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Ying-en Ge and Malachy Carey 16 September 2004

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Presentation on theme: "Ying-en Ge and Malachy Carey 16 September 2004"— Presentation transcript:

1 A numerical comparison of three heuristic methods for path reassignment for dynamic user equilibrium
Ying-en Ge and Malachy Carey 16 September 2004 School of Management & Economics Queen’s University Belfast BT7 1NN 16 Sep 04 Transport Workshop at Queen's

2 Transport Workshop at Queen's
Introduction Dynamic traffic assignment (DTA) Network loading, with inflows/ assignment to spatial paths taken as given compute new path travel times Spatial path reassignment (based on travel-times from 1) Three methods for path reassignment Pair-wise swapping method Wu et al. (1998) method Lo & Szeto (2002) method 16 Sep 04 Transport Workshop at Queen's

3 Pair-wise swapping method
Step 1 At iteration n, for each time interval i, note the path with current highest cost (travel time) and path with lowest cost [ or variants of this, e.g. choose the same paths for several time intervals, etc.] Step 2 For each time interval i, switch proportion sin of inflow from higher cost to lower cost path sin = an where an is a chosen parameter (1 > an > 0) 16 Sep 04 Transport Workshop at Queen's

4 Transport Workshop at Queen's
Wu et al. (1998) method VI formulation The solution of the VI formulation is obtained by solving a series of quadratic programs below (1) where a is a positive constant. 16 Sep 04 Transport Workshop at Queen's

5 Transport Workshop at Queen's
Lo & Szeto (2002) method Step 1. Compute gipn and vin for all i and p by: gipn = max{0, fipn –b[hipn – (uipn –b(p fipn – di))]} vin = uin -b(p gipn – di) Step 2. Compute fipn and uin for all i and p fipn+1 = fipn - tn gn (fipn - gipn) uin+1 = uin - tn gn (uin - vin) where tn = dn( bm-1), dn(0,2) such that tn(0,1) and gn = r1/r2 with r1 = ip(fipn - gipn)2 +b2i(gipn–gi) and r2 = r1 + bi(p fipn – gipn)2 16 Sep 04 Transport Workshop at Queen's

6 Numerical experiments
Scenario Settings 2-link network Network loading Travel demand Convergence measure Maximum absolute difference Numerical experiments Effects of parameters in three methods Convergence measure values over iterations, and Accuracy of numerical solutions 16 Sep 04 Transport Workshop at Queen's

7 Transport Workshop at Queen's
16 Sep 04 Transport Workshop at Queen's

8 Transport Workshop at Queen's
16 Sep 04 Transport Workshop at Queen's

9 Minimum values of convergence measure
Maximum absolute difference Pair-wise swapping method (an = 1) Wu et al. method (a = 2) Lo & Szeto method (b = 0.5 and tn =1.0) 16 Sep 04 Transport Workshop at Queen's

10 Transport Workshop at Queen's
16 Sep 04 Transport Workshop at Queen's

11 Stopping iterations when given tolerances for
maximum absolute difference are satisfied tolerance for maximum absolute difference (5%) (1%) (0.5%) Pair-wise swapping method (an = 1) 17 112 Wu et al. method (a = 2) 290 Lo & Szeto method (b = 0.50 and tn = 1.00) 305 630 783 Note: The percentages given in the round brackets after each tolerance represent the proportion of a tolerance to the free-flow travel time of the shorter of the two paths [1.25 minutes]. 16 Sep 04 Transport Workshop at Queen's

12 Transport Workshop at Queen's
Summary Preferred parameter values Not able to set an arbitrarily small tolerance Performance of three methods 16 Sep 04 Transport Workshop at Queen's


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