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All projectsSHRADDHA PALURI / 2024
Mathematical Modeling · SAMPLE PROJECT

Modeling Urban Flow

Using graph theory and discrete-event simulation to study traffic bottlenecks and adaptive signal timing.

PythonNetworkXSciPy
Illustrative profile · Academic records, achievements, and affiliations are sample data pending verification.
ROLE / AUTHORSHIP
Model designer
PROJECT STATUS
Completed
RECORD YEAR
2024 · Sample record
01

Problem & objective

Using graph theory and discrete-event simulation to study traffic bottlenecks and adaptive signal timing.

02

Methods & evaluation

Sample method: construct a four-intersection road graph, sample traffic demand, run discrete-event queue simulations, and compare constrained adaptive timing with fixed-cycle signals.

03

System architecture

  1. 01

    Road-network graph

  2. 02

    demand sampler

  3. 03

    queue simulation

  4. 04

    constrained signal optimization.

04

Results & findings

ILLUSTRATIVE RESULT · NOT VERIFIED

Sample simulation: median wait time decreased 18% against fixed-cycle timing on a synthetic four-intersection network.

05

Limitations & pending evidence

Results are illustrative and use a synthetic network. Real-world traffic calibration, repeated-seed uncertainty, and validation against observed traffic are pending.

06

Documentation & links

Repository · URL pendingSchematics · URL pendingLive demo · URL pending
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