups of Travelers. Transportation Science, Vol. 16, No. 4, 1982, pp. 430–442.

12.

Florian

, and Nguyen

A Combined Trip Distribution, Modal Split and Trip Assignment Model. Transportation Research, Vol. 12, No. 4, 1978, pp. 241–246.

13.

Abrahamsson

, and Lundqvist

Formulation and Estimation of Combined Network Equilibrium Models with Applications to Stockholm. Transportation Science, Vol. 33, No. 1, 1999, pp. 80–100.

14.

Safwat

K. N.

, and Magnanti

T. L.

A Combined Trip Generation, Trip Distribution, Modal Split, and Trip Assignment Model. Transportation Science, Vol. 22, No. 1, 1988, pp. 14–30.

15.

de Cea

, Fernandez

, Dekock

, Soto

, and Friesz

ESTRAUS: Computer Package for Solving Supply–Demand Equilibrium Problems on Multimodal Urban Transportation Networks with Multiple User Classes. Presented at 82nd Annual Meeting of the Transportation Research Board, Washington, D.C., 2003.

16.

Oppenheim

A Combined Equilibrium Model of Urban Personal Travel and Goods Movements. Transportation Science, Vol. 27, No. 2, 1993, pp. 161–173.

17.

Boyce

D. E.

, Chon

K. S.

, Lee

Y. J.

, Lin

K. T.

, and LeBlanc

L. J.

Implementation and Computational Issues for Combined Models of Location, Destination, Mode, and Route Choices. Environment and Planning, Vol. 15A, No. 9, 1983, pp. 1219–1230.

18.

Boyce

D. E.

, and Lundqvist

Network Equilibrium Models of Urban Location and Travel Choices: Alternative Formulations for the Stockholm Region. Papers of the Regional Science Association, Vol. 61, 1987, pp. 93–104.

19.

Boyce

D. E.

, and Mattsson

L.-G.

Modeling Residential Location Choice in Relation to Housing Location and Road Tolls on Congested Urban Highway Networks. Transportation Research Part B: Methodological, Vol. 33, No. 8, 1999, pp. 581–591.

20.

Chu

Y.-L.

Network Equilibrium Model of Employment Location and Travel Choices. In Transportation Research Record: Journal of the Transportation Research Board, No. 1667, TRB, National Research Council, Washington, D.C., 1999, pp. 60–66.

21.

Ben-Akiva

, and Lerman

S. R.

Discrete Choice Analysis: Theory and Application to Travel Demand. MIT Press, Cambridge, Mass., 1985.

22.

Daly

Estimating Choice Models Containing Attraction Variables. Transportation Research Part B: Methodological, Vol. 16, No. 1, 1982, pp. 5–15.

23.

Bhat

C. R.

, Govindarajan

, and Pulugurta

Disaggregate Attraction-End Choice Modeling: Formulation and Empirical Analysis. In Transportation Research Record 1645, TRB, National Research Council, Washington, D.C., 1998, pp. 60–68.

24.

Sheffi

Urban Transportation Networks. Prentice Hall, Englewood Cliffs, N.J., 1985.

25.

Boyce

D. E.

, and Daskin

M. S.

Urban Transportation. In Design and Operation of Civil and Environmental Engineering Systems ( Revelle

, and Megarity

, eds.), John Wiley and Sons, New York, 1997, pp. 277–341.

26.

Dial

R. B.

A Probabilistic Multipath Traffic Assignment Algorithm Which Obviates Path Enumeration. Transportation Research, Vol. 5, No. 2, 1971, pp. 83–111.

27.

Leurent

F. M.

Curbing the Computational Difficulty of the Logit Equilibrium Assignment Model. Transportation Research Part B: Methodological, Vol. 31, No. 4, 1997, pp. 315–326.

Distribution and Assignment of Compulsory and Discretionary Traffic

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