journal article·2026-01-04Open access

Optimization of AEBS for Heavy Goods Vehicles Incorporating Driver’s Control and 3D Visibility of Vulnerable Road Users

Xi Zhang, Binglei Xie, Mingtao Song

Applied Sciences· Volume 16· Issue 1

Abstract

While an advanced emergency braking system (AEBS) significantly improves the safety of a heavy goods vehicle (HGV), current implementations face limitations including inadequate scenario coverage for vulnerable road users (VRUs), overriding driver control and limited human–machine collaboration mechanisms, and an insufficient consideration of blind spot challenges in HGVs. To improve the adaptability of the AEBS for HGVs, this study proposes and validates a novel 2D AEBS control algorithm incorporating driver’s control and 3D visibility of VRUs. The proposed algorithm is designed to firstly identify the motion state scenarios based on the spatial relationship between the HGV and VRU. Then, based on the scenario classification result, the proposed algorithm determines whether the HGV needs to brake in the current scenario according to the 2D time to collision for both entities to reach the potential collision area while maintaining their current speeds. Finally, for situations requiring braking, it evaluates whether safety can be ensured under three conditions: the ego vehicle in free driving, the ego vehicle under driver-controlled braking (considering the 3D visibility of the VRU), and the ego vehicle under 2D AEBS-controlled braking. According to the test results, the proposed algorithm can deal with the VRU crossing scenario and leverage the driver’s control capabilities while utilizing AEBS as a safety net function.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Autonomous Vehicle Technology and Safety · Traffic control and management · Vehicle Dynamics and Control Systems

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Architecture, Harbin Institute of Technology (Shenzhen), Shenzhen 518000, China

Institute of Transportation Safety Research, Shenzhen Technology Institute of Urban Public Safety, Shenzhen 518001, China

Funding

National Natural Science Foundation of China · Shenzhen Technology Institute of Urban Public Safety

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