M^4World: Controllable Driving World Model for AV Simulation

M^4World generates future surround-view video and synchronized LiDAR, with controls for object layout and appearance plus minute-long rollouts.

TL;DR — M^4World is a multimodal driving world model that generates surround-view video and synchronized LiDAR, supports object-level controls, and targets stable minute-long simulation streams.

Background: Why driving world models matter

Autonomous-driving systems need exposure to a wide range of road situations: common traffic patterns, unusual objects, difficult intersections, and rare events that are costly or risky to capture with real vehicles.

That demand has pushed research toward driving world models: generative systems that simulate how a driving scene evolves over time. Rather than producing a single image, these models generate future sensor streams that can be used for training, testing, or scenario editing.

The arXiv paper “M^4World: A Multi-view Multimodal Driving World Model for Interactive Object Manipulation and Minute-long Streaming” targets two gaps identified in its abstract: limited object-level controllability and instability over longer rollouts.

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