AlignDrive: Aligned Lateral-Longitudinal Planning for End-to-End Autonomous Driving

TL;DR

AlignDrive introduces a cascaded, path-conditioned framework for autonomous driving that improves safety and coordination by explicitly coupling lateral and longitudinal planning, achieving state-of-the-art results on benchmark datasets.

Contribution

The paper presents a novel cascaded planning framework with anchor-based regression and a safety-critical data augmentation strategy for better autonomous driving.

Findings

Achieves a driving score of 89.07 on Bench2Drive

Success rate of 73.18% on the benchmark

Demonstrates improved safety and coordination over SOTA methods

Abstract

Practical autonomous driving requires models that generalize by reasoning through spatial-temporal possibilities to exclude unsafe outcomes. While state-of-the-art (SOTA) methods use parallel planning architectures, they fail to explicitly couple speed decisions with agent behavior along the driving path, leading to suboptimal coordination. To address this, we propose a cascaded framework that transforms longitudinal planning from an independent prediction task into a path-conditioned reasoning process. On the model side, we introduce an anchor-based regression design that conditions longitudinal prediction on the lateral drive path, and reformulate longitudinal planning as 1D displacement prediction along the path. This reduces geometric uncertainty and sharpens the model's focus on interaction-driven dynamics. On the data side, we introduce a planning-oriented data augmentation strategy that simulates rare safety-critical events by programmatically inserting agents and relabeling longitudinal targets to enforce collision avoidance. Evaluated on the challenging Bench2Drive benchmark, our method achieves SOTA performance with a driving score of 89.07 and a success rate of 73.18%, demonstrating significantly improved coordination and safety. Further evaluation on Fail2Drive confirms strong generalization to rare edge cases where parallel formulations typically fail. Project page:https://yanhaowu.github.io/AlignDrive/.