Behavioral Adaptations to Lane Keeping Systems: Effects of Exposure and Withdrawal

Miller, Erika E.; Boyle, Linda Ng

doi:10.1177/0018720818800538

Cited by 21 publications

(13 citation statements)

References 14 publications

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“…However, the standard deviation of lane position increased over the same period, possibly indicating a reduction in driver performance. This is in agreement with Miller et al (2019) who found an increase in SDLP after using an LKS. Overall because improvements in driver performance between the practice and final drives were demonstrated for most measures and changes in driver performance due to LKAS alignment errors moved opposite to those improvements, the experimental design was effective.…”

Section: Resultssupporting

confidence: 93%

“…Some researchers have investigated full Lane Keeping Systems (LKS), which, opposed to a LKAS, provides enough torque to steer without any driver intervention. Miller et al (2019) conducted an experiment to investigate what happens when the LKS functions stop with a resulting transition from automated driving to manual driving. They found that drivers had an increased SDLP and decreased mean Time to Collision (TTC) after system withdrawal.…”

Section: Literature Reviewmentioning

confidence: 99%

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Impact of lane keeping assist system camera misalignment on driver behavior

Romano

Maggi

Hirose

et al. 2020

Journal of Intelligent Transportation Systems

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This research investigated the impact of sensor camera misalignment on the quality of the lane keeping assistance, end user experience and driving performance. Testing was performed with 16 participants, both males and females, with an age range from 25 to 35. The Lane Keeping Assist System (LKAS) errors in lateral offset ranged from À0.66 m to 0.66 m and testing was performed on two roads. The results indicated that introducing an error in the LKAS system of 0.66 m caused the mean lane position of the vehicle to move in a similar direction by 0.1 m while some individuals showed as much as a 0.2 m change in their lateral position. Increases in error in the camera misalignment also increased the number of steering reversals indicating that the drivers worked harder to stay in their lane.

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Section: Resultssupporting

confidence: 93%

Section: Literature Reviewmentioning

confidence: 99%

Impact of lane keeping assist system camera misalignment on driver behavior

Romano

Maggi

Hirose

et al. 2020

Journal of Intelligent Transportation Systems

View full text Add to dashboard Cite

show abstract

“…An unexpected finding in our study was that mean headway was not affected by driving condition nor secondary task difficulty. However, previous work (Miller & Boyle, 2018) that examined the effects of LKS and secondary task on workload and driving performance, found shorter headway times using the LKS and in the Manual driving condition without a secondary task. In another study, Kubose (2005) reported longer headway times in the dual-task condition (driving with a speech task) compared to the single-task condition.…”

Section: Discussionmentioning

confidence: 80%

“…For example, for Level-1 automation, Rudin-Brown and Parker (2004) showed that the use of ACC alone results in significantly larger variability in lane position compared to manual driving. Miller and Boyle (2018), on the other hand, reported that the introduction of LKS in isolation reduces mean headway distances.…”

Section: Introductionmentioning

confidence: 99%

The Effect of Secondary Cognitive Task Difficulty on Headway Maintenance and Perceived Workload While Using Lane Keeping Systems

Liang

Pitts

2019

Proceedings of the Human Factors and Ergonomics Society Annual

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Vehicle automation is developing at a rapid rate worldwide. However, even lower levels of automation, such as SAE Level-1, are expected to reduce drivers’ workload by controlling either speed or lane position. At the same time, however, drivers’ engagement in secondary tasks may make up for this difference in workload displaced by automation. Previous research has investigated the effects of adaptive cruise control on driving performance and workload, but little attention has been devoted to lane keeping systems (LKS). In addition, the influence of secondary cognitive tasks on Level-1 driving performance is also not well understood. The goal of this study was to examine the effects of secondary cognitive tasks on driving performance and perceived workload while using LKS. Nine participants drove a simulated vehicle in manual and LKS modes, while maintaining a specific headway and performing a secondary cognitive (n-back) task with varying levels of difficulty. Results showed that standard deviation of headway and NASA-TLX workload scores were significantly higher during the most difficulty secondary task. Also, LKS was not found to improve driving performance nor reduce perceived workload. This paper highlights potential performance costs and benefits associated with LKS technology and proposes directions for future research.

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“…As a feasible transition for automated driving at the present stage, cooperative driving possesses vital academic value. Meanwhile, cooperative driving for lane keeping has been developed to reduce the driver's workload and satisfy driver intentions [6][7][8][9].…”

Section: Introductionmentioning

confidence: 99%

Human–Machine Cooperative Control of Intelligent Vehicles for Lane Keeping—Considering Safety of the Intended Functionality

et al. 2021

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Reasonably foreseeable misuse by persons, as a primary aspect of safety of the intended functionality (SOTIF), has a significant effect on cooperation performance for lane keeping. This paper presents a novel human–machine cooperative control scheme with consideration of SOTIF issues caused by driver error. It is challenging to balance lane keeping performance and driving freedom when driver error occurs. A safety evaluation strategy is proposed for safety supervision, containing assessments of driver error and lane departure risk caused by driver error. A dynamic evaluation model of driver error is designed based on a typical driver model in the loop to deal with the uncertainty and variability of driver behavior. Additionally, an extension model is established for determining the cooperation domain. Then, an authority allocation strategy is proposed to generate a dynamic shared authority and achieve an adequate balance between lane keeping performance and driving freedom. Finally, a model predictive control (MPC)-based controller is designed for calculating optimal steering angle, and a steer-by-wheel (SBW) system is employed as an actuator. Numerical simulation tests are conducted on driver error scenarios based on the CarSim and MATLAB/Simulink software platforms. The simulation results demonstrate the effectiveness of the proposed method.

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Behavioral Adaptations to Lane Keeping Systems: Effects of Exposure and Withdrawal

Cited by 21 publications

References 14 publications

Impact of lane keeping assist system camera misalignment on driver behavior

Impact of lane keeping assist system camera misalignment on driver behavior

The Effect of Secondary Cognitive Task Difficulty on Headway Maintenance and Perceived Workload While Using Lane Keeping Systems

Human–Machine Cooperative Control of Intelligent Vehicles for Lane Keeping—Considering Safety of the Intended Functionality

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