OpenDRIVE (.xodr)
May 25,2026

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Introduction

OpenDRIVE (.xodr) is an open standard file format used to describe static road networks in autonomous driving simulation. Based on the XML structure, it can precisely represent critical information such as road geometry, lane layout, and traffic signs. Maintained by the ASAM organization, it is primarily used in high‑definition maps and driving simulators, supporting data exchange between different simulation platforms and ensuring high realism and interoperability when testing and validating autonomous driving systems in virtual environments.

File Structure

The OpenDRIVE (.xodr) file is an XML‑based standardized format used to accurately describe road networks for autonomous driving simulation. Its file structure mainly consists of the following core components:

<OpenDRIVE> root element: The outermost container of every .xodr file. All other elements are nested within it, forming a complete road network description.
<header> metadata: Located at the beginning of the file, containing metadata such as version numbers (revMajor/revMinor), file name, creation date, author, geographic boundaries (south/north/west/east), and coordinate reference system (e.g., UTM projection).
<road> element: The core unit describing an individual road, each with a unique ID.
<junction> intersection: Describes the connection logic between multiple roads, defining the drivable path combinations at intersections and supporting complex traffic flow simulations.
Extensions and data precision: All floating‑point numbers use the IEEE 754 double‑precision format, with 17 significant digits recommended to ensure precision. Users can also define custom extension fields via <userData> to enhance flexibility.

Pros

Strong standardization and interoperability: Maintained by the ASAM organization, OpenDRIVE has become a de facto industry standard, enabling seamless exchange of road data between different simulation platforms (e.g., CARLA, PreScan).
High description accuracy: Capable of precisely modeling road geometry (e.g., clothoids, curvature changes), elevation, lateral slopes, and lane‑level details, meeting the high demands of autonomous driving perception and planning for environmental modeling.
Flexible and structured design: Supports complex road topologies, including loops, branches, merges, and multi‑level interchanges, with refined intersection connection logic implemented through <junction>.
Good extensibility: Allows custom fields via <userData> to adapt to specific system requirements (e.g., Apollo’s extensions to OpenDRIVE).
Compatible with both real and synthetic data: Can be used both for high‑definition road networks built from real maps and for generating virtual test scenarios, serving algorithm validation and extreme‑condition simulation.

Cons

Large file size and low parsing efficiency: Due to the XML format, data redundancy is significant. A one‑kilometer highway segment can generate tens of megabytes of data, affecting real‑time parsing performance on the vehicle side.
High production barrier: Editing typically relies on professional commercial software (e.g., RoadRunner). Open‑source toolchains have limited functionality, leading to high data production costs.
Static nature: Describes only static road information (e.g., lanes, signs) and does not include dynamic traffic participants or behavioral logic. It must be supplemented with standards such as OpenSCENARIO.
Poor planning‑friendliness: Its data structure is more oriented toward simulation rendering and sensor simulation than toward efficient topology queries and semantic expression required for autonomous driving decision‑making.
Complex coordinate system: Uses a hybrid of track coordinates (s, t, h) and inertial coordinates, increasing the learning and conversion overhead for developers.

Application Scenario

OpenDRIVE (.xodr) is primarily used in virtual simulation testing, high‑definition map construction, and path planning for autonomous driving, providing a precise static road network model for the system. It is widely adopted in simulation platforms such as CARLA, PreScan, and MATLAB, supporting digital modeling of complex urban roads, highways, and intersections. This ensures high realism and repeatability when validating perception, decision‑making, and control algorithms in virtual environments. Additionally, OpenDRIVE is used in the design and testing of cooperative vehicle‑infrastructure systems and intelligent transportation infrastructure.