Stochastic Shockwave Dynamics in First-Order Traffic Flow
Abstract
Moving congestion fronts vary across realizations even when the traffic-flow law is fixed. This paper develops a generator-based formulation of the Lighthill--Whitham--Richards (LWR) model with random initial density and a deterministic fundamental diagram. Randomness enters through the initial spatial density field; every realization follows the same conservation law. For a smooth strictly concave fundamental diagram, we adapt established one-sided spatial Markov closure to traffic variables under the stated spatial-process and regularity assumptions, and derive a kinetic balance for physically normalized front intensities. Evolving the spatial generator provides density laws and congestion-front statistics without solving a road-grid problem for every realization. The formulation is continuous in physical space and time, while its numerical implementation approximates density state and integrates physical time. Four experiments distinguish deterministic consistency from stochastic comparison. Riemann and signal examples recover independently constructed exact LWR solutions. Smooth strictly concave approximations approach the deterministic triangular-diagram signal solution over the tested finite horizons; this does not establish stochastic closure at contacts or the capacity kink. A matched Monte Carlo Godunov ensemble evaluates front counts, sizes, mergers, and density distributions. The evolved generator also yields an instantaneous travel-time distribution for a frozen density field, compared with the same functional of the matched Godunov profiles. This quantity is not experienced travel time through evolving traffic. Resolution checks identify remaining normalization and small-front-loss effects. The contribution is direct evolution and interpretation of traffic-state and front distributions under a fixed first-order traffic law.
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BibTeX
@misc{zhang2026stochastic,
title = {{Stochastic Shockwave Dynamics in First-Order Traffic Flow}},
author = {Yanlin Zhang and Alireza Talebpour},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2610.23022},
eprint = {2610.23022},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2610.23022},
}
RIS
TY - UNPB
TI - Stochastic Shockwave Dynamics in First-Order Traffic Flow
AU - Yanlin Zhang
AU - Alireza Talebpour
PY - 2026
DA - 2026/10/16
PB - arXiv
DO - 10.48550/arxiv.2610.23022
UR - https://arxiv.org/abs/2610.23022
AB - Moving congestion fronts vary across realizations even when the traffic-flow law is fixed. This paper develops a generator-based formulation of the Lighthill--Whitham--Richards (LWR) model with random initial density and a deterministic fundamental diagram. Randomness enters through the initial spatial density field; every realization follows the same conservation law. For a smooth strictly concave fundamental diagram, we adapt established one-sided spatial Markov closure to traffic variables under the stated spatial-process and regularity assumptions, and derive a kinetic balance for physically normalized front intensities. Evolving the spatial generator provides density laws and congestion-front statistics without solving a road-grid problem for every realization. The formulation is continuous in physical space and time, while its numerical implementation approximates density state and integrates physical time. Four experiments distinguish deterministic consistency from stochastic comparison. Riemann and signal examples recover independently constructed exact LWR solutions. Smooth strictly concave approximations approach the deterministic triangular-diagram signal solution over the tested finite horizons; this does not establish stochastic closure at contacts or the capacity kink. A matched Monte Carlo Godunov ensemble evaluates front counts, sizes, mergers, and density distributions. The evolved generator also yields an instantaneous travel-time distribution for a frozen density field, compared with the same functional of the matched Godunov profiles. This quantity is not experienced travel time through evolving traffic. Resolution checks identify remaining normalization and small-front-loss effects. The contribution is direct evolution and interpretation of traffic-state and front distributions under a fixed first-order traffic law.
ER -