skip to main content
10.1145/3302509.3314026acmconferencesArticle/Chapter ViewAbstractPublication PagesiccpsConference Proceedingsconference-collections
research-article

Real-time distance estimation and filtering of vehicle headways for smoothing of traffic waves

Published: 16 April 2019 Publication History

Abstract

In this paper we describe an experience report and field deployment of real-time filtering algorithms used with a robotic vehicle to smooth emergent traffic waves. When smoothing these waves in simulation, a common approach is to implement controllers that utilize space gap, relative velocity and even acceleration from smooth ground truth information, rather than from realistic data. As a result, many results may be limited in their impact when considering the dynamics of the vehicle under control and the discretized nature of the laser data as well as its periodic arrival. Our approach discusses trade-offs in estimation accuracy to provide both distance and velocity estimates, with ground-truth hardware-in-the-loop tests with a robotic car. The contribution of the work enabled an experiment with 21 vehicles, including the robotic car closing the loop at up to 8.0 m/s with the filtered estimates, stressing the importance of an algorithm that can deliver real-time results with acceptable accuracy for the safety of the drivers in the experiment.

References

[1]
Ahmed Abdel-Hadi. 2010. Real-time object tracking using color-based Kalman particle filter. In Computer Engineering and Systems (ICCES), 2010 International Conference on. IEEE, 337--341.
[2]
António Almeida, Jorge Almeida, and Rui Araújo. 2005. Real-time tracking of multiple moving objects using particle filters and probabilistic data association. AUTOMATIKA-ZAGREB- 46, 1/2 (2005), 39.
[3]
Amir Aminifar, Petru Eles, Zebo Peng, Anton Cervin, and Karl-Erik Årzén. 2017. Control-Quality Driven Design of Embedded Control Systems with Stability Guarantees. IEEE Design & Test (2017).
[4]
Rahul Bhadani, Benedetto Piccoli, Benjamin Seibold, Jonathan Sprinkle, and Daniel B. Work. 2018. Dissipation of Emergent Traffic Waves in Stop-and-Go Traffic Using a Supervisory Controller. 57th IEEE Conference on Decision and Control 57 (2018), 3628--3633.
[5]
Rahul Bhadani, Jonathan Sprinkle, and Matthew Bunting. 2018. The CAT Vehicle Testbed: A Simulator with Hardware in the Loop for Autonomous Vehicle Applications. Proceedings 2nd International Workshop on Safe Control of Autonomous Vehicles (SCAV 2018), Porto, Portugal, 10th April 2018, Electronic Proceedings in Theoretical Computer Science 269, pp. 32--47 (2018).
[6]
Ashwin Carvalho, Alek Williams, Stéphanie Lefevre, and Francesco Borrelli. 2016. Autonomous cruise control with cut-in target vehicle detection. In Advanced Vehicle Control: Proceedings of the 13th International Symposium on Advanced Vehicle Control (AVEC'16), September 13--16, 2016, Munich, Germany. CRC Press, 93.
[7]
George Casella and Roger L Berger. 2002. Statistical inference. Vol. 2. Duxbury Pacific Grove, CA.
[8]
P Fancher and Z Bareket. 1994. Evaluating headway control using range versus range-rate relationships. Vehicle System Dynamics 23, 1 (1994), 575--596.
[9]
Douglas Gettman and Larry Head. 2003. Surrogate safety measures from traffic simulation models. Transportation Research Record: Journal of the Transportation Research Board 1840 (2003), 104--115.
[10]
Jürgen Hasch, Eray Topak, Raik Schnabel, Thomas Zwick, Robert Weigel, and Christian Waldschmidt. 2012. Millimeter-wave technology for automotive radar sensors in the 77 GHz frequency band. IEEE Transactions on Microwave Theory and Techniques 60, 3 (2012), 845--860.
[11]
Fei Hu, Yu Lu, Athanasios V Vasilakos, Qi Hao, Rui Ma, Yogendra Patil, Ting Zhang, Jiang Lu, Xin Li, and Neal N Xiong. 2016. Robust cyber-physical systems: concept, models, and implementation. Future generation computer systems 56 (2016), 449--475.
[12]
Irene Anindaputri Iswanto and Bin Li. 2017. Visual Object Tracking Based on Mean-shift and Particle-Kalman Filter. Procedia Computer Science 116 (2017), 587--595. Discovery and innovation of computer science technology in artificial intelligence era: The 2nd International Conference on Computer Science and Computational Intelligence (ICCSCI 2017).
[13]
Holger Kantz and Thomas Schreiber. 2004. Nonlinear time series analysis. Vol. 7. Cambridge university press.
[14]
Stéphanie Lefevre, Ashwin Carvalho, and Francesco Borrelli. 2016. A learning-based framework for velocity control in autonomous driving. IEEE Transactions on Automation Science and Engineering 13, 1 (2016), 32--42.
[15]
John Leonard, Jonathan How, Seth Teller, Mitch Berger, Stefan Campbell, Gaston Fiore, Luke Fletcher, Emilio Frazzoli, Albert Huang, Sertac Karaman, et al. 2008. A perception-driven autonomous urban vehicle. Journal of Field Robotics 25, 10 (2008), 727--774.
[16]
Pavlo Molchanov, Shalini Gupta, Kihwan Kim, and Kari Pulli. 2015. Short-range FMCW monopulse radar for hand-gesture sensing. In Radar Conference (Radar-Con), 2015 IEEE. IEEE, 1491--1496.
[17]
V. M. Monica and K. G. J. Nigel. 2017. Object tracking based on Kalman filter and gait feature extraction. In 2017 International Conference on Inventive Systems and Control (ICISC). 1--5.
[18]
Michael Montemerlo, Jan Becker, Suhrid Bhat, Hendrik Dahlkamp, Dmitri Dolgov, Scott Ettinger, Dirk Haehnel, Tim Hilden, Gabe Hoffmann, Burkhard Huhnke, et al. 2008. Junior: The stanford entry in the urban challenge. Journal of field Robotics 25, 9 (2008), 569--597.
[19]
Alan V Oppenheim and Ronald W Schafer. 2014. Discrete-time signal processing. Pearson Education.
[20]
Anna Petrovskaya and Sebastian Thrun. 2009. Model based vehicle detection and tracking for autonomous urban driving. Autonomous Robots 26, 2--3 (2009), 123--139.
[21]
Morgan Quigley, Ken Conley, Brian Gerkey, Josh Faust, Tully Foote, Jeremy Leibs, Rob Wheeler, and Andrew Y Ng. 2009. ROS: an open-source Robot Operating System. In ICRA workshop on open source software, Vol. 3. Kobe, Japan, 5.
[22]
Mark A Richards. 2005. Fundamentals of radar signal processing. Tata McGraw-Hill Education.
[23]
Josef Steinbaeck, Christian Steger, Gerald Holweg, and Norbert Druml. 2017. Next generation radar sensors in automotive sensor fusion systems. In Sensor Data Fusion: Trends, Solutions, Applications (SDF), 2017. IEEE, 1--6.
[24]
Raphael E. Stern, Shumo Cui, Maria Laura Delle Monache, Rahul Bhadani, Matt Bunting, Miles Churchill, Nathaniel Hamilton, R'mani Haulcy, Hannah Pohlmann, Fangyu Wu, Benedetto Piccoli, Benjamin Seibold, Jonathan Sprinkle, and Daniel B. Work. 2018. Dissipation of stop-and-go waves via control of autonomous vehicles: Field experiments. Transportation Research Part C: Emerging Technologies 89 (2018), 205--221.
[25]
Yuki Sugiyama, Minoru Fukui, Macoto Kikuchi, Katsuya Hasebe, Akihiro Nakayama, Katsuhiro Nishinari, Shin-ichi Tadaki, and Satoshi Yukawa. 2008. Traffic jams without bottlenecks - experimental evidence for the physical mechanism of the formation of a jam. New journal of physics 10, 3 (2008), 033001.
[26]
Wenshuo Wang, Chang Liu, and Ding Zhao. 2017. How much data are enough? A statistical approach with case study on longitudinal driving behavior. IEEE Transactions on Intelligent Vehicles 2, 2 (2017), 85--98.
[27]
William Young, Amir Sobhani, Michael G Lenné, and Majid Sarvi. 2014. Simulation of safety: A review of the state of the art in road safety simulation modelling. Accident Analysis & Prevention 66 (2014), 89--103.

Cited By

View all
  • (2024)Stability of ring roads and string stability of car following modelsMathematical Control and Related Fields10.3934/mcrf.2024062(0-0)Online publication date: 2024
  • (2024)Assessing the Impact of CAV Driving Strategies on Mixed Traffic on the Ring Road and FreewaySustainability10.3390/su1608317916:8(3179)Online publication date: 10-Apr-2024
  • (2024)Modifying Adaptive Cruise Control Systems for String Stable Stop-and -Go Wave ControlIEEE Robotics and Automation Letters10.1109/LRA.2024.34408349:10(8330-8337)Online publication date: Oct-2024
  • Show More Cited By

Recommendations

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences
ICCPS '19: Proceedings of the 10th ACM/IEEE International Conference on Cyber-Physical Systems
April 2019
367 pages
ISBN:9781450362856
DOI:10.1145/3302509
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]

Sponsors

In-Cooperation

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

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 April 2019

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. autonomous vehicles
  2. connected vehicles
  3. cyber-physical systems
  4. digital filter
  5. real-time applications
  6. sensors
  7. simulation
  8. traffic

Qualifiers

  • Research-article

Conference

ICCPS '19
Sponsor:

Acceptance Rates

Overall Acceptance Rate 25 of 91 submissions, 27%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • Downloads (Last 12 months)10
  • Downloads (Last 6 weeks)3
Reflects downloads up to 19 Feb 2025

Other Metrics

Citations

Cited By

View all
  • (2024)Stability of ring roads and string stability of car following modelsMathematical Control and Related Fields10.3934/mcrf.2024062(0-0)Online publication date: 2024
  • (2024)Assessing the Impact of CAV Driving Strategies on Mixed Traffic on the Ring Road and FreewaySustainability10.3390/su1608317916:8(3179)Online publication date: 10-Apr-2024
  • (2024)Modifying Adaptive Cruise Control Systems for String Stable Stop-and -Go Wave ControlIEEE Robotics and Automation Letters10.1109/LRA.2024.34408349:10(8330-8337)Online publication date: Oct-2024
  • (2024)Reinforcement Learning with Communication Latency with Application to Stop-and-Go Wave Dissipation2024 IEEE Intelligent Vehicles Symposium (IV)10.1109/IV55156.2024.10588394(1187-1193)Online publication date: 2-Jun-2024
  • (2023)Analysis of a Runtime Data Sharing Architecture over LTE for a Heterogeneous CAV FleetProceedings of Cyber-Physical Systems and Internet of Things Week 202310.1145/3576914.3587712(164-169)Online publication date: 9-May-2023
  • (2023)Approaches for Synthesis and Deployment of Controller Models on Automated Vehicles for Car-following in Mixed AutonomyProceedings of Cyber-Physical Systems and Internet of Things Week 202310.1145/3576914.3587711(158-163)Online publication date: 9-May-2023
  • (2022)Data from the Development Evolution of a Vehicle for Custom Control2022 2nd Workshop on Data-Driven and Intelligent Cyber-Physical Systems for Smart Cities Workshop (DI-CPS)10.1109/DI-CPS56137.2022.00013(40-46)Online publication date: May-2022
  • (2022)Emergency Obstacle Avoidance Based on Gradient Descent Distance for Self-driving VehiclesProceedings of 2021 International Conference on Autonomous Unmanned Systems (ICAUS 2021)10.1007/978-981-16-9492-9_292(2980-2989)Online publication date: 18-Mar-2022
  • (2021)Reachability Analysis for FollowerStopper: Safety Analysis and Experimental Results2021 IEEE International Conference on Robotics and Automation (ICRA)10.1109/ICRA48506.2021.9561360(8607-8613)Online publication date: 30-May-2021

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Figures

Tables

Media

Share

Share

Share this Publication link

Share on social media