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eclipse/sumo

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4,054 نجوم·1,736 تفرعات·Python·EPL-2.0·4 مشاهداتeclipse.dev/sumo↗

Sumo

SUMO is a microscopic traffic simulation suite designed to model the movement of individual vehicles and pedestrians across large-scale urban road networks. It functions as a multimodal transport simulator that integrates cars, pedestrians, bicycles, railways, and waterways within a single environment, supported by tools for road network generation and traffic demand modeling.

The project distinguishes itself through specialized toolsets for environmental impact analysis, which calculate vehicle emissions and energy consumption for electric and hybrid fleets. It provides comprehensive capabilities for modeling autonomous vehicles and automated driving systems, as well as a road network generator that imports industry-standard spatial data and XML definitions.

The system covers a broad range of operational areas including traffic infrastructure management for signal schedules, traffic flow calibration using real-world sensor data, and the generation of vehicle flow profiles via origin-destination matrices. It also supports the simulation of traffic incidents and the creation of custom sensing devices to monitor or influence traffic flow.

The software utilizes structured XML files for scenario definition and offers an external interface for real-time simulation control.

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.
  • محاكاة الروبوتات - Simulates road traffic.
  • Simulation Environments - Traffic simulation for large road networks.

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بدائل مفتوحة المصدر لـ Sumo

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    SUMO is a microscopic traffic simulator and road network generator designed to model the detailed movement of individual vehicles, pedestrians, and public transport. It serves as a multimodal transport simulator and an autonomous vehicle simulator, enabling the analysis of interactions between different transport modes and the testing of automated driving behaviors. The project distinguishes itself through its ability to couple simulations with external controllers and network simulators to model vehicle communication and autonomous control transitions. It supports the creation of simulation-

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    CARLA is an autonomous driving simulator and research environment designed for developing and validating self-driving software. It functions as an urban traffic simulator that generates realistic vehicle and pedestrian behavior and as a synthetic sensor data generator producing LiDAR, Radar, and camera data. The platform distinguishes itself through its deep integration with robotics frameworks, specifically providing native connectivity to ROS2 nodes for robotic control and data processing. It supports the training of driving models via imitation and reinforcement learning within a controlle

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    A/B Street is an open-source traffic simulation and urban planning tool that models how cars, bikes, and pedestrians move through real-world street networks. It imports data from OpenStreetMap to build detailed, lane-level road models, then runs discrete-event simulations to analyze travel times, delays, and congestion patterns across different infrastructure scenarios. The project provides an interactive map editor for modifying road geometry, lane configurations, traffic signals, and access restrictions, with full undo/redo support. Users can design low-traffic neighborhoods by placing moda

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الأسئلة الشائعة

ما هي وظيفة eclipse/sumo؟

SUMO is a microscopic traffic simulation suite designed to model the movement of individual vehicles and pedestrians across large-scale urban road networks. It functions as a multimodal transport simulator that integrates cars, pedestrians, bicycles, railways, and waterways within a single environment, supported by tools for road network generation and traffic demand modeling.

ما هي الميزات الرئيسية لـ eclipse/sumo؟

الميزات الرئيسية لـ eclipse/sumo هي: Microscopic Traffic Simulation, Multimodal Transport Simulation, Autonomous Vehicle Simulators, Behavioral Modeling, Integration Frameworks, Road Network Generators, Traffic Generation, Urban Traffic Simulation.

ما هي البدائل مفتوحة المصدر لـ eclipse/sumo؟

تشمل البدائل مفتوحة المصدر لـ eclipse/sumo: 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.