Vehicle Tracking for Heavy Road Vehicle Collision Avoidance with an Inexpensive Solid State Laser Sensor

Vimal Kumar; Shankar C. Subramanian; Rajesh Rajamani

doi:10.1109/ITSC.2019.8917420

Vehicle Tracking for Heavy Road Vehicle Collision Avoidance with an Inexpensive Solid State Laser Sensor

Vimal Kumar
, Shankar C. Subramanian
, Rajesh Rajamani

Mechanical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Scopus citations

Abstract

The focus of this paper is on the development of a vehicle-tracking algorithm using a solid-state LIDAR sensor for application to Collision Avoidance Systems (CAS) for Heavy Commercial Road Vehicles. Solid State LIDARs are relatively inexpensive compared to RADARs and point cloud LIDARs, and hence could accelerate commercialization of Advanced Driver Assistance Systems (ADAS) especially in cost-sensitive markets. The suitability of an inexpensive LIDAR sensor for Rear End Collision Avoidance application is analyzed first. Then, using the measurements from the sensor, an Interacting Multiple Model filter and a linear Kalman Filter are used for estimating the longitudinal and the lateral motion variables respectively, for various classes of road vehicles. Good tracking accuracy is achieved in the lateral direction despite the sensor's low angular resolution. The proposed estimation algorithm is first evaluated in a vehicle dynamics software, IPG TruckMaker®, and then through experiments, and the results are presented.

Original language	English (US)
Title of host publication	2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1136-1141
Number of pages	6
ISBN (Electronic)	9781538670248
DOIs	https://doi.org/10.1109/ITSC.2019.8917420
State	Published - Oct 2019
Event	2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 - Auckland, New Zealand Duration: Oct 27 2019 → Oct 30 2019

Publication series

Name	2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019

Conference

Conference	2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
Country/Territory	New Zealand
City	Auckland
Period	10/27/19 → 10/30/19

Bibliographical note

Publisher Copyright:
© 2019 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being

Publisher link

10.1109/ITSC.2019.8917420

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Kumar, V., Subramanian, S. C., & Rajamani, R. (2019). Vehicle Tracking for Heavy Road Vehicle Collision Avoidance with an Inexpensive Solid State Laser Sensor. In 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019 (pp. 1136-1141). Article 8917420 (2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ITSC.2019.8917420

Vehicle Tracking for Heavy Road Vehicle Collision Avoidance with an Inexpensive Solid State Laser Sensor. / Kumar, Vimal; Subramanian, Shankar C.; Rajamani, Rajesh.
2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. p. 1136-1141 8917420 (2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Kumar, V, Subramanian, SC & Rajamani, R 2019, Vehicle Tracking for Heavy Road Vehicle Collision Avoidance with an Inexpensive Solid State Laser Sensor. in 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019., 8917420, 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019, Institute of Electrical and Electronics Engineers Inc., pp. 1136-1141, 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019, Auckland, New Zealand, 10/27/19. https://doi.org/10.1109/ITSC.2019.8917420

Kumar V, Subramanian SC, Rajamani R. Vehicle Tracking for Heavy Road Vehicle Collision Avoidance with an Inexpensive Solid State Laser Sensor. In 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019. Institute of Electrical and Electronics Engineers Inc. 2019. p. 1136-1141. 8917420. (2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019). doi: 10.1109/ITSC.2019.8917420

Kumar, Vimal ; Subramanian, Shankar C. ; Rajamani, Rajesh. / Vehicle Tracking for Heavy Road Vehicle Collision Avoidance with an Inexpensive Solid State Laser Sensor. 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 1136-1141 (2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019).

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abstract = "The focus of this paper is on the development of a vehicle-tracking algorithm using a solid-state LIDAR sensor for application to Collision Avoidance Systems (CAS) for Heavy Commercial Road Vehicles. Solid State LIDARs are relatively inexpensive compared to RADARs and point cloud LIDARs, and hence could accelerate commercialization of Advanced Driver Assistance Systems (ADAS) especially in cost-sensitive markets. The suitability of an inexpensive LIDAR sensor for Rear End Collision Avoidance application is analyzed first. Then, using the measurements from the sensor, an Interacting Multiple Model filter and a linear Kalman Filter are used for estimating the longitudinal and the lateral motion variables respectively, for various classes of road vehicles. Good tracking accuracy is achieved in the lateral direction despite the sensor's low angular resolution. The proposed estimation algorithm is first evaluated in a vehicle dynamics software, IPG TruckMaker{\textregistered}, and then through experiments, and the results are presented.",

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AB - The focus of this paper is on the development of a vehicle-tracking algorithm using a solid-state LIDAR sensor for application to Collision Avoidance Systems (CAS) for Heavy Commercial Road Vehicles. Solid State LIDARs are relatively inexpensive compared to RADARs and point cloud LIDARs, and hence could accelerate commercialization of Advanced Driver Assistance Systems (ADAS) especially in cost-sensitive markets. The suitability of an inexpensive LIDAR sensor for Rear End Collision Avoidance application is analyzed first. Then, using the measurements from the sensor, an Interacting Multiple Model filter and a linear Kalman Filter are used for estimating the longitudinal and the lateral motion variables respectively, for various classes of road vehicles. Good tracking accuracy is achieved in the lateral direction despite the sensor's low angular resolution. The proposed estimation algorithm is first evaluated in a vehicle dynamics software, IPG TruckMaker®, and then through experiments, and the results are presented.

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Vehicle Tracking for Heavy Road Vehicle Collision Avoidance with an Inexpensive Solid State Laser Sensor

Abstract

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Bibliographical note

UN SDGs

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