Fuzzy-logic-based approach for identifying objects of interest in the PRIDE framework

Zeid Kootbally, Craig Schlenoff, Raj Madhavan, Sebti Foufou

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

On-road autonomous vehicle navigation requires real-time motion planning in the presence of static and moving objects. Based on sensed data of the environment and the current traffic situation, an autonomous vehicle has to plan a path by predicting the future location of objects of interest. In this context, an object of interest is a moving or stationary object in the environment that has a reasonable probability of intersecting the path of the autonomous vehicle within a predetermined time frame. This paper investigates the identification of objects of interest within the PRIDE (PRediction In Dynamic Environments) framework. PRIDE is a multi-resolutional, hierarchical framework that predicts the future location of moving objects for the purposes of path planning and collision avoidance for an autonomous vehicle. Identifying objects of interest is an aspect of situation awareness and is performed in PRIDE using a dangerous zone, i.e., a fuzzy-logic-based approach representing a hazardous space area around an autonomous vehicle. Once objects of interest are identified, the risk of collision between the autonomous vehicle and each object of interest is then evaluated. To illustrate the performance of a dangerous zone within PRIDE, preliminary results are presented using a traffic scenario with the high-fidelity physics-based framework for the Unified System for Automation and Robot Simulation (USARSim).

Original languageEnglish (US)
Title of host publicationPerformance Metrics for Intelligent Systems (PerMIS) Workshop - Proceedings of the PerMIS'08 Workshop
Pages17-24
Number of pages8
DOIs
StatePublished - Dec 1 2008
Event8th Workshop on Performance Metrics for Intelligent Systems, PerMIS'08 - Gaithersburg, MD, United States
Duration: Aug 19 2008Aug 21 2008

Other

Other8th Workshop on Performance Metrics for Intelligent Systems, PerMIS'08
CountryUnited States
CityGaithersburg, MD
Period8/19/088/21/08

Fingerprint

Fuzzy logic
Motion planning
Collision avoidance
Navigation
Automation
Physics
Robots

Keywords

  • 4D/RCS
  • autonomous vehicle
  • dangerous zone
  • fuzzy logic
  • fuzzy space
  • long-term prediction
  • moving object prediction
  • object of interest
  • PRIDE
  • situation awareness

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Science Applications
  • Control and Systems Engineering

Cite this

Kootbally, Z., Schlenoff, C., Madhavan, R., & Foufou, S. (2008). Fuzzy-logic-based approach for identifying objects of interest in the PRIDE framework. In Performance Metrics for Intelligent Systems (PerMIS) Workshop - Proceedings of the PerMIS'08 Workshop (pp. 17-24) https://doi.org/10.1145/1774674.1774678

Fuzzy-logic-based approach for identifying objects of interest in the PRIDE framework. / Kootbally, Zeid; Schlenoff, Craig; Madhavan, Raj; Foufou, Sebti.

Performance Metrics for Intelligent Systems (PerMIS) Workshop - Proceedings of the PerMIS'08 Workshop. 2008. p. 17-24.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kootbally, Z, Schlenoff, C, Madhavan, R & Foufou, S 2008, Fuzzy-logic-based approach for identifying objects of interest in the PRIDE framework. in Performance Metrics for Intelligent Systems (PerMIS) Workshop - Proceedings of the PerMIS'08 Workshop. pp. 17-24, 8th Workshop on Performance Metrics for Intelligent Systems, PerMIS'08, Gaithersburg, MD, United States, 8/19/08. https://doi.org/10.1145/1774674.1774678
Kootbally Z, Schlenoff C, Madhavan R, Foufou S. Fuzzy-logic-based approach for identifying objects of interest in the PRIDE framework. In Performance Metrics for Intelligent Systems (PerMIS) Workshop - Proceedings of the PerMIS'08 Workshop. 2008. p. 17-24 https://doi.org/10.1145/1774674.1774678
Kootbally, Zeid ; Schlenoff, Craig ; Madhavan, Raj ; Foufou, Sebti. / Fuzzy-logic-based approach for identifying objects of interest in the PRIDE framework. Performance Metrics for Intelligent Systems (PerMIS) Workshop - Proceedings of the PerMIS'08 Workshop. 2008. pp. 17-24
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