mlsanityData to 14 Oct 2026

Pedestrian Behavior Maps for Safety Advisories: CHAMP Framework and Real-World Data Analysis

arXiv 2305.04506 ↗First posted 8 May 2023cs.CV cs.AIcited by 9

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Abstract (arXiv)

It is critical for vehicles to prevent any collisions with pedestrians. Current methods for pedestrian collision prevention focus on integrating visual pedestrian detectors with Automatic Emergency Braking (AEB) systems which can trigger warnings and apply brakes as a pedestrian enters a vehicle's path. Unfortunately, pedestrian-detection-based systems can be hindered in certain situations such as night-time or when pedestrians are occluded. Our system addresses such issues using an online, map-based pedestrian detection aggregation system where common pedestrian locations are learned after repeated passes of locations. Using a carefully collected and annotated dataset in La Jolla, CA, we demonstrate the system's ability to learn pedestrian zones and generate advisory notices when a vehicle is approaching a pedestrian despite challenges like dark lighting or pedestrian occlusion. Using the number of correct advisories, false advisories, and missed advisories to define precision and recall performance metrics, we evaluate our system and discuss future positive effects with further data collection. We have made our code available at https://github.com/s7desai/ped-mapping, and a video demonstration of the CHAMP system at https://youtu.be/dxeCrS_Gpkw.

Key facts. Cited by 9 papers in the map (data through 14 Oct 2026). Builds on 11 of its 44 references that are in the map. First posted on arXiv 8 May 2023.

Builds on

11 of 44 references.

References · 11

  1. 2020Trajectory Forecasts in Unknown Environments Conditioned on Grid-Based Planscited by 72
  2. 2022A9-Dataset: Multi-Sensor Infrastructure-Based Dataset for Mobility Researchcited by 40
  3. 20193D BAT: A Semi-Automatic, Web-based 3D Annotation Toolbox for Full-Surround, Multi-Modal Data Streamscited by 36
  4. 2020Trajectory Prediction in Autonomous Driving with a Lane Heading Auxiliary Losscited by 30
  5. 2019Scene Compliant Trajectory Forecast with Agent-Centric Spatio-Temporal Gridscited by 24
  6. 2023Salient Sign Detection In Safe Autonomous Driving: AI Which Reasons Over Full Visual Contextcited by 14
  7. 2021On Salience-Sensitive Sign Classification in Autonomous Vehicle Path Planning: Experimental Explorations with a Novel Datasetcited by 13
  8. 2019Understanding Pedestrian-Vehicle Interactions with Vehicle Mounted Vision: An LSTM Model and Empirical Analysiscited by 4
  9. 2015Deep convolutional neural networks for pedestrian detectioncited by 3
  10. 2022From Pedestrian Detection to Crosswalk Estimation: An EM Algorithm and Analysis on Diverse Datasetscited by 3
  11. 2022Pedestrian Emergency Braking in Ten Weekscited by 2

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 4; 2025: 4; 2026: 1.

9 papers.

  1. 2024Language-Driven Active Learning for Diverse Open-Set 3D Object Detectioncited by 15
  2. 2024doScenes: An Autonomous Driving Dataset with Natural Language Instruction for Human Interaction and Vision-Language Navigationcited by 15
  3. 2025Towards a Multi-Agent Vision-Language System for Zero-Shot Novel Hazardous Object Detection for Autonomous Driving Safetycited by 9
  4. 2024Evaluating Vision-Language Models for Zero-Shot Detection, Classification, and Association of Motorcycles, Passengers, and Helmetscited by 4
  5. 2024Driver Activity Classification Using Generalizable Representations from Vision-Language Modelscited by 3
  6. 2025Towards Vision Zero: The TUM Traffic Accid3nD Datasetcited by 2
  7. 2025Enhancing Highway Safety: Accident Detection on the A9 Test Stretch Using Roadside Sensorscited by 1
  8. 2025Safety-Critical Learning for Long-Tail Events: The TUM Traffic Accident Datasetcited by 1
  9. 2026Vision-Language Work Zone Intelligence for Safety-Critical Speed Regulation of Mixed-Autonomy Vehicles in Dynamic Environmentscited by 0