mlsanityData to 14 Oct 2026

TLD-READY: Traffic Light Detection -- Relevance Estimation and Deployment Analysis

arXiv 2409.07284 ↗First posted 11 Sep 2024cs.CV cs.LGcited by 5

Not on the map. Why?

Abstract (arXiv)

Effective traffic light detection is a critical component of the perception stack in autonomous vehicles. This work introduces a novel deep-learning detection system while addressing the challenges of previous work. Utilizing a comprehensive dataset amalgamation, including the Bosch Small Traffic Lights Dataset, LISA, the DriveU Traffic Light Dataset, and a proprietary dataset from Karlsruhe, we ensure a robust evaluation across varied scenarios. Furthermore, we propose a relevance estimation system that innovatively uses directional arrow markings on the road, eliminating the need for prior map creation. On the DriveU dataset, this approach results in 96% accuracy in relevance estimation. Finally, a real-world evaluation is performed to evaluate the deployment and generalizing abilities of these models. For reproducibility and to facilitate further research, we provide the model weights and code: https://github.com/KASTEL-MobilityLab/traffic-light-detection.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 23 of its 69 references that are in the map. First posted on arXiv 11 Sep 2024.

Builds on

23 of 69 references.

References · 23

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11 more
  1. 2023Robust Traffic Light Detection Using Salience-Sensitive Loss: Computational Framework and Evaluationscited by 11
  2. 2018Detecting Traffic Lights by Single Shot Detectioncited by 8
  3. 2019Traffic Light Recognition Using Deep Learning and Prior Maps for Autonomous Carscited by 8
  4. 2024CoCar NextGen: a Multi-Purpose Platform for Connected Autonomous Driving Researchcited by 8
  5. 2018A Hierarchical Deep Architecture and Mini-Batch Selection Method For Joint Traffic Sign and Light Detectioncited by 6
  6. 2024One Stack to Rule them All: To Drive Automated Vehicles, and Reach for the 4th levelcited by 5
  7. 2022Towards Real-time Traffic Sign and Traffic Light Detection on Embedded Systemscited by 3
  8. 2023Traffic Light Recognition using Convolutional Neural Networks: A Surveycited by 3
  9. 2020Deep traffic light detection by overlaying synthetic context on arbitrary natural imagescited by 1
  10. 2022DualCam: A Novel Benchmark Dataset for Fine-grained Real-time Traffic Light Detectioncited by 1
  11. 2023Small, but important: Traffic light proposals for detecting small traffic lights and beyondcited by 1

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 2.

5 papers.

  1. 2025Enhancing LLM-based Autonomous Driving with Modular Traffic Light and Sign Recognitioncited by 3
  2. 2025The ATLAS of Traffic Lights: A Reliable Perception Framework for Autonomous Drivingcited by 2
  3. 2025Fool the Stoplight: Realistic Adversarial Patch Attacks on Traffic Light Detectorscited by 1
  4. 2026Enhancing Multimodal Large Language Models for Safety-Critical Driving Video Analysiscited by 0
  5. 2026One Perception, All Maneuvers: Directional Traffic Signal Understanding for Maneuver-Level Signal Intent Predictioncited by 0