# autonomousvision/navsim

[CoRL '25] Pseudo-Simulation for Autonomous Driving; [NeurIPS '24] NAVSIM: Data-Driven Non-Reactive Autonomous Vehicle Simulation and Benchmarking

Repository: https://github.com/autonomousvision/navsim
Canonical: https://ross.abutalabs.com/products/navsim
Language: Python
License: Apache-2.0
License Family: permissive
Topics: autonomous-driving, planning, self-driving
Last push: 2025-10-27T21:19:43+00:00

## Health v2 (maintenance only)
Score: 50/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 49, release rhythm 40, longevity 68
- inputs: {"age_days": 956, "days_push": 310, "days_rel": 492, "gap_med": 0, "n_releases_24m": 10}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1076, forks 128 (observed 2026-08-28T04:03:29.432623+00:00)

## What it is
NAVSIM is a data-driven pseudo-simulation framework and benchmark for autonomous vehicle planning, evaluating driving agents non-reactively on logged sensor data. It powers public leaderboards (navtest/navhard) for end-to-end driving research from the University of Tübingen, NVIDIA Research, and collaborators.

## Use cases
- benchmark end-to-end autonomous driving planners
- evaluate driving policies without full reactive simulation
- run pseudo-simulation on logged driving datasets
- submit entries to the NAVSIM challenge leaderboard
- train and validate self-driving planning models
- compare planning agents on standardized metrics

## When to choose
- you research autonomous driving planning and need a standardized benchmark
- you want leaderboard-comparable evaluation without building a full simulator
- you work with nuPlan/OpenScene-style logged sensor data

## When to avoid
- you need closed-loop reactive simulation with interactive traffic
- you need a production-grade driving simulator for game or robotics deployment
- you don't work with large autonomous driving datasets

## Facets
- artifact type: library
- maturity: active
- function: simulation, machine-learning, benchmarking, computer-vision
- domain: autonomous-vehicles, machine-learning, simulation, computer-vision
- platform: python
- tags: autonomous-driving, planning, self-driving, pseudo-simulation, benchmark, navsim, dataset, linux

## Member repositories
- autonomousvision/navsim (main) score 50

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:03:29.432623+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T06:53:20.949610+00:00, confidence not recorded.
  - readme: https://github.com/autonomousvision/navsim (fetched 2026-08-28T04:03:29.432623+00:00, sha e591f2f17907)
- Data as of 2026-08-30T08:39:29.467469+00:00.