Smart Infrastructure: A Research Junction

TL;DR

This paper presents a smart infrastructure at an urban junction equipped with visual sensors and a digital twin to enhance traffic monitoring, support HAD system development, and improve safety through advanced data and AI training.

Contribution

Introduction of a novel intelligent infrastructure with multi-view cameras and a digital twin for research, data generation, and AI training in complex urban traffic environments.

Findings

Effective traffic monitoring of motorized and non-motorized vehicles.

Generation of real, synthetic, and augmented data for AI training.

Enhanced research capabilities for HAD systems and safety improvements.

Abstract

Complex inner-city junctions are among the most critical traffic areas for injury and fatal accidents. The development of highly automated driving (HAD) systems struggles with the complex and hectic everyday life within those areas. Sensor-equipped smart infrastructures, which can communicate and cooperate with vehicles, are essential to enable a holistic scene understanding to resolve occlusions drivers and vehicle perception systems for themselves can not cover. We introduce an intelligent research infrastructure equipped with visual sensor technology, located at a public inner-city junction in Aschaffenburg, Germany. A multiple-view camera system monitors the traffic situation to perceive road users' behavior. Both motorized and non-motorized traffic is considered. The system is used for research in data generation, evaluating new HAD sensors systems, algorithms, and Artificial Intelligence (AI) training strategies using real-, synthetic- and augmented data. In addition, the junction features a highly accurate digital twin. Real-world data can be taken into the digital twin for simulation purposes and synthetic data generation.