Assessment of data glasses for motorcycle riders in a simulated lane change test

Relevant riding information such as speed or navigation instructions are typically displayed in head down dashboards on Powered Two-Wheelers. Data glasses provide information directly in the field of view and could, therefore, reduce glances away from the roadway ahead to focus on the dashboard. This study aimed to examine whether providing information in data glasses while riding as compared to classical head down displays makes a difference. Therefore, a total of N = 24 riders completed the ISO lane change test on a motorcycle riding simulator. Meanwhile, riders had to react to changing turn-by-turn indications which were either displayed in the dashboard, in the data glasses or redundantly in both display technologies. The performance in the lane change test and the reaction times achieved in the secondary task were examined along with riders’ workload by means of the Detection Response Task (DRT) and questionnaire data. Results revealed that riders’ lane change performances did not differ between the conditions ‘data glasses’ and ‘dashboard’. Information displayed in the data glasses was recognized faster and fewer turn-by-turn indications were missed. The performance in the DRT remained unchanged throughout the test conditions, while the subjective workload experience decreased with the use of data glasses. Overall, the results suggest that data glasses did not provoke an attentional capture effect and were, therefore, not inferior compared to dashboards regarding riding performance. However, data glasses did reduce the perceived workload and may in particular provide a safety benefit when time-critical information, such as warnings, need to be displayed.     

Evasive action characteristics of motorcycle riders towards occluded-surprise and expected pedestrians: A pedestrian mock-up study

Evasive action performance of motorcycle riders plays a vital role in the prevention of road crashes. In possible conflicting scenarios, motorcycle riders need to respond quickly and perform evasive actions successfully to prevent collisions with other vulnerable road users such as crossing pedestrians. To study the motorcycle rider behavior in conflicts with occluded and visible pedestrians, we designed four mock-up pedestrian scenarios, which includes, two surprise scenarios, one stationary scenario, and one expected scenario. Riders’ responses to the conflicts were measured using instrumented vehicle’s trajectory. Most riders preferred deceleration over swerving at the beginning of the interaction, followed by swerving at manageable speeds. Further, the analysis of riders’ deceleration rates revealed that a linear relationship existed between the deceleration rates and time to collisions (TTC). The study also analyzed the riders’ responses using repeated-measures analysis of variance (RM-ANOVA) to check for the effect of scenario type on deceleration rates. Results indicated that scenario type significantly affected the mean deceleration rates. Further, RM-ANOVA analysis carried out on the jerk behavior of motorcycle riders indicated that there was a significant effect of scenario type on the jerk behavior. Motorcycle riders’ jerks varied linearly with TTC and motorcyclists employ relatively higher decelerations and jerks when faced with pedestrians emerging suddenly from occluded locations such as from the blind spots formed due to parked vehicles. This study helps in understanding motorcycle rider behavior in critical situations and shows the need for assistive evasive systems for motorcycle riders to mitigate collisions with other vulnerable road users.     

Predicting e-bike users’ intention to run the red light: An application and extension of the theory of planned behavior

Electric bike (e-bike) users in China have a high red light running (RLR) rate, contributing to a large number of accidents. This paper aims to examine the psychological motivation of e-bike users’ RLR intentions. A survey questionnaire was designed employing the construct of theory of planned behavior (TPB). The survey was performed in Chengdu, China in November 2016. We found that users older than 40 identify themselves as more cautious riders. Younger riders have higher intention to run the red light. E-bike users with car drivers’ licenses regard running the red light as a more difficult task to perform, and regard this behavior as more morally wrong. Hierarchical regression was used to analyze the data. The results showed that demographic variables (age, marriage status, and college degree), TPB variables (attitude and perceived behavioral control) and extended variables (moral norm and self-identity) are significant predictors for the intention of RLR behavior. The results could provide reference for designing more effective interventions and safety education programs for reducing e-bike users’ RLR rate.     

Conditions for speeding behaviour: A comparison of car drivers and powered two wheeled riders

Against a UK background of decreases in collisions involving car drivers, motorcycle collisions are on the increase. To throw light on this process, this paper explores differences between motorcyclists and car drivers in the conditions for speeding behaviour. Some predictions derived from the model of Task-difficulty Homeostasis (TDH) were tested using self-report data from samples of older (>35 years), male car drivers (n = 269) and motorcyclists (n = 102). As predicted, riders were more likely to speed on rural roads and less likely to speed on urban roads, and, riders were much more likely to speed in daytime than at night.Riding a motorcycle offers opportunities for expressive use of the vehicle and riders are more likely to say they really enjoy riding fast. However amongst older riders this behaviour appears to be largely confined to daytime riding on rural roads. Compared with cars, motorcycles provide more of an opportunity to manoeuvre around obstacles in controlling task demand, rather than using speed as the primary controlling variable. Although this provides more options for the rider, it carries with it vulnerability to loss of control from variation in road surface adhesion and maintaining too high a speed.     

Evaluation of motorized two-wheeler rider responses towards jaywalking pedestrians through mockup control studies for urban streets

This study aims to model the motorized two-wheeler (MTW) riders’ evasive-action behavior towards jaywalking pedestrians using a mockup study. The brake reaction times (BRTs), approach speeds, decelerations, headings, and yaw rates were analyzed for two surprise scenarios (scenarios 1 and 3), one stationary scenario (scenario-2), and one expected scenario (scenario-4). In total, 50 riders participated in the mockup study. The results revealed that the 90th percentile BRT for the expected and surprise scenarios were 3.6 and 1.6 s, respectively. Further, repeated-measures ANOVA was performed followed by mixed effect modeling to ascertain the effect of conflict severity (two groups: group-1 with Time to Collision (TTC) < 1.5 s and group-2 with TTC > 1.5 s) and scenario type (three groups: scenarios 1, 3 and 4) on BRT. The results indicated that the main effects were significant while the interaction effect was not significant. The positive and significant coefficient (0.32) of TTC group-2 indicated higher BRTs than TTC group-1. Considering scenario-1 as the base scenario, the coefficient of scenario 3 (-0.02) indicated that scenario-1 and scenario-3 had a similar effect on BRT, while the coefficient of scenario-4 (1.47) indicated higher BRTs compared to scenario-1. The analysis of evasive action behavior revealed that 32% of riders performed hard braking in surprise scenarios. Further, yaw rate values at the crossing point indicated a loss of control of MTW in 90% of surprise events. The observations from this study provide a basis for developing countermeasures to improve pedestrian and MTW rider safety.