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Derivation of a fundamental diagram for urban traffic flow

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12 The European Physical Journal B<br />

defined as<br />

∫x 1<br />

dx ′ w(x ′ )f(x ′ )<br />

x 0<br />

∫x 1<br />

. (A.1)<br />

dx ′ w(x ′ )<br />

x 0<br />

In case <strong>of</strong> uni<strong>for</strong>m arrivals <strong>of</strong> vehicles, we have a functional<br />

relationship <strong>of</strong> the <strong>for</strong>m f(x) =a + bx <strong>for</strong> the travel time,<br />

and the weigth function is constant, i.e. w(x) =w. Here,<br />

a = Ti 0,<br />

x = ΔN i,andb =1/A i =1/(u i ̂Q i ). With x 0 =0<br />

and x 1 = ΔNi<br />

max , the <strong>for</strong>mula <strong>for</strong> the average travel time<br />

becomes<br />

w[(ax 1 + bx 2 1 /2) − (ax 0 + bx 2 0 /2)]<br />

= a + b x 1 + x 0<br />

,<br />

w(x 1 − x 0 )<br />

2<br />

(A.2)<br />

wherewehaveused(x 2 1 − x 2 0 )=(x 1 − x 0 )(x 1 + x 0 ).<br />

Inserting the above parameters, we obtain the previously<br />

derived result<br />

T i = T 0<br />

i<br />

+<br />

ΔN<br />

max<br />

i<br />

2u i ̂Qi<br />

. (A.3)<br />

When determining the average velocity Vi<br />

av , the function<br />

to average over is <strong>of</strong> the <strong>for</strong>m f(x) =c/(a + bx), where<br />

c = L i and the other parameters are as defined be<strong>for</strong>e. We<br />

use the relationship<br />

∫ x 1<br />

dx ′ wc<br />

a + bx ′ = wc (<br />

)<br />

ln |a + bx 1 |−ln |a + bx 0 |<br />

b<br />

x 0<br />

= wc ∣ ∣ ∣∣∣<br />

b ln a + bx 1 ∣∣∣<br />

.<br />

(A.4)<br />

a + bx 0<br />

Dividing this again by the normalization factor w(x 1 −x 0 )<br />

and inserting the above parameters finally gives<br />

V av<br />

i<br />

= L iu i ̂Qi<br />

ΔN max<br />

i<br />

(<br />

max<br />

i<br />

ln<br />

1+ΔN ∣ u i ̂Qi Ti<br />

0 ∣ ≈ L i<br />

Ti<br />

0 1 −<br />

ΔN<br />

max<br />

i<br />

2u i ̂Qi T 0<br />

i<br />

)<br />

,<br />

(A.5)<br />

wherewehaveusedln(1+x) ≤ x − x 2 /2. This <strong>for</strong>mula<br />

corrects the naive <strong>for</strong>mula<br />

V av<br />

i<br />

≈ L i<br />

T i<br />

=<br />

T 0<br />

i<br />

+<br />

L i<br />

ΔN max<br />

1<br />

2u i ̂Qi<br />

≈ L i<br />

T 0<br />

i<br />

(<br />

1 −<br />

)<br />

max<br />

ΔN1<br />

, (A.6)<br />

2u i ̂Qi Ti<br />

0<br />

wherewehaveused1/(1 + x) ≈ 1 − x. There<strong>for</strong>e, the<br />

above Taylor approximations <strong>of</strong> both <strong>for</strong>mulas agree, but<br />

higher-order approximations would differ. The <strong>for</strong>mulas<br />

in the main part <strong>of</strong> the paper result <strong>for</strong> Ni<br />

av = Ni max /2,<br />

which corresponds to the case δ i = 0 (i.e. f i − u i ).<br />

Generalizing the above approach to the case δ i > 0,<br />

we must split up the integrals into one over wc/(a + bx ′ )<br />

extending from x 0 =0tox 1 = ΔNi<br />

max and another one<br />

over wc/a from x 1 = ΔNi max to x 2 =(1− u i )A i T cyc =<br />

(1−u i )u i ̂Qi T cyc , where the specifications <strong>of</strong> a, b, andc are<br />

unchanged. Taking into account Vi 0 = L i /Ti 0,thisgives<br />

V av<br />

i<br />

= wL iu i ̂Qi ln |1+ΔN max<br />

i /(u i ̂Qi T 0<br />

i )| + Z<br />

w(1 − u i )u i ̂Qi T cyc , (A.7)<br />

where<br />

Z = wV 0<br />

i [(1 − u i )u i ̂Qi T cyc − ΔN max<br />

i ]. (A.8)<br />

Considering equation (15), we get<br />

V av<br />

i =<br />

L i<br />

(1 − u i )T cyc<br />

ln<br />

(<br />

1+(1− f i ) T cyc<br />

T 0<br />

i<br />

)<br />

+ Vi<br />

0 f i − u i<br />

.<br />

1 − u i<br />

(A.9)<br />

In second-order Taylor approximation, this results in<br />

[ ( 1 −<br />

Vi av ≈ Vi<br />

0 fi<br />

1 − (1 − f )<br />

i)T cyc<br />

1 − u i 2Ti<br />

0 + f ]<br />

i − u i<br />

,<br />

1 − u i<br />

(A.10)<br />

which can also be derived from equation (A.6), considering<br />

equation (15) and the percentage <strong>of</strong> delayed vehicles,<br />

which is given by equation (19).Thesameresultfollows<br />

from<br />

V av<br />

i =<br />

T 0<br />

i<br />

L i<br />

+ T av<br />

i<br />

≈ V 0<br />

i<br />

together with equation (21).<br />

References<br />

(1 − T i<br />

av )<br />

Ti<br />

0<br />

(A.11)<br />

1. D.C. Gazis, Traffic Theory (Kluwer Academic, Boston,<br />

2002)<br />

2. J. Esser, M. Schreckenberg, Int. J. Mod. Phys. B 8, 1025<br />

(1997)<br />

3. P.M. Simon, K. Nagel, Phys. Rev. E 58, 1286 (1998)<br />

4. K. Nagel, Multi-Agent Transportation Simulations, see<br />

http://www2.tu-berlin.de/fb10/ISS/FG4/archive/<br />

sim-archive/publications/book/<br />

5. M. Hilliges, W. Weidlich, Transpn. Res. B 29, 407 (1995)<br />

6. D. Helbing, J. Siegmeier, S. Lämmer, Networks and<br />

Heterogeneous Media 2, (2007)<br />

7. M. Cremer, J. Ludwig, Math. Comput. Simul. 28, 297ff<br />

(1986)<br />

8. C.F. Daganzo, Transpn. Res. B 29, 79 (1995)<br />

9. T. Nagatani, Phys. Rev. E 48, 3290 (1993)<br />

10. D. Chowdhury, A. Schadschneider, Phys. Rev. E 59,<br />

R1311 (1999)<br />

11. O. Biham, A.A. Middleton, D. Levine, Phys. Rev. A 46,<br />

R6124 (1992)<br />

12. J.-F. Zheng, Z.-Y. Gao, X.-M. Zhao, Phys. Stat. Mech.<br />

Appl. 385, 700 (2007)<br />

13. N.A. Irwin, M. Dodd, H.G. Von Cube, Highway Research<br />

Board Bulletin 347, 258 (1961)<br />

14. R.J. Smock, Highway Research Board Bulletin 347, 60<br />

(1962)<br />

15. W.W. Mosher, Highway Research Record 6, 41 (1963)<br />

16. Bureau <strong>of</strong> Public Roads, Traffic Assignment Manual<br />

(US Dept. <strong>of</strong> Commerce, Urban Planning Division,<br />

Washington, D.C., 1964)<br />

17. T.J. Soltmann, Highway Research Record 114, 122 (1965)<br />

18. K.B. Davidson, in Proceedings <strong>of</strong> the 3rd ARRB<br />

Conference, Part 1 (Australian Road Research Board,<br />

Melbourne, 1966), pp. 183–194

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