Autonomous Vehicles

Autonomous Vehicles

Are commercially implemented adaptive cruise control systems string stable?

G. Gunter, Gloudemans, D., Stern, R. E., McQuade, S., Bhadani, R., Bunting, M., Monache, M. Laura Dell, Seibold, B., Sprinkle, J., Piccoli, B., and Work, D. B., “Are commercially implemented adaptive cruise control systems string stable?”, IEEE Transactions on Intelligent Transportation Systems, p. 12 pages, 2020.

Adaptive HSL Filters and Inverse Perspective Transforms in Lane Detection for Autonomous Driving

H. Mason, Bentley, L., MacInnes, J., Bhadani, R., and Bose, T., “Adaptive HSL Filters and Inverse Perspective Transforms in Lane Detection for Autonomous Driving”, in CAT Vehicle REU, 2019. Document: PDF icon Download preprint (1.86 MB)

Tracking vehicle trajectories and fuel rates in phantom traffic jams: Methodology and data

F. Wu, Stern, R. E., Cui, S., Monache, M. Laura Dell, Bhadani, R., Bunting, M., Churchill, M., Hamilton, N., Piccoli, B., Seibold, B., Sprinkle, J., and Work, D. B., “Tracking vehicle trajectories and fuel rates in phantom traffic jams: Methodology and data”, Transportation Research Part C: Emerging Technologies, vol. 99, pp. 82–109, 2019.

Real-Time Distance Estimation and Filtering of Vehicle Headways for Smoothing of Traffic Waves

R. Bhadani, Bunting, M., Seibold, B., Stern, R. E., Cui, S., Sprinkle, J., Piccoli, B., and Work, D. B., “Real-Time Distance Estimation and Filtering of Vehicle Headways for Smoothing of Traffic Waves”, International Conference on Cyber-Physical Systems 2019. Montreal, Canada, 2019.

Quantifying air quality benefits resulting from few autonomous vehicles stabilizing traffic

Y. Chen, Churchill, M., Wu, F., Monache, M. Laura Dell, Piccoli, B., Seibold, B., Sprinkle, J., and Work, D. B., “Quantifying air quality benefits resulting from few autonomous vehicles stabilizing traffic”, Transportation Research Part D: Transport and Environment, vol. 67, 2019.

{A LiDAR Error Model for Cooperative Driving Simulations}

M. Segata, Cigno, R. Lo, Bhadani, R., Bunting, M., and Sprinkle, J., “{A LiDAR Error Model for Cooperative Driving Simulations}”, in IEEE Vehicular Network Conference, Taipei, Taiwan, 2018. Document: PDF icon Download preprint (1.16 MB) PDF icon Download preprint (3.11 MB)

Dissipation of Emergent Traffic Waves in Stop-and-Go Traffic Using a Supervisory Controller

R. Bhadani, Piccoli, B., Seibold, B., Sprinkle, J., and Work, D. B., “Dissipation of Emergent Traffic Waves in Stop-and-Go Traffic Using a Supervisory Controller”, 57th IEEE Conference on Decision and Control, vol. 57. IEEE, Fontainbleau, Miami Beach, USA, 2018. Document: PDF icon Download preprint (1.5 MB) PDF icon Download preprint (6.58 MB)

{The CAT Vehicle Testbed: A Simulator with Hardware in the Loop for Autonomous Vehicle Applications}

R. Bhadani, Sprinkle, J., and Bunting, M., “{The CAT Vehicle Testbed: A Simulator with Hardware in the Loop for Autonomous Vehicle Applications}”, in Proceedings 2nd International Workshop on Safe Control of Autonomous Vehicles (SCAV 2018), Porto, Portugal, Electronic Proceedings in Theoretical Computer Science , 2018, vol. 269. Document: PDF icon Download preprint (5.53 MB)

NSF REU Site: Cognitive and Autonomous Test Vehicle (CATVehicle)

This research experience for undergraduates (REU) engaged in the myriad of applications that are related to autonomous ground vehicles. This summer, 10 NSF-funded undergraduate students participated in an immersive research experience, sitting side-by-side with graduate researchers and working on one of the most compelling, and complex, applications of today: autonomous systems.

Control of Vehicular Traffic Flow via Low Density Autonomous Vehicles

In the next few decades, autonomous vehicles will become an integral part of the traffic flow on highways. However, they will constitute only a small fraction of all vehicles on the road. This research develops technologies to employ autonomous vehicles already in the stream to improve traffic flow of human-controlled vehicles. The goal is to mitigate undesirable jamming, traffic waves, and to ultimately reduce the fuel consumption.

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