A Kinematic Modeling Framework for Prediction of Instantaneous Status of Towing Vehicle Systems

Liu, Yucheng; Davenport, Collin; Gafford, James; Ball, John; Doude, Matthew; Burch, Reuben F.; Abdelwahed, Sherif; Mazzola, Michael S.

doi:10.4271/06-11-02-0015

Cited by 4 publications

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LiDAR and Camera Detection Fusion in a Real-Time Industrial Multi-Sensor Collision Avoidance System

et al. 2018

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Collision avoidance is a critical task in many applications, such as ADAS (advanced driver-assistance systems), industrial automation and robotics. In an industrial automation setting, certain areas should be off limits to an automated vehicle for protection of people and high-valued assets. These areas can be quarantined by mapping (e.g., GPS) or via beacons that delineate a no-entry area. We propose a delineation method where the industrial vehicle utilizes a LiDAR (Light Detection and Ranging) and a single color camera to detect passive beacons and model-predictive control to stop the vehicle from entering a restricted space. The beacons are standard orange traffic cones with a highly reflective vertical pole attached. The LiDAR can readily detect these beacons, but suffers from false positives due to other reflective surfaces such as worker safety vests. Herein, we put forth a method for reducing false positive detection from the LiDAR by projecting the beacons in the camera imagery via a deep learning method and validating the detection using a neural network-learned projection from the camera to the LiDAR space. Experimental data collected at Mississippi State University's Center for Advanced Vehicular Systems (CAVS) shows the effectiveness of the proposed system in keeping the true detection while mitigating false positives.

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LiDAR and Camera Detection Fusion in a Real-Time Industrial Multi-Sensor Collision Avoidance System

et al. 2018

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An Automatic Emergency Braking System for Collision Avoidance Assist of Multi-Trailer Vehicle Based on Model Prediction Control

Liu¹,

Ball²,

Abdelwahed³

et al. 2021

SAE Technical Paper Series

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Collision Avoidance Study for Towbarless Aircraft Taxiing Systems on the Airport Apron Considering the Measuring Uncertainty

Zhu¹,

Xu²,

Zhang³

et al. 2023

SAE Technical Paper Series

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<div class="section abstract"><div class="htmlview paragraph">The towbarless aircraft taxiing system (TLATS) consists of the towbarless towing vehicle (TLTV) and the aircraft. The tractor realizes the towing work by fixing the nose wheel. During the towing process, the tractor driver may cause the aircraft to collide with an obstacle because of the blind spot of vision leading to the accident. The special characteristics of aircraft do not allow us to modify the structure of the aircraft to achieve collision avoidance. In this paper, three degrees of freedom (DOE) kinematic model of the tractor system is established for each of the two cases of pushing and pulling the aircraft, and the relationship between the coordinates of each danger point and the relatively articulated angle of the TLATS and the velocity of the midpoint of the rear axle is derived. Considering that there is an error between the velocity and relatively articulated angle measured by the sensor and the actual one, the effect of velocity and relatively articulated angle uncertainty on the traction trajectory of the aircraft-tractor system is investigated based on the Chebyshev expansion function. The calculation efficiency and the result range of Chebyshev method and those of Monte Carlo(MC) method are compared. An aircraft collision avoidance model on the apron is established based on Simulink. The simulation results show that the method can achieve the measurement of aircraft attitude and position and realize the anti-collision.</div></div>

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A Kinematic Modeling Framework for Prediction of Instantaneous Status of Towing Vehicle Systems

Cited by 4 publications

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LiDAR and Camera Detection Fusion in a Real-Time Industrial Multi-Sensor Collision Avoidance System

LiDAR and Camera Detection Fusion in a Real-Time Industrial Multi-Sensor Collision Avoidance System

An Automatic Emergency Braking System for Collision Avoidance Assist of Multi-Trailer Vehicle Based on Model Prediction Control

Collision Avoidance Study for Towbarless Aircraft Taxiing Systems on the Airport Apron Considering the Measuring Uncertainty

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