Driving,Pseudo‐reality and the BTK: A Case Study

The significance of occupational choice, in particular those that involve driving, has not yet been studied or investigated in relation to serial murder. This paper, which adopts a case study approach, attempts to shed light on how driving as an occupation may instrumentally influence the offending behaviour of one North American serial murderer—Dennis Rader. Attention is given towards how spending such significant amounts of time driving may have held deep psychological importance for Rader, with regard to the development of his offending‐oriented fantasies. In particular, the “offending space model” is used to examine the relationship between ‘thinking and doing’. In providing this micro‐level analysis, we suggest that transient oriented occupations provide a rich array of practical advantages that may aid serial murderers in avoiding detection, whilst also holding deep psychological influence in the nurturing and development of their fantasies. Copyright © 2015 John Wiley & Sons, Ltd.     

An Intriguing Third Way: Mapping Contextual Education for Curricular Integration

This article emerges from the experience of incorporating doctoral students into our Contextual Education (CXE) Program at Emmanuel College (Toronto). This change, I argue, helped us to distinguish more clearly among and thus distinctly orient the different kinds of relationships and theological practices that make up our program towards the often‐elusive goal of curricular integration. After outlining a definition of integration, I contextualize that definition in our particular practices at Emmanuel College using Kathryn Tanner's (1997) understanding of theology as a cultural practice as my guide. I then offer a brief overview of our CXE Programs to demonstrate how nurturing strategic partnerships within them has made certain forms of integration possible for our students. I close with some activities for practical application in other CXE contexts.     

Drunk driving offenders’ knowledge and behaviour in relation to alcohol-involved driving in Yinchuan and a comparison with Guangzhou,China

ObjectiveThis study was conducted after a legislative amendment criminalising drunk driving (BAC > 80 mg/100 ml) had been in force for a year and investigated whether drunk driving offenders in Yinchuan, China were aware of the law, and whether their knowledge of and exposure to enforcement and the existence of alcohol use disorders were related to their alcohol-involved driving behaviour. The results were compared with results from an earlier study in Guangzhou, China.MethodA survey was conducted from July to October 2012 in Yinchuan to collect information on drunk driving offenders’ knowledge and practice in relation to alcohol-involved driving. The Alcohol Use Disorders Identification Test (AUDIT) was used to assess hazardous drinking levels. In total, 106 drunk driving offenders were recruited while in detention. The findings were compared with those of the Guangzhou study, where the same procedure was used to recruit 101 drunk driving offenders.ResultsThe mean age of the sample was 31.7 years (SD = 8.1; range 17–59 years). Males constituted 96% of the sample. The mean age at which offenders reported starting to drink alcohol was 18.7 years (SD = 3.2; range 10–26 years). Driver’s licenses had been held for an average of 8.5 years. The status of knowledge in relation to alcohol-involved driving in Yinchuan was slightly lower in proportion than in Guangzhou. The rate of alcohol-involved driving reported in the previous 12 months in Yinchuan (43%) was slightly higher than in Guangzhou (39%). The proportion of recidivists in Guangzhou (21.8%) was higher than Yinchuan’s (10.4%). On average, offenders had experienced 1.6 police alcohol breath tests in the previous year (SD = 1.3; range 1–10). AUDIT scores indicated that a substantial proportion of the offenders had high levels of alcohol use disorders.DiscussionLimited awareness of legal alcohol limits might contribute to drunk driving offences. The high level of alcohol consumption by many offenders suggests that hazardous drinking levels may be a contributor. Recidivist drivers also had higher AUDIT scores, which suggest there may be benefit in using the AUDIT to identify potential drink drivers and recidivists, subject to further research.     

The influence of age on the take-over of vehicle control in highly automated driving

The growing proportion of older drivers in the population plays an increasingly relevant role in road traffic that is currently awaiting the introduction of automated vehicles. In this study, it was investigated how older drivers (⩾60 years) compared to younger drivers (⩽28 years) perform in a critical traffic event when driving highly automated. Conditions of the take-over situation were manipulated by adding a verbal non-driving task (20 questions task) and by variation of traffic density. Two age groups consisting of 36 younger and 36 older drivers drove either with or without a non-driving task on a six-lane highway. They encountered three situations with either no, medium or high traffic density where they had to regain vehicle control and evade an obstacle on the road. Older drivers reacted as fast as younger drivers, however, they differed in their modus operandi as they braked more often and more strongly and maintained a higher time-to-collision (TTC). Deterioration of take-over time and quality caused by increased traffic density and engagement in a non-driving task was on the same level for both age groups. Independent of the traffic density, there was a learning effect for both younger and older drivers in a way that the take-over time decreased, minimum TTC increased and maximum lateral acceleration decreased between the first and the last situation of the experiment. Results highlight that older drivers are able to solve critical traffic events as well as younger drivers, yet their modus operandi differs. Nevertheless, both age groups adapt to the experience of take-over situations in the same way.     

Secondary task engagement and vehicle automation – Comparing the effects of different automation levels in an on-road experiment

Recent and upcoming advances in vehicle automation are likely to change the role of the driver from one of actively controlling a vehicle to one of monitoring the behaviour of an assistant system and the traffic environment. A growing body of literature suggests that one possible side effect of an increase in the degree of vehicle automation is the tendency of drivers to become more heavily involved in secondary tasks while the vehicle is in motion. However, these studies have mainly been conducted in strictly controlled research environments, such as driving simulators and test tracks, and have mainly involved either low levels of automation (i.e., automation of longitudinal control by Adaptive Cruise Control (ACC)) or Highly automated driving (i.e., automation of both longitudinal and lateral control without the need for continuous monitoring). This study aims to replicate these effects during an on-road experiment in everyday traffic and to extend previous findings to an intermediate level of automation, in which both longitudinal and lateral control are automated but the driver must still monitor the traffic environment continuously (so-called Partial automation). N = 32 participants of different age groups and different levels of familiarity with ACC drove in rush-hour traffic on a highway segment. They were assisted by ACC, ACC with steering assistance (ACC+SA), or not at all. The results show that while subjective and objective driving safety were not influenced by the degree of automation, drivers who were already familiar with ACC increased the frequency of interactions with an in-vehicle secondary task in both assisted drives. However, participants generally rated performing the secondary task as less effortful when being assisted, regardless of the automation level (ACC vs. ACC+SA). The results of this on-road experiment thus validate previous findings from more-controlled research environments and extend them to Partially automated driving.     

Effects of explanation-based knowledge regarding system functions and driver’s roles on driver takeover during conditionally automated driving: A test track study

The present study was designed to examine the influence of explanation-based knowledge regarding system functions and the driver’s role in conditionally automated driving (Level 3, as defined in SAE J3016). In particular, we studied how safely and successfully drivers assume control of the vehicle when encountering situations that exceed the automation parameters. This examination was conducted through a test-track experiment. Thirty-two younger drivers (mean age = 37.3 years) and 24 older drivers (mean age = 71.1 years) participated in Experiments 1 and 2, respectively. Adopting a between-participants design, in each experiment the participants were divided into two age- and sex-matched groups that were given differing levels of explanation-based knowledge concerning the system limitations of automated driving. The only information given to the less-informed groups was that, during automated driving, drivers may be required to occasionally assume control of the vehicle. The well-informed groups were given the same information, as well as details regarding the auditory-visual alerts produced by the human–machine interface (HMI) during requests to intervene (RtIs), and examples of situations where RtIs would be issued. Ten and nine RtI events were staged for each participant in Experiment 1 and 2, respectively; the participants performed a non-driving-related task while the automated driving system was functioning. For both experiments it was found that, for all RtI events, more participants in the well-informed groups than the less-informed groups successfully assumed control of the vehicle. These results suggest that, in addition to providing information regarding the possible occurrence of RtIs, explanations of HMI and RtI-related situations are effective for helping both younger and older drivers safely and successfully negotiate such events.     

Are novice drivers competent to take over control from level 3 automated vehicles? A comparative study with experienced drivers

With level 3 automated vehicles poised to appear on the roads soon, takeover remains a major challenge. At present, the effect of manual driving experience on takeover performance is unknown. Therefore, a simulator study was conducted to investigate the influence of driving experience (novice and experienced) on takeover performance in different takeover time budgets (7 s and 5 s) and in combination with a visual secondary task (i.e., surrogate reference task). Data from 48 young and middle-aged participants consisting of 24 novice and 24 experienced drivers were used for this study. Researchers found that the overall stability of evasive maneuvers by novice drivers was considerably worse than that by experienced drivers. A detailed analysis showed that the influence of driving experience on takeover stability was mainly reflected in longitudinal control rather than lateral control. A significant interaction between driving experience and visual secondary task showed that the latter had a substantial impact on the takeover stability of experienced drivers but not on that of novice drivers. Researchers also found that rich manual driving experience cannot make the takeover process of experienced drivers more stable than that of novice drivers under conditions of eye-off-road. In addition, no significant difference was found between novice and experienced drivers in automation disengagement time, takeover time and minimum time to collision. Results indicate that novice drivers have poor takeover stability and weak adaptability, but their longitudinal collision risk is not deteriorated by the lack of manual driving experience.     

Effects of visual factors during automated driving of mobility scooters on user comfort: An exploratory simulator study

An automated mobility scooter is expected to provide convenient and safe transportation for users in their living area. However, there is limited research on user comfort compared to that on user safety for the automated driving of mobility scooters. Because the user does not perform driving tasks in automated driving, the visual information from the peripheral environment and visual behavior is expected to closely affect the psychological comfort of the user. This study clarifies the effects of factors related to the automated driving of mobility scooters and the peripheral environment on the visual behavior and psychological comfort of the user. Effects of driving velocity and pedestrian density on the visual behavior and psychophysiological responses of users were investigated via a driving simulator. The results showed that automated driving in an environment with a high pedestrian density can result in a decrease in fixation duration, deactivation of visual processing, sympathetic activation, and feeling of negative emotion. This implies that the assessment of visual behaviors of users is important for the design of automated mobility scooters to improve user comfort.     

Measuring drivers’ takeover performance in varying levels of automation: Considering the influence of cognitive secondary task

Mixed control by driver and automated system will remain in use for decades until fully automated driving is perfected. Thus, drivers must be able to accurately regain control of vehicles in a timely manner when the automated system sends a takeover request (TOR) at its limitation. Therefore, determining the factors that affect drivers’ takeover quality at varying levels of automated driving is important. Previous studies have shown that visually distracting secondary tasks impair drivers’ takeover performance and increase the subjective workload. However, the influence of purely cognitive distracting secondary tasks on drivers’ takeover performance and how this influence varies at different levels of automation are still unknown. Hence, a 5 (driving modes) × 3 (cognitive secondary tasks) factorial design with the within-subject factors was adopted for this driving simulator experiment. The sample consisted of 21 participants. The participants’ subjective workloads were recorded by the NASA-Task Load Index (NASA-TLX). Results showed that compared to manual driving conditions, the drivers’ subjective workloads were significantly reduced in both partially and highly automated driving conditions, even with a TOR, confirming the benefit of the automated driving system in terms of reducing the driving workload. Moreover, the drivers exhibited a lower takeover behavior quality at high levels of automation than manual driving in terms of increased reaction time, abnormal performance, standard deviation of lane position, lane departure probability, and reduced minimum of time to collision. However, at the highly automated driving condition, the drivers’ longitudinal driving safety and ability to follow instructions improved when performing a highly cognitive secondary task. This phenomenon possibly occurred because automated driving conditions lead to an underload phenomenon, and the execution of highly cognitive tasks transfers drivers into moderate load, which helps with the drivers’ takeover performance.