Fallback Level Research Articles

Accuracy requirements for the road friction coefficient estimation of a friction-adaptive automatic emergency steer assist (ESA)

The number of traffic accidents resulting in personal injury and property damage is increasingly being reduced by effective advanced driver assistance systems (ADAS). Nevertheless, many traffic accidents still cannot be prevented today because they are due to wet, snow- and ice-covered roads. For this reason, the Institute of Automotive Engineering (IAE) of the Technical University of Braunschweig is investigating the road friction coefficient sensitivity and adaptation of advanced driver assistance systems (ADAS) currently in series production from 2018 to 2021 as part of the ‘Road Condition Cloud’ research project funded by the German Research Foundation (DFG) to increase driving safety, particularly on wet, snow- and ice-covered roads. In this article, the road friction coefficient sensitivity and adaptation of an automatic emergency steer assist is simulatively investigated. This assist overrides the driver to automatically execute an evasive maneuver. The driving maneuver used is a standardized obstacle-avoidance maneuver that is simulatively repeated on a dry, wet, snow- and ice-covered road. The road friction coefficient sensitivity shows that this test is already failed on a wet road because the simulated vehicle does not pass the second lane without errors. Subsequently, a road friction coefficient adaptation of the emergency steer assist is investigated. This adaptation varies the maximum lateral acceleration of the evasive trajectory depending on an estimated value of the road friction coefficient in order not to exceed the maximum adhesion coefficient of the wheels during the evasive maneuver. Ideally, the estimated value matches the true road friction coefficient so that the second lane is passed without errors even on a wet, snow- and ice-covered road. In contrast, an existing difference determines whether the second lane is reached. Finally, the necessary accuracy requirements of the road friction coefficient estimation are determined in an novel estimation error diagram. A road friction coefficient adaptation increases the driving safety of driver advanced assistance systems (ADAS) that are in series production today and future highly automated driving functions (HAF) and is necessary for automated driving because the driver is not present as a fallback level. The described results were presented before in [1].

Augmented Reality Head-Up Display: A Visual Support During Malfunctions in Partially Automated Driving?

Malfunctions are a major challenge in partially automated driving. During such malfunctions, the driver must be able to adequately take over vehicle guidance without being requested to intervene. This may be particularly difficult in urban areas due to their high complexity and information density. Augmented Reality Head-Up Displays (ARHUDs) may have the potential to support the driver during the monitoring task by providing driving-related information at its required location in the primary field of view. The effects of an ARHUD compared to a Baseline concept in case of malfunctions were investigated in a driving simulation experiment with 52 participants. In a partially automated urban drive, participants experienced a longitudinal and a lateral malfunction in permuted order. The concepts–ARHUD or Baseline– were presented as a between-subject factor. The results showed significantly shorter take-over times when using the ARHUD, resulting in fewer crashes. For those who were able to avoid the crash, no differences in the take-over quality between both concepts were found. There was one difference in visual attention: the attention ratio on the instrument cluster was lower for the ARHUD. In addition, the ARHUD revealed a significantly higher trust and usability rating. However, there were no differences in acceptance and subjective workload between the two concepts. The results showed that the ARHUD has more potential to prevent crashes in the event of malfunctions compared to the Baseline. Nevertheless, the high number of crashes, regardless of the concept, showed the importance of a fallback level for partially automated urban driving.

Effects of non-driving related tasks on mental workload and take-over times during conditional automated driving

BackgroundAutomated driving will be of high value in the future. While in partial-automated driving the driver must always monitor the traffic situation, a paradigm shift is taking place in the case of conditional automated driving (Level 3 according to SAE). From this level of automation onwards, the vehicle user is released from permanent vehicle control and environmental monitoring and is allowed to engage in Non-Driving Related Tasks (NDRT) in his or her newly gained spare time. These tasks can be performed until a take-over request informs the user to resume vehicle control. As the driver is still considered to be the fall-back level, this aspect of taking over control is considered especially critical.MethodsWhile previous research projects have focused their studies on the factors influencing the take-over request, this paper focuses on the effects of NDRT on the user of the vehicle during conditional automated driving, especially on the human workload. NDRT (such as Reading, Listening, Watching a movie, Texting and Monitoring ride) were examined within a static driving simulator at the Institute of Ergonomics & Human Factors with 56 participants in an urban environment. These NDRT were tested for mental workload and the ability to take over in a critical situation. To determine the perceived workload, the subjective workload, psychophysiological activity as well as performance-based parameters of a secondary competing task performed by a were used.ResultsThis study revealed that the selected NDRT vary significantly in their mental workload and that the workload correlates with the length of the time needed for take over control. NDRT which are associated with a high workload (such as Reading or Texting) also lead to longer reaction times.

A Novel Initiative Braking System With Nondegraded Fallback Level for ADAS and Autonomous Driving

A novel compact initiative braking system orienting intelligent vehicles and autonomous driving is revealed. The delicate arrangement of on – off switch valves guarantees precise hydraulic pressure modulation. Integrated stroke simulator provides a well-tuned pedal force feedback. The fallback level is intensively designed to be nondegraded. A hierarchical control frame with the underlying hydraulic controller is designed to govern operation procedures. The underlying hydraulic controller is set up based on adaptive gain scheduling proportion differentiation controller and logic threshold control. Hardware-in-loop tests are carried out in full perspectives. The test result of slope-sine combination tracking shows that, compared with the conventional proportion integration differentiation controller, the designed underlying controller achieves higher pressure modulation accuracy with no chattering effect. Controller robustness to accumulator pressure fluctuation is proven by the dual-cylinder tracking test. A batch of step-response tests under different accumulator pressures shows a rapid pressure building capability in emergency situations under all pressure range. The fail-safe test result indicates that the conventional hydraulic brake can be restored in 1.5 s with the operation of the driver, which significantly increases the margin of brake safety for highly autonomous vehicles. The regenerative braking test result suggests the immense potential of the developed system in an application to electrified vehicles.

Towards guidelines and verification methods for automated vehicle HMIs

In most levels of vehicle automation, drivers will not be merely occupants or passengers of automated vehicles. Especially in lower levels of automation, where the driver is still required to serve as a fallback level (SAE L3) or even as a supervisor (SAE L2), there is a need to communicate relevant system states (e.g., that the automated driving system works reliably or that there is a need for manual intervention) via the Human-Machine Interface (HMI). However, there are currently no agreed-upon guidelines that apply specifically to HMIs for automated driving. In this paper, we summarize design recommendations for visual-auditory and visual-vibrotactile HMIs derived from empirical research, applicable standards and design guidelines pertaining to in-vehicle interfaces. On this basis, we derive an initial set of principles and criteria for guiding the development and design of automated vehicle HMIs. A heuristic evaluation methodology consisting of an itemized checklist evaluation that can be used to verify that basic HMI requirements formulated in the guidelines are met is also presented. The heuristic evaluation involves an inspection of the HMI during typical use cases, judging their compliance with the proposed guidelines and documentation of identified instances of non-compliance. Taken together, the combination of the proposed guidelines and the heuristic evaluation methodology form the basis for both design and validation recommendations of automated vehicle HMIs, that can serve the industry in the important evolution of automation within vehicles.

Effect of different alcohol levels on take-over performance in conditionally automated driving

Automated driving systems are getting pushed into the consumer market, with varying degrees of automation. Most often the driver’s task will consist of being available as a fall-back level when the automation reaches its limits. These so-called take-over situations have attracted a great body of research, focusing on various human factors aspects (e.g., sleepiness) that could undermine the safety of control transitions between automated and manual driving. However, a major source of accidents in manual driving, alcohol consumption, has been a non-issue so far, although a false understanding of the driver’s responsibility (i.e., being available as a fallback level) might promote driving under its influence. In this experiment, N = 36 drivers were exposed to different levels of blood alcohol concentrations (BACs: placebo vs. 0.05% vs. 0.08%) in a high fidelity driving simulator, and the effect on take-over time and quality was assessed. The results point out that a 0.08% BAC increases the time needed to re-engage in the driving task and impairs several aspects of longitudinal and lateral vehicle control, whereas 0.05% BAC did only go along with descriptive impairments in fewer parameters.

Expert-based controllability assessment of control transitions from automated to manual driving

Up to a level of full vehicle automation, drivers will have to be available as a fallback level and take back manual control of the vehicle in case of system limits or failures. Before introducing automated vehicles to the consumer market, the controllability of these control transitions has to be demonstrated. This paper presents a novel procedure for an expert-based controllability assessment of control transitions from automated to manual driving. A standardized rating scheme is developed that allows trained raters to integrate different aspects of driving performance during control transitions (e.g., quality of lateral and longitudinal control, adequateness of signalling to other road users, etc.) into one global controllability measure based on video material of the driving situation. The method is adapted from an existing assessment procedure that has been successfully applied to assess the criticality of driving situations in manual driving conditions (e.g., assessment of substance-induced impairments, assessment of fitness-to-drive of novice drivers). This paper presents the rating procedure, including instructions of how to code relevant qualities of the drivers’ performance with accompanying video-demonstrations, and material used for rater training.•A rating procedure for an expert-based controllability assessment of control transitions from automated to manual driving based on observation of video material was adapted from an existing method used in studies on manual driving.•The advantage of this method consists in an integration of different dimensions of driving performance (e.g., operational and tactical driving behaviour, criticality of the situation) into one global controllability measure.•The method allows an assessment and comparison of diverse take-over scenarios, detached from driver performance variables.•The accompanying video-based training material allows reproducible and reliable execution of the rating procedure.

Fallback level concepts for conventional and by-wire automotive brake systems

Brake-by-wire represents the replacement of traditional brake components such as pumps, hoses, fluids, brake boosters, and master cylinders by electronic sensors and actuators. The different design of these brake concepts poses new challenges for the automotive industry with regard to availability and fallback levels in comparison to standard conventional brake systems. This contribution focuses on the development of appropriate fallback level concepts. Hardware-in-the-loop (HIL) techniques and field trials will be used to investigate the performance and the usability of such systems.

The self-energising hydraulic brake

Driver assistance systems require for low-power electrical interfaces for braking control. At the same time for safety reasons a mechanical fallback level should be provided. At the Institute of Fluid Power Drives and Controls of the RWTH Aachen University (Germany) an innovative Self-Energising Hydraulic Brake is being developed to solve this conflict of objectives. Besides its low power consumption it features a closed loop control of the actual braking torque. The presented measuring results demonstrate the brake’s development potential for cars and utility vehicles.