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Impact of Automated Lane Change Assist on Energy Consumption
Technical Paper
2020-01-0082
ISSN: 0148-7191, e-ISSN: 2688-3627
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Abstract
This paper models adaptive cruise control combined with automated lane change assist to investigate the energy consumption improvements that such a system may provide compared to conventional adaptive cruise control. Automatically executing a lane change may improve efficiency, for example, when following a vehicle that is slowing to make a turn. Changing lanes while maintaining speed is hypothesized to be more efficient than staying in the same lane as the turning vehicle and reducing speed. The differences in such scenarios are simulated in a virtual environment using a cuboid model with idealized sensors. The ego-vehicle detects scenarios and performs a lane change to reduce or eliminate required speed changes. The results of the simulations compare the energy content of the resulting drive cycle as an idealized method to measure energy consumption for each cruise control strategy. The simulations consider traffic laws, such as turn signal requirements that may dictate the distance the ego-vehicle must travel before the lane changes can be executed. The results showed that energy consumption can be reduced with an automated lane change feature, but the benefits could be limited by sensor range and local law requirements.
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Troxler, C., Currier, P., and Reinholtz, C., "Impact of Automated Lane Change Assist on Energy Consumption," SAE Technical Paper 2020-01-0082, 2020, https://doi.org/10.4271/2020-01-0082.Data Sets - Support Documents
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References
- NHSTA Automated Vehicles for Safety NHSTA.gov https://www.nhtsa.gov/technology-innovation/automated-vehicles-safety October 30, 2019
- Liu , S. , Liu , L. , Tang , J. , Yu , B. et al. Edge Computing for Autonomous Driving: Opportunities and Challenges Proceedings of the IEEE 107 8 1697 1716 Aug. 2019 10.1109/JPROC.2019.2915983
- Taiebat , M. , Brown , A. , Safford , H. , Qu , S. , and Xu , M. A Review on Energy, Environmental, and Sustainability of Connected and Automated Vehicles Environmental Science & Technology 52 20 11449 11465 2018 10.1021/acs.est.8b00127
- SAE Recommended Practice June 15, 2018
- Wifvat , V. , Shaffer , B. , and Samuelsen , S. A Review of Sensor Technologies for Automotive Fuel Economy Benefits SAE Intl. J CAV 2 1 5 16 2019 https://doi.org/10.4271/12-02-01-0001
- Michel , P. , Karbowski , D. , and Rousseau , A. Impact of Connectivity and Automation on Vehicle Energy Use SAE Technical Paper 2016-01-0152 2016 https://doi.org/10.4271/2016-01-0152
- Tunnell , J. , Asher , Z. , Pasricha , S. , and Bradley , T. Toward Improving Vehicle Fuel Economy with ADAS SAE Intl. J CAV 1 2 81 92 2018 https://doi.org/10.4271/12-01-02-0005
- Tate , L. , Hochgreb , S. , Hall , J. , and Bassett , M. Energy Efficiency of Autonomous Car Powertrain SAE Technical Paper 2018-01-1092 2018 https://doi.org/10.4271/2018-01-1092
- Mathworks Lane Following Control with Sensor Fusion and Lane Detection mathworks.com https://www.mathworks.com/help/mpc/ug/lane-following-control-with-sensor-fusion-and-lane-detection.html#d117e38726 October 8, 2019
- Svensson , L. and Eriksson , J. 2015
- Mathworks Lateral Controller Stanley https://www.mathworks.com/help/driving/ref/lateralcontrollerstanley.html October 9, 2019
- Hoffmann , G. , Tomlin , C. , Montemerlo , M. and Thrun , S. Autonomous Automobile Trajectory Tracking for Off-Road Driving: Controller Design, Experimental Validation and Racing American Control Conference 2007 2296 2301 10.1109/ACC.2007.4282788
- Zhu , B. , Liu , S. , and Zhao , J. A Lane-Changing Decision-Making Method for Intelligent Vehicle Based on Acceleration Field SAE Int. J. Passeng. Cars - Electron. Electr. Syst. 11 3 219 230 2018 https://doi.org/10.4271/2018-01-0599
- Mathworks Vehicle Body 3DOF mathworks.com https://www.mathworks.com/help/vdynblks/ref/vehiclebody3dof.html?s_tid=doc_ta October 9, 2019
- FL