Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
}
TY - GEN
T1 - Modelling freeway networks by hybrid stochastic models
AU - Boel, R.
AU - Mihaylova, L.
N1 - pp. 182-187 IEEE catalog number: 04TH8730C ISBN: 0-7803-8311-7 doi:10.1109/IVS.2004.1336378
PY - 2004/7/15
Y1 - 2004/7/15
N2 - Traffic flow on freeways is a nonlinear, many-particle phenomenon, with complex interactions between the vehicles. This paper presents a stochastic hybrid model of freeway traffic at a time scale and at a level of detail suitable for on-line flow estimation, for routing and ramp metering control. The model describes the evolution of continuous and discrete state variables. The freeway is considered as a network of components, each component representing a different section of the network. The traffic model, designed from physical considerations, comprises sending and receiving functions describing the downstream and upstream propagation of perturbations to be controlled. Results from simulation investigations illustrate the effectiveness of our model compared to the well-known METANET model.
AB - Traffic flow on freeways is a nonlinear, many-particle phenomenon, with complex interactions between the vehicles. This paper presents a stochastic hybrid model of freeway traffic at a time scale and at a level of detail suitable for on-line flow estimation, for routing and ramp metering control. The model describes the evolution of continuous and discrete state variables. The freeway is considered as a network of components, each component representing a different section of the network. The traffic model, designed from physical considerations, comprises sending and receiving functions describing the downstream and upstream propagation of perturbations to be controlled. Results from simulation investigations illustrate the effectiveness of our model compared to the well-known METANET model.
KW - vehicular traffik
KW - aggregated models
KW - METANET
KW - compositional model DCS-publications-id
KW - inproc-430
KW - DCS-publications-credits
KW - dsp
KW - DCS-publications-personnel-id
KW - 121
U2 - 10.1109/IVS.2004.1336378
DO - 10.1109/IVS.2004.1336378
M3 - Conference contribution/Paper
SN - 0-7803-8311-7
SP - 182
EP - 187
BT - Intelligent Vehicles Symposium, 2004 IEEE
T2 - IEEE Intelligent Vehicle Symposium
Y2 - 14 June 2004 through 17 June 2004
ER -