Driver Acceptance of Adaptive Cruise Control and Active Lane Keeping in Five Production Vehicles

2017 ◽  
Vol 61 (1) ◽  
pp. 1949-1953
Author(s):  
Ian J. Reagan ◽  
David G. Kidd ◽  
Jessica B. Cicchino
Keyword(s):  
Adaptive Cruise Control ◽  
Highway Safety ◽  
Cruise Control ◽  
Driving Experience ◽  
Stop And Go ◽  
Driver Acceptance ◽  
Automation Technology ◽  
Lane Keeping ◽  
Toyota Prius

Little is known about how consumers interact with driving automation technology that controls steering, speed, or headway in production vehicles. Forty-eight Insurance Institute for Highway Safety employees used a Honda Civic, Infiniti QX60, Toyota Prius, or Audi A4 or Q7 as a personal vehicle for up to several weeks and completed surveys about their experiences. Agreement about whether adaptive cruise control (ACC) or active lane keeping (ALK) improved driving experience varied significantly among vehicles. The Q7’s ACC improved the driving experience significantly more than its ALK. The Civic’s ALK improved the driving experience more than the Q7’s system, but this effect only approached significance. Drivers were most comfortable using systems on free-flowing interstates and least comfortable using ACC in stop-and-go traffic and ALK on curvy roads. The findings show a range of qualitative differences in driving automation technologies and that use of current technologies likely is limited to low-demand conditions.

scholarly journals Correctness Guarantees for the Composition of Lane Keeping and Adaptive Cruise Control

2018 ◽  
Vol 15 (3) ◽  
pp. 1216-1229 ◽  
Author(s):  
Xiangru Xu ◽  
Jessy W. Grizzle ◽  
Paulo Tabuada ◽  
Aaron D. Ames
Keyword(s):  
Adaptive Cruise Control ◽  
Cruise Control ◽  
Lane Keeping

Human-Aware Autonomous Control for Cooperative Adaptive Cruise Control (CACC) Systems

2015 ◽  
Author(s):  
Xujie Wang ◽  
Yue Wang
Keyword(s):  
Adaptive Cruise Control ◽  
Controller Design ◽  
Cruise Control ◽  
String Stability ◽  
Driving Experience ◽  
Traffic Efficiency ◽  
Cooperative Adaptive Cruise Control ◽  
Human Driver ◽  
Driving Assistance ◽  
System Controller

This paper discusses the design of a human-aware cooperative adaptive cruise control (CACC) system that (i) takes into account driver comfort in autonomous cruise control, and (ii) provides assistive corrections to avoid driver errors. To incorporate driver characteristics into system controller design, two self-learning algorithms are used to estimate driver’s preferred time headway. We then develop a human-like blending control for CACC based on a model predictive control (MPC)-type method, which integrates the driver comfort, traffic efficiency, and fuel economy criteria. Furthermore, a driving assistance controller is developed to help human driver to maintain string stability in platoon. Simulation results show that (i) the human-like CACC design can significantly improve driving experience, and (ii) with the help of the assistive controller, string stability is satisfied for both exclusively autonomous CACC and when the CACC switches to manual driving in a platoon.

scholarly journals Intelligent Vehicle Automatic Stop-and-Go Task Based on Humanized Learning Control Model

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Tianjun Sun ◽  
Zhenhai Gao ◽  
Fei Gao ◽  
Tianyao Zhang ◽  
Di Ji ◽  
...  
Keyword(s):  
Learning Control ◽  
Control Model ◽  
Intelligent Vehicles ◽  
Cruise Control ◽  
Driving Experience ◽  
Stop And Go ◽  
Full Speed ◽  
Vehicle Test ◽  
Dynamic Time ◽  
Humanized Learning

The automatic stop-and-go task of intelligent vehicles can make the adaptive cruise control system achieve a full-speed range. However, the conventional design methods mostly focus on functional safety, without considering drivers’ behaviors, thereby leading to a poor driving experience. To improve the situation, a humanized learning control model is used instead of mechanical switching logic. Therefore, first, the common characteristics of human drivers with different driving styles are found by analyzing real drivers’ experiments. Then, the vehicle automatic starting function is designed based on iterative learning control with the fast Fourier transform for acceleration fitting. Next, the vehicle automatic braking function is designed based on dynamic time to collision. Finally, the simulation of the stop-and-go scenario is shown in CARSIM, and the real vehicle test is performed under the urban overpass driving condition. Results show that the proposed model can improve the humanization in the vehicle stop-and-go task.

Sign in / Sign up

Export Citation Format

Share Document