Effect of multimodal takeover request issued through A-pillar LED light,earcon, speech message,and haptic seat in conditionally automated driving

The driver of a conditionally automated vehicle equivalent to level 3 of the SAE is obligated to accept a takeover request (TOR) issued by the vehicle. Considerable research has been conducted on the TOR, especially in terms of the effectiveness of multimodal methods. Therefore, in this study, the effectiveness of various multimodalities was compared and analyzed. Thirty-six volunteers were recruited to compare the effects of the multimodalities, and vehicle and physiological data were obtained using a driving simulator. Eight combinations of TOR warnings, including those implemented through LED lights on the A-pillar, earcon, speech message, or vibrations in the back support and seat pan, were analyzed to clarify the corresponding effects. When the LED lights were implemented on the A-pillar, the driver reaction was faster (p = 0.022) and steering deviation was larger (p = 0.024) than those in the case in which no LED lights were implemented. The speech message resulted in a larger steering deviation than that in the case of the earcon (p = 0.044). When vibrations were provided through the haptic seat, the reaction time (p < 0.001) was faster, and the steering deviation (p = 0.001) was larger in the presence of vibrations in the haptic seat than no vibration. An interaction effect was noted between the visual and auditory modalities; notably, the earcon resulted in a small steering deviation and skin conductance response amplitude (SCR amplitude) when implemented with LED lights on the A-pillar, whereas the speech message led to a small steering deviation and SCR amplitude without the LED lights. In the design of a multimodal warning to be used to issue a TOR, the effects of each individual modality and corresponding interaction effects must be considered. These effects must be evaluated through application to various takeover situations.     

Assessing the potential impacts of connected vehicle systems on Driver’s situation awareness and driving performance

Vehicles equipped with connected vehicle technologies are able to communicate with each other and with infrastructures. Compared to Advanced Driving Assistance Systems (ADAS) using camera systems and sensor technologies, the Connected Vehicle Systems (CVS) leverage the wireless communication networks to detect hazards with a greater range, alert drivers of hazards much earlier, and therefore enhance driving safety. However, drivers’ reliance on the CVS to detect critical situations could negatively affect them maintaining situation awareness (SA) in noncritical situations when no warning is issued by the CVS. The present study conducted a driving simulator experiment with 40 participants to investigate the effect of connected vehicle systems on driver SA in normal, noncritical driving scenarios after they were exposed to the CVS with different designs of collision warning lead time (3 s, 6 s, and no warnings). After drivers experienced the CVS-supported warnings with the assigned design of lead time in critical situations, driver SA was measured in normal driving conditions using the freeze probe technique. Results revealed that drivers who experienced the CVS with early warnings (6 s) showed lower SA for normal driving events compared to those who experienced the CVS with late warnings (3 s) or no warnings. Although early warnings of CVS brought more safety benefits to drivers in critical situations, the degraded driver SA due to drivers’ reliance on such warning systems could endanger drivers when a system failure occurred. These findings highlight the importance of balancing the effects of warning lead time on driver SA and driving performance in designing connected vehicle systems.     

Behavior model and guidance strategies of the crossing behavior at unsignalized intersections in the connected vehicle environment

The connected vehicle environment is considered to be a disruptive technology that reconstructs the way people travel and road transport, and more importantly, ensures traffic safety. This study aims on investigating drivers’ interactive behavior at an unsignalized intersection in the connected vehicle environment. Specifically, a simplified iterative behavior model was established to predict the potential conflicting vehicles’ behavior. Furthermore, based on principles of safety, efficiency, and comfort, the guidance strategies were proposed to help the subject vehicles cross intersections. A multi-user driving simulator experiment was carried out and 48 participants were divided into 24 pairs to complete the test. The simplified iterative behavior model was constructed based on the dynamic interaction of each participant pair as they approached the intersection from straight-crossing directions. The comparison results showed the behavior model was an effective microscopic simulation tool for vehicles at unsignalized intersections with high accuracy and good applicability. Then, the guidance strategies under different compliance rates (baseline, 50 % compliance, 100% compliance) were evaluated based on three indexes i.e. standard deviation of speed (SDS), duration of crossing the intersection (DCI), and time exposed post-encroachment-time (TEP). The numerical simulation results showed that the guidance strategies could effectively improve the safety and efficiency of drivers crossing the intersection under both 50% and 100% compliance rates. Besides, with the increase of compliance rate, the comfort level also increased evidently. This study can provide theoretical and algorithmic references for microscopic simulation and guidance strategy at unsignalized intersections in the connected vehicle environment.     

Evaluating the influence of approaching vehicles on pedestrian’s visual patterns and crossing behaviors at an uncontrolled crosswalk

The visual behaviors and movement characteristics of pedestrians are related to their surrounding potential safety hazards, such as approaching vehicles. This study primarily aimed to investigate the visual patterns and walking behaviors of pedestrians interacting with approaching vehicles. Field experiments were conducted at two uncontrolled crosswalks located at the Cuihua and Yanta roads in Xi’an, China. The visual performance of pedestrians was assessed using the eye tracking system from SensoMotoric Instruments (SMI). Moreover, motion trajectories of the pedestrians and approaching vehicles were obtained using an unmanned aerial vehicle. Subsequently, the visual attributes and movement trajectories of pedestrians and motion trajectories of approaching vehicles were statistically analyzed. The results showed that approaching vehicles distracted the fixation of crossing pedestrians significantly, and occupied 29.5% of the total duration of fixation; that is, pedestrians always directed more fixation points to the approaching vehicles compared to other stimuli. As a vehicle approached, pedestrians’ fixation shifted from other areas of interest to the vehicle. Moreover, an increase in the velocity of the vehicle and a closer distance between pedestrian and the vehicle resulted in an increase in the pedestrians’ duration of fixation on the approaching vehicle, and they implemented more saccades. Furthermore, approaching vehicle’s velocity and distance between pedestrian and approaching vehicle are not significantly associated with pedestrian’s movement attributes. These findings provide insights into the crossing behavior of pedestrians during pedestrian-vehicle interactions, which could assist future researchers and policy makers.     

User acceptance of automated shuttles in Berlin-Schöneberg: A questionnaire study

Automated shuttles are now in a prototyping phase in several research projects. However, there is still a paucity of knowledge on the acceptance of these shuttles. This paper presents the results of a questionnaire study among individuals (n = 384) who physically experienced an automated shuttle on an office campus in Berlin-Schöneberg. The findings indicate that the respondents were positive towards automated shuttles and could envision their use as feeders to public transport systems, in both urban and rural areas. The respondents were less satisfied with the effectiveness of the shuttle compared to their existing form of travel, the speed of the shuttle, and the space for luggage. A principal component analysis resulted in the retention of three components: (1) intention to use, (2) shuttle and service characteristics, and (3) shuttle effectiveness compared to existing transport. Older respondents expressed a higher intention to use, but found the shuttle less effective than their existing travel. We argue that automated shuttles are a valued concept, but speed and efficiency have to improve, in order for automated shuttles to become viable on a wide scale. Future research should use more objective measures and establish long-term effects in larger, more representative samples.     

Human factors of transitions in automated driving: A general framework and literature survey

The topic of transitions in automated driving is becoming important now that cars are automated to ever greater extents. This paper proposes a theoretical framework to support and align human factors research on transitions in automated driving. Driving states are defined based on the allocation of primary driving tasks (i.e., lateral control, longitudinal control, and monitoring) between the driver and the automation. A transition in automated driving is defined as the process during which the human-automation system changes from one driving state to another, with transitions of monitoring activity and transitions of control being among the possibilities. Based on ‘Is the transition required?’, ‘Who initiates the transition?’, and ‘Who is in control after the transition?’, we define six types of control transitions between the driver and automation: (1) Optional Driver-Initiated Driver-in-Control, (2) Mandatory Driver-Initiated Driver-in-Control, (3) Optional Driver-Initiated Automation-in-Control, (4) Mandatory Driver-Initiated Automation-in-Control, (5) Automation-Initiated Driver-in-Control, and (6) Automation-Initiated Automation-in-Control. Use cases per transition type are introduced. Finally, we interpret previous experimental studies on transitions using our framework and identify areas for future research. We conclude that our framework of driving states and transitions is an important complement to the levels of automation proposed by transportation agencies, because it describes what the driver and automation are doing, rather than should be doing, at a moment of time.     

Driver brake vs. steer response to sudden forward collision scenario in manual and automated driving modes

In autonomous vehicle operation, situations may arise when the driver is required to re-engage in manual control of the vehicle. Whether the control handoff from vehicle to human is done in a structured or unstructured manner, the process may be affected by the driver’s state, i.e. distracted or not. The study reported here was designed to measure a non-distracted driver’s response to a sudden forward collision (FC) event, in which the driver would assume manual control of the autonomous vehicle. Three driving scenarios were investigated: autonomous vehicle driven with full collision avoidance support, autonomous vehicle driven without collision avoidance support, and vehicle driven in manual mode.Forty-eight volunteers participated in a simulator study conducted in VIRTTEX. It was found that, at handoff, (1) drivers in manual mode tended to use evasive steering, rather than braking, compared to drivers in both the autonomous modes, (2) between subjects variations in speed were higher for the automation with collision support condition than for the other two scenarios, (3) for both autonomous driving scenarios, drivers reaction times were longer than for manual driving. In some cases the driver response was so late and the distance remaining so reduced that crash avoidance might be unfeasible. At a minimum, results of this study suggest that drivers may benefit from appropriate driver assistance technologies when a crash imminent situation is suddenly encountered.     

First-time experience of critical range situations in BEV use and the positive effect of coping information

A frequently discussed phenomenon in the context of limited range as a usage barrier for battery electric vehicles (BEVs) is range anxiety (i.e., range stress). The objective of the present research was (1) to examine if the effect of first-time experience of a critical range situation on inexperienced BEV drivers’ range experience (e.g., range stress) is rather positive or negative, (2) to examine if providing minimal coping information can enhance this effect and (3) if a positive adaptation effect can be found under different criticality levels regarding the available range. A field experiment was conducted, in which 74 participants drove a BEV in a critical range situation (i.e., experience of a small range safety buffer) on an unaccompanied 94 km round trip. Results indicate that the first-time experience of a critical range situation has a moderate positive effect on range stress (i.e., reduced range stress after the trip compared to range stress before the trip), that coping information can partly enhance range experience and that these positive effects can be found under both examined criticality levels (critical vs. highly critical range situation). The results can be useful to inform strategies aimed at reducing the experience of range stress in the early period of BEV usage.     

Parameter selection based on fuzzy logic to improve UAV path-following algorithms

In order to steer an Unmanned Aerial Vehicle (UAV) and make it follow a desired trajectory, a high level controller is needed. Depending on the control algorithm, one or more parameters have to be tuned, having their values high impact on the performance. In most of the works, these parameters are taken as constant. In this paper, we apply fuzzy logic to select the parameters of the control law and compare this approach with the tuning by constant parameters and with another adjusting method based on the kinematic analysis of the equations of the UAV. After many simulations of the quadrotor following randomly generated paths, we have proved that the fuzzy tuning law is not only a good and feasible solution, but also more general as it can be applied to any trajectory.     

An analytic tableau calculus for a temporalised belief logic

A tableau is a refutation-based decision procedure for a related logic, and is among the most popular proof procedures for modal logics. In this paper, we present a labelled tableau calculus for a temporalised belief logic called TML⁺, which is obtained by adding a linear-time temporal logic onto a belief logic by the temporalisation method of Finger and Gabbay. We first establish the soundness and the completeness of the labelled tableau calculus based on the soundness and completeness results of its constituent logics. We then sketch a resolution-type proof procedure that complements the tableau calculus and also propose a model checking algorithm for TML⁺ based on the recent results for model checking procedures for temporalised logics. TML⁺ is suitable for formalising trust and agent beliefs and reasoning about their evolution for agent-based systems. Based on the logic TML⁺, the proposed labelled tableau calculus could be used for analysis, design and verification of agent-based systems operating in dynamic environments.