Australian parents’ willingness to use a rideshare vehicle to transport their unaccompanied children

This study aimed to identify the key factors associated with Australian parents' willingness to use a rideshare vehicle to transport their unaccompanied child(ren). Six hundred and thirty-one participants completed an online survey (M = 39.2 years, SD = 10.5, Range = 18.0–70.0 years; Female: 63.4%). Most participants (62.1%) reported that they would 'never' use a rideshare vehicle to transport their unaccompanied child(ren). The results of a logistic regression model showed that participants': previous use of a rideshare vehicle with their child, annual mileage, propensity for technology adoption, aberrant driving behaviours, as well their requirements for vehicle features were significantly associated with their willingness to use a rideshare vehicle to transport their unaccompanied child, χ2(7) = 159.59, p < 0.001. Overall, the findings suggest that Australian parents are mostly ‘unwilling’ to use a rideshare vehicle to transport their unaccompanied children. Understanding the views of parents towards emerging transportation modes for their children is crucial for urban planning, traffic engineering, economic and social mobility and ultimately, on supporting safe modes of transportation.     

External communication of automated vehicles in mixed traffic: Addressing the right human interaction partner in multi-agent simulation

The urban traffic system is most likely to change in the next years to a mixed traffic with human drivers, vulnerable road users, and automated vehicles. In the past, the development of external communication approaches for automated vehicles focused on scenarios where an automated vehicle communicates with either a pedestrian or a human driver. However, interactions with more than one traffic partner are more realistic. Therefore, a study with 42 participants was conducted with a multi-agent simulation in which an automated vehicle interacted simultaneously with two participants, a pedestrian and a driver of a manual vehicle. In this study, two main scenarios were investigated in order to evaluate the safety and efficiency of the interactions and to determine whether the human road users feel correctly addressed. In one scenario, the pedestrian had to cross the road in front of the automated and the manual vehicle, which were approaching from different sides. In the other, the manual vehicle had to drive through a bottleneck in front of the oncoming automated vehicle, while the pedestrian had to cross the road after both vehicles passed. The communication approach of the automated vehicle consisted of implicit signals using a speed profile and lateral offset within its lane, and explicit signals using an external human–machine interface. The results of the study show that no collisions were observed in terms of safety and no significant negative effects on efficiency were measured. However, in contrast to single agent interactions, a majority of participants felt wrongly addressed in situations where the automated vehicle signals the right-of-way to the other human road user. It can be concluded that the communication approach of the automated vehicle needs to be modified in order to address certain road users more clearly.     

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.     

How to identify the take-over criticality in conditionally automated driving? An examination using drivers’ physiological parameters and situational factors

Autonomous vehicles and advanced driver assistance technology are growing exponentially, and vehicles equipped with conditional automation, which has features like Traffic Jam Pilot and Highway Assist, are already available in the market. And this could expose the driver to a stressful driving condition during the takeover mission. To identify stressful takeover situations and better interact with automated systems, the relationship and effect between drivers’ physiological responses, situational factors (e.g., takeover request [TOR] lead time, takeover frequencies, and scenario types), and takeover criticality were investigated.34 participants were involved in a series of takeover events in a simulated driving environment, which are varied by different TOR lead time conditions and driving scenes. The situational factors, drivers’ skin conductance (SC), heart rate (HR), gaze behaviors, and takeover criticality ratings were collected and analyzed. The results indicated that drivers had a higher takeover criticality rating when they experienced a shorter TOR lead time level or at first to fourth take-overs. Besides, drivers who encountered a dynamic obstacle reported higher takeover criticality ratings when they were at the same Time to collision (TTC). We also observed that the takeover situations of higher criticality have larger driver’s maximum HR, mean pupil size, and maximum change in the SC (relative to the initial value of a takeover stage). Those findings of situational factors and physiological responses can provide additional support for the designing of adaptive alert systems and environmental soothing technology in conditionally automated driving, which will improve the takeover performances and drivers’ experience.     

The role of values in road safety culture: Examining the valuation of freedom to take risk,risk taking and accident involvement in three countries

National focus on individual freedom versus paternalistic values is a fundamental theme, which defines the status of traffic safety in different countries. The present study examines the role of such values in road safety culture based on survey data from car and bus drivers from three countries with distinctly different road safety records: Norway (N = 596), Israel (N = 129) and Greece (N = 386). While Norway has the highest road safety level in Europe, and Israel also performs better than the EU average, the road safety level in Greece was far below the EU average. As these positions reflect differences in policies and national regulations in drivers’ freedom to take risk, we hypothesize a higher focus on individual freedom to take risk and lower focus on paternalism among the Greek drivers. Results indicate, in accordance with our hypothesis, that the Greek drivers value freedom to take risk in traffic higher than drivers from Norway and Israel. Greek drivers also expect higher levels of risk taking from other drivers in their country, they report higher levels of risky driving themselves, and are more often involved in accidents. Thus, it seems that values have an important role in Road Safety Culture (RSC), legitimizing and motivating risky driving, which are related to accidents. We found, however, contrary to our hypotheses, that the Greek drivers also had the most paternalistic attitudes among the drivers in the three countries. In the present paper, we try to solve this Greek paradox.     

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.     

Personality and demographic differences in the perceived risks of potentially timid driving behaviours

Timid driving behaviours can be described as overly cautious and hesitant driving behaviours. Little research has examined behaviours that potentially resemble timid driving and how these behaviours are perceived by other drivers. This is despite the potential for these behaviours to be perceived in a way that leads to angry and aggressive retaliatory behaviours in some drivers (e.g., in anger-prone drivers). We conducted an online survey examining the perceived road safety risks of several behaviours that could potentially result from timid driving and their relationships with driver personality (trait anxiety, trait driving anger), behaviour (anxious driving, angry driving), and demographic (age, gender, annual mileage) background. Drivers (N = 439, M_age = 49.41 ± 5.59 years, aged 18–89) perceived excessively cautious and unpredictable braking behaviours as posing moderate levels of risk. Multiple linear regression analyses also indicated higher perceived risks of slow and excessively cautious behaviours in older, male, and anger prone drivers. No meaningful associations were found between driver characteristics and the risks of unpredictable braking behaviours. These results suggest that safety campaigns to reduce aggressive behaviour may benefit from targeting the perceptions of other drivers’ behaviours.     

Driving self-regulation and risky driving outcomes

Self-regulation has been associated with risky driving outcomes in the past but there are no available measures to assess driving-specific self-regulatory capacity. The present study assessed the association of a newly developed driving self-regulation measure with driving violations, errors, and lapses. Overall, 330 UK drivers completed measures of risky driving outcomes, driving anger, trait impulsivity, sensation seeking, normlessness, domain-general trait self-regulation plus a new unidimensional measure of Driving Self-Regulation Questionnaire (DSRQ-16). Bivariate correlation analysis indicated that the DSRQ-16 showed expected associations with both driving-related outcomes and factors, as well as with impulsivity traits and general self-regulation. Bootstrapped hierarchical linear regression models showed that the DSRQ-16 was significantly associated with driving violations, errors, and lapses after controlling for the effects of other relevant predictors. This is the first study to demonstrate the association of driving-specific self-regulation with risky driving behaviour, driving anger, impulsivity and related personality traits. Driving-specific self-regulation may present a novel target for road safety interventions, as well as a theoretically relevant component of models of risky driving behaviour.     

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.