Automatic Emergency Steering with Distracted Drivers: Effects of Intervention Design

Sieber, Markus; Siedersberger, Karl-Heinz; Siegel, Andreas; Färber, Berthold

doi:10.1109/itsc.2015.330

Cited by 14 publications

(15 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Conversely, TV is continuously active, which further benefits vehicle safety and stability [10]. Other interesting ADAS are steering control systems, which are being increasingly adopted in modern cars: notable examples are the Lane Keeping System, or the Automatic Emergency Steering [11,12]. Their principle of operation is quite different than TV as they directly intervene on the steering wheel angle position in particular situations, such as driver distractions.…”

Section: Introductionmentioning

confidence: 99%

An integrated torque-vectoring control framework for electric vehicles featuring multiple handling and energy-efficiency modes selectable by the driver

2021

View full text Add to dashboard Cite

A key feature achievable by electric vehicles with multiple motors is torque-vectoring. Many control techniques have been developed to harness torque-vectoring in order to improve vehicle safety and energy efficiency. The majority of the existing contributions only deal with specific aspects of torque-vectoring. This paper presents an integrated approach allowing a smooth coordination among the main blocks that constitute a torque-vectoring control framework: (1) a reference generator, that defines target yaw rate and sideslip angle; (2) a high level controller, that works out the required total torque and yaw moment at the vehicle level; (3) a low level controller, that maps the required force and yaw moment into individual wheel torque demands. In this framework, the driver can select one among a number of driving modes that allow to change the vehicle cornering response and, as a second priority, maximise energy efficiency. For the first time, the selectable driving modes include an “Energy efficiency” mode that uses torque-vectoring to prioritise the maximisation of the vehicle energy efficiency, thus further increasing the vehicle driving range. Simulation results show the effectiveness of the proposed framework on an experimentally validated 14 degrees of freedom vehicle model.

show abstract

Section: Introductionmentioning

confidence: 99%

An integrated torque-vectoring control framework for electric vehicles featuring multiple handling and energy-efficiency modes selectable by the driver

2021

View full text Add to dashboard Cite

show abstract

“…However, in emergency situations requiring fast and precise responses, control sharing may actually have a negative effect on joint system performance. Automation systems can perform evasive steering maneuvers in emergency scenarios, including scenarios in which braking alone is insufficient to avoid collisions [4], [5]. Meanwhile, human drivers may react to emergencies by executing inadequate steering maneuvers.…”

Section: Introductionmentioning

confidence: 99%

“…However, in this study a very low value of automation impedance was chosen, resulting in a collision with almost every obstacle encountered during the coupled steering case. Other studies testing the performance of emergency obstacle evasion systems have primarily focused on the influence of haptic and auditory warnings in a decoupled driving paradigm (see, for example, studies by Sieber et al [4] and Hesse et al [12]).…”

Section: Introductionmentioning

confidence: 99%

Comparing Coupled and Decoupled Steering Interface Designs for Emergency Obstacle Evasion

Bhardwaj

Pan

et al. 2021

IEEE Access

View full text Add to dashboard Cite

Automatic evasive steering maneuvers can outperform human-initiated steering maneuvers in emergency situations. A steering interface that decouples the steering wheel from the tires may enhance the efficiency of automatic steering maneuvers by providing full authority to the automation system. Yet, an alternative interface in which the steering wheel remains coupled to the tires has the advantages of enabling the driver to intervene in the event of an automation failure and preventing the human factors issues associated with decoupling the driver. In this paper, we present a driving simulator study with 64 participants where we compared four steering interface design schemes in their ability to enable successful obstacle evasion in emergency scenarios. The steering wheel was either decoupled from the tires and the automation was given full authority, or the steering wheel was coupled to the tires and the automation was provided high, low or no authority. The automation was designed to avoid all obstacles, except for the last one when it failed unexpectedly. Results uncovered a design tradeoff: as the authority of an agent (driver or automation) increases, the protection against the agent's faults (provided by the other agent) reduces. The results also show that decoupled driving reduced driver's vigilance and mode awareness and deprived the drivers of the authority required to intervene during automation faults. Coupled driving alleviated these issues but caused driver discomfort when designed with high automation authority and resulted in a larger number of collisions during perfect automation operation when designed with low automation authority.

show abstract

“…Many researches also showed that in critical situations, braking is favored than steering [3], [4]. Moreover, despite of advanced sensing and control techniques, Advance Driver Assistance System (ADAS) with emergency steering for collision avoidance is not yet available for public [5]. Additionally, drivers tend to perform actions that are against automatic steering assistance at subconscious level [6].…”

Section: Introductionmentioning

confidence: 99%

Brake Maneuver Prediction – An Inference Leveraging RNN Focus on Sensor Confidence

Liu

Koch

Gahr

et al. 2019

2019 IEEE Intelligent Transportation Systems Conference (ITSC)

View full text Add to dashboard Cite

In recent years, driver behavior analysis has led to countless driver assistance systems. In these systems, earlier detection of a driver's maneuver intentions offers opportunities to improve driving experience and safety. Especially brake maneuvers are of fundamental importance because they are directly related to the avoidance of potential hazards. Current state-of-the-art brake assistance systems rely on the release speed of accelerator pedal as an indicator whether a brake event is planned. However, this simple and practical algorithm, fails to capture the overall movement pattern of accelerator pedal behaviors and cannot utilize rich information from different vehicle sensors. To address this issue, we propose a novel recurrent neural network architecture for the purpose of brake maneuver prediction. The proposed method exploits the advantages of multiple sensors. Unlike conventional practices where all signals are aggregated to a single neural network, we leverage the confidence of each sensor. We evaluate our approach based on a dataset of 44 drivers, comprising around 500 hours of naturalistic driving data. The evaluation results show that the proposed algorithm outperforms baseline method by large margin.

show abstract

Automatic Emergency Steering with Distracted Drivers: Effects of Intervention Design

Cited by 14 publications

References 4 publications

An integrated torque-vectoring control framework for electric vehicles featuring multiple handling and energy-efficiency modes selectable by the driver

An integrated torque-vectoring control framework for electric vehicles featuring multiple handling and energy-efficiency modes selectable by the driver

Comparing Coupled and Decoupled Steering Interface Designs for Emergency Obstacle Evasion

Brake Maneuver Prediction – An Inference Leveraging RNN Focus on Sensor Confidence

Contact Info

Product

Resources

About