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Autonomous intelligent cruise control
Open accessAbstract
Vehicle following and its effects on traffic flow has been an active area of research. Human driving involves reaction times, delays, and human errors that affect traffic flow adversely. One way to eliminate human errors and delays in vehicle following is to replace the human driver with a computer control system and sensors. The purpose of this paper is to develop an autonomous intelligent cruise control (AICC) system for automatic vehicle following, examine its effect on traffic flow, and compare its performance with that of the human driver models. The AICC system developed is not cooperative; i.e., it does not exchange information with other vehicles and yet is not susceptible to oscillations and "slinky" effects. The elimination of the "slinky" effect is achieved by using a safety distance separation rule that is proportional to the vehicle velocity (constant time headway) and by designing the control system appropriately. The performance of the AICC system is found to be superior to that of the human driver models considered. It has a faster and better transient response that leads to a much smoother and faster traffic flow. Computer simulations are used to study the performance of the proposed AICC system and analyze vehicle following in a single lane, without passing, under manual and automatic control. In addition, several emergency situations that include emergency stopping and cut-in cases were simulated. The simulation results demonstrate the effectiveness of the AICC system and its potentially beneficial effects on traffic flow.>
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Cited by
String-Stable CACC Design and Experimental Validation: A Frequency-Domain Approach
Naus, G. J. L., Vugts, R. P. A., Ploeg, J., van de Molengraft, M. J. G., & Steinbuch, M. (2010) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2010.2076320 · Cited by 916
Evaluating the impact of connected and autonomous vehicles on traffic safety
Ye, L., & Yamamoto, T. (2019) · Physica A: Statistical Mechanics and its Applications · doi:10.1016/j.physa.2019.04.245 · Cited by 296
Assessing the Long-term Effects of Autonomous Vehicles: A Speculative Approach
Gruel, W., & Stanford, J. M. (2016) · Transportation Research Procedia · doi:10.1016/j.trpro.2016.05.003 · Cited by 166
Metadata
- Authors
- Ioannou, P. A., & Chien, C. C.
- Venue
- IEEE Transactions on Vehicular Technology
- Published
- 1993
- Volume
- 42
- Issue
- 4
- Pages
- 657-672
- ISSN
- 0018-9545 (ISSN-L)
- OpenAlex
- W2111204826
- Cited by
- 757
- References
- 0
- FWCI
- 12.69
- Type
- journal article
- Language
- en
- Open access
- green
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