Vehicle Detection Techniques for Collision Avoidance Systems: A Review

By Amir Mukhtar, Likun Xia, T. Tang. IEEE transactions on intelligent transportation systems (Print), 2015

405 citations recorded by the source corpus.

Subfields: Automotive Engineering, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/23a73412b3eb7a2843d87c35efaf20423388c4b3

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

In Computer Vision and Pattern Recognition

Citations in the corpus

Smart Transportation: An Overview of Technologies and Applications (2023, background): “Because of its low power consumption and low cost, a large number of roadside WSNs may be strategically positioned to help vehicle communication technology [48].”
Ship Collision Avoidance and COLREGS Compliance Using Simulation-Based Control Behavior Selection With Predictive Hazard Assessment (2016, neutral): “In this paper, we address the design of the collision avoidance control algorithm, that must decide on the control actions required to ensure compliance with COLREGS and minimize hazard to an acceptable level based on the available sensor information.”
A Survey on 3D Object Detection Methods for Autonomous Driving Applications (2019, methodology): “[9] reviewed 2D vehicle detection methods for Driver Assistance Systems with focus on motion and appearance-based approaches using a traditional pipeline.”
Detection and tracking of pedestrians and vehicles using roadside LiDAR sensors (2019, background): “Additionally, the illumination condition has a significant effect on video quality – video recorded at night cannot provide as much valid information as video recorded during the daytime (Mukhtar et al., 2015) .”
Internet of vehicles in big data era (2018, background): “capability to fulfill communication tasks in worldwide [58].”
Perception, Planning, Control, and Coordination for Autonomous Vehicles (2017, background): “For more information on conventional hand-crafted feature/cue based approaches, interested readers may refer to the following survey papers: [68,69] for lane line marking detection, [70] for road surface detection, [71,72] for vehicle detection and [73] for pedestrian detection.”