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Safer adaptive cruise control for traffic wave dampening

Published: 19 May 2021 Publication History

Abstract

This project aims to develop an adaptive cruise controller for vehicles at low speeds in stop-and-go traffic. Current adaptive cruise controllers can use RADAR sensors to follow a vehicle at high speeds (greater than 18 mph), but reach their limits if the lead vehicle's velocity dips below threshold, requiring the driver of the host vehicle to resume control over the car's speed. Some cruise controllers adapt to stop-and-go traffic, but these are mostly experimental and have yet to see widespread commercial implementation. These experimental models often have issues because of their limited data; consequently, the acceleration and deceleration can be jarring and uncomfortable to passengers. In contrast, because of our reliable sensor data, and the sensor configuration unique to the CAT Vehicle, our cruise controller will be capable of following cars at low speeds and functioning continuously, even when the car is stopped.

References

[1]
Rahul Bhadani, Jonathan Sprinkle, and M. Bunting. 2018. The CAT Vehicle Testbed: A Simulator with Hardware in the Loop for Autonomous Vehicle Applications. 2nd International Workshop on Safe Control of Autonomous Vehicles (2018), 32--47.
[2]
R. E. Stern, S. Cui, M. L. Delle Monache, R. Bhadani, M. Bunting, M. Churchill, N. Hamilton, R. Haulcy, H. Pohlmann, F. Wu, B. Piccoli, B. Seibold, J. Sprinkle, and D. B. Work. 2017. The Arizona Ring Experiments Dataset (ARED).
[3]
C. Wu, Z. Xu, Y. Liu, C. Fu, K. Li, and M. Hu. 2020. Spacing Policies for Adaptive Cruise Control: A Survey. IEEE Access 8 (2020), 50149--50162.

Cited By

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  • (2022)CANClassify: Automated Decoding and Labeling of CAN Bus SignalsJournal of Engineering Research and Sciences10.55708/js01100021:10(5-12)Online publication date: Oct-2022

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Published In

cover image ACM Conferences
ICCPS '21: Proceedings of the ACM/IEEE 12th International Conference on Cyber-Physical Systems
May 2021
242 pages
ISBN:9781450383530
DOI:10.1145/3450267
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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  • IEEE-CS\TCRT: TC on Real-Time Systems

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 May 2021

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Author Tags

  1. adaptive cruise control
  2. stop-and-go
  3. vehicle autonomy

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  • Research-article

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Overall Acceptance Rate 25 of 91 submissions, 27%

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Cited By

View all
  • (2022)CANClassify: Automated Decoding and Labeling of CAN Bus SignalsJournal of Engineering Research and Sciences10.55708/js01100021:10(5-12)Online publication date: Oct-2022

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