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I recently encountered neatnet, a new street geometry processing toolkit for Python (by @martinfleis, @jGaboardi and @anastassia, among others). It's very well documented in this paper. Since UXsim performance decreases with increasing network complexity, I think it would be interesting of this type of simplification is also suitable for UXsim's mesoscopic traffic simulation.
Problem
UXsim works with street networks that are often transportation-focused (e.g., OSM data), containing detailed dual carriageways, roundabouts, and complex intersections. This creates two challenges:
Computational overhead: Complex networks significantly increase simulation time and memory usage
Unknown impact on accuracy: It's unclear whether this (and which) geometric detail meaningfully affects traffic flow results
Background
Relates to #95. Understanding how network representation affects simulation validity and performance is crucial for establishing UXsim's scientific credibility and practical applicability.
Proposed Solution
Integrate support for the neatnet package for automated network simplification, with comprehensive validation of the impact on simulation outcomes.
Implementation
Add neatnet integration: Support simplified networks as input option
Create validation framework: Compare simulation results between original and simplified networks
Document performance trade-offs: Establish guidelines for when simplification is appropriate
Validation Approach
importneatnetfromuxsimimportWorld# Compare same scenarios on both network typesoriginal_network=load_osm_network(city)
simplified_network=neatnet.neatify(original_network)
# Test key metrics:# - Travel time distributions# - Congestion location accuracy# - Route choice patterns# - Computational performance
Expected Outcomes
Usage guidelines: Clear recommendations on when to use simplified vs. detailed networks
Performance benchmarks: Quantified computational gains and accuracy trade-offs
I recently encountered neatnet, a new street geometry processing toolkit for Python (by @martinfleis, @jGaboardi and @anastassia, among others). It's very well documented in this paper. Since UXsim performance decreases with increasing network complexity, I think it would be interesting of this type of simplification is also suitable for UXsim's mesoscopic traffic simulation.
Problem
UXsim works with street networks that are often transportation-focused (e.g., OSM data), containing detailed dual carriageways, roundabouts, and complex intersections. This creates two challenges:
Background
Relates to #95. Understanding how network representation affects simulation validity and performance is crucial for establishing UXsim's scientific credibility and practical applicability.
Proposed Solution
Integrate support for the
neatnetpackage for automated network simplification, with comprehensive validation of the impact on simulation outcomes.Implementation
Validation Approach
Expected Outcomes