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eclipse/sumo

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4,054 estrellas·1,736 forks·Python·EPL-2.0·4 vistaseclipse.dev/sumo↗

Sumo

SUMO es una suite de simulación de tráfico microscópico diseñada para modelar el movimiento de vehículos individuales y peatones a través de redes viales urbanas a gran escala. Funciona como un simulador de transporte multimodal que integra coches, peatones, bicicletas, ferrocarriles y vías navegables dentro de un único entorno, respaldado por herramientas para la generación de redes viales y el modelado de la demanda de tráfico.

El proyecto se distingue por sus conjuntos de herramientas especializados para el análisis de impacto ambiental, que calculan las emisiones de los vehículos y el consumo de energía para flotas eléctricas e híbridas. Proporciona capacidades integrales para modelar vehículos autónomos y sistemas de conducción automatizada, así como un generador de redes viales que importa datos espaciales y definiciones XML estándar de la industria.

El sistema cubre una amplia gama de áreas operativas, incluyendo la gestión de infraestructura de tráfico para horarios de señales, la calibración del flujo de tráfico utilizando datos de sensores del mundo real y la generación de perfiles de flujo de vehículos a través de matrices origen-destino. También admite la simulación de incidentes de tráfico y la creación de dispositivos de detección personalizados para monitorear o influir en el flujo de tráfico.

El software utiliza archivos XML estructurados para la definición de escenarios y ofrece una interfaz externa para el control de la simulación en tiempo real.

Features

  • Microscopic Traffic Simulation - Models detailed movements of individual vehicles and pedestrians to analyze high-resolution urban traffic flow.
  • Multimodal Transport Simulation - Provides a multimodal simulation environment that models interactions between cars, pedestrians, bicycles, railways, and waterways.
  • Autonomous Vehicle Simulators - Simulates the behavior and impact of self-driving cars and automated driving systems on traffic safety.
  • Behavioral Modeling - Simulates autonomous vehicles by applying specific car-following models and removing human driving imperfections.
  • Integration Frameworks - Provides capabilities to equip simulated vehicles with automated driving systems and transition-of-control devices.
  • Road Network Generators - Includes a generator that converts standardized road network definitions into simulation environments.
  • Traffic Generation - Produces realistic patterns of vehicle and pedestrian movement using traffic counts and virtual population models.
  • Urban Traffic Simulation - Models individual vehicle interactions and pedestrian movement across various simulation levels in urban environments.
  • Graph-Based Route Computation - Calculates optimal paths between nodes in a road network using dynamic user assignment and intermodal routing.
  • Multi-Modal Network Models - Represents roads, rails, and pedestrian paths as a unified spatial graph for intermodal routing.
  • Origin-Destination Matrix Models - Implements mathematical models for generating traffic demand and trip chains based on origin-destination matrices.
  • Traffic Infrastructure Control - Provides real-time management of road infrastructure elements like speed limits and signal timings.
  • Traffic Infrastructure Management - Configures the behavior of traffic lights and signage to control vehicle flow throughout the simulation.
  • Vehicle Emissions Analysis - Calculates vehicle emissions and energy consumption for electric and hybrid fleets to analyze urban pollution.
  • Dynamic Routing Costing - Computes optimal vehicle paths by iteratively updating routing costs based on simulated congestion.
  • Scenario Definitions - Uses structured XML files to define reproducible road networks, demand patterns, and infrastructure configurations.
  • Stochastic Simulation Ensembles - Runs multiple simulation iterations with different random seeds to ensure statistically robust results.
  • Road Network Importers - Converts common map formats into compatible simulation layouts to build digital representations of road networks.
  • Movement Trace Generation - Converts simulation outputs into standardized spatial-temporal trajectory files for external vehicle movement analysis.
  • Geospatial Map Importers - Provides importers that transform raw geographic data formats into structured map models for simulation.
  • Simulation Logic Extensions - Provides interfaces to implement custom car-following models and lane-changing behaviors for simulation agents.
  • Traffic Scenario Modeling - Defines complex road interaction scenarios to facilitate the modeling of specific urban mobility environments.
  • Infrastructure Design - Evaluates the effectiveness of different traffic light schedules and road layouts via simulation.
  • Traffic Incident Modelling - Models road disruptions including accidents, blockages, and emergency lane closures to trigger vehicle re-routing.
  • Traffic Rule Configurations - Allows configuration of driving sides and specific behaviors like opposite-direction driving or lane-free traffic.
  • Coordinate Projections - Implements mathematical projections to translate geographic coordinates and satellite imagery into a simulation grid.
  • GPS Map Matching - Aligns raw GPS coordinate traces to the most likely path along a road network.
  • Ensemble Simulation Engines - Runs large-scale parallel simulation ensembles with different random seeds to generate statistical aggregates.
  • High-Performance Routing Calculations - Distributes shortest-path and re-routing calculations across multiple CPU cores for large-scale network performance.
  • Routing Parallelization - Distributes routing and re-routing computations across multiple CPU cores to increase processing speed.
  • Traffic Flow Calibration Tools - Adjusts vehicle speed and flow distributions based on real-world sensor data to ensure simulation accuracy.
  • Travel Demand Generators - Generates randomized trips and routes to simulate stochastic traffic patterns across the network.
  • Programmatic Simulation Control - Provides an external interface to modify simulation parameters and agent behaviors programmatically during execution.
  • External Control APIs - Exposes an external API that allows third-party programs to control simulation state and parameters in real-time.
  • Simulación de robótica - Simulates road traffic.
  • Simulation Environments - Traffic simulation for large road networks.

Historial de estrellas

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Ver las 30 alternativas a Sumo→

Preguntas frecuentes

¿Qué hace eclipse/sumo?

SUMO es una suite de simulación de tráfico microscópico diseñada para modelar el movimiento de vehículos individuales y peatones a través de redes viales urbanas a gran escala. Funciona como un simulador de transporte multimodal que integra coches, peatones, bicicletas, ferrocarriles y vías navegables dentro de un único entorno, respaldado por herramientas para la generación de redes viales y el modelado de la demanda de tráfico.

¿Cuáles son las características principales de eclipse/sumo?

Las características principales de eclipse/sumo son: Microscopic Traffic Simulation, Multimodal Transport Simulation, Autonomous Vehicle Simulators, Behavioral Modeling, Integration Frameworks, Road Network Generators, Traffic Generation, Urban Traffic Simulation.

¿Qué alternativas de código abierto existen para eclipse/sumo?

Las alternativas de código abierto para eclipse/sumo incluyen: eclipse-sumo/sumo — SUMO is a microscopic traffic simulator and road network generator designed to model the detailed movement of… carla-simulator/carla — CARLA is an autonomous driving simulator and research environment designed for developing and validating self-driving… a-b-street/abstreet — A/B Street is an open-source traffic simulation and urban planning tool that models how cars, bikes, and pedestrians… udacity/self-driving-car-sim — This project is an autonomous vehicle simulator designed to validate self-driving logic and train deep learning… facebookresearch/habitat-sim — Habitat-sim is a high-performance 3D simulation platform designed for training and benchmarking embodied AI agents… amin-tgz/awesome-carla — 👉 CARLA resources such as tutorial, blog, code and etc https://github.com/carla-simulator/carla.