Safe driving in a green world: A review of driver performance benchmarks and technologies to support ‘smart’ driving

Road transport is a significant source of both safety and environmental concerns. With climate change and fuel prices increasingly prominent on social and political agendas, many drivers are turning their thoughts to fuel efficient or ‘green’ (i.e., environmentally friendly) driving practices. Many vehicle manufacturers are satisfying this demand by offering green driving feedback or advice tools. However, there is a legitimate concern regarding the effects of such devices on road safety – both from the point of view of change in driving styles, as well as potential distraction caused by the in-vehicle feedback. In this paper, we appraise the benchmarks for safe and green driving, concluding that whilst they largely overlap, there are some specific circumstances in which the goals are in conflict. We go on to review current and emerging in-vehicle information systems which purport to affect safe and/or green driving, and discuss some fundamental ergonomics principles for the design of such devices. The results of the review are being used in the Foot-LITE project, aimed at developing a system to encourage ‘smart’ – that is safe and green – driving.     

Effects of road surface appearance and low friction warning systems on driver behaviour and confidence in the warning system

Warning systems for slippery road conditions are a potential newcomer among driver support systems. A total of 75 participants drove in a high-fidelity driving simulator on roads with both visible and invisible ice, to investigate to which extent drivers rely on a low friction warning system. Three experimental groups with different versions of a low friction warning system and a control group without warning system were compared. All drivers ranked the systems according to trust. A system displaying recommended speed received the best ratings. Driving speed was analysed for three particular segments of the route. Generally, lowest speeds were achieved with the recommended speed system. The participants drove more slowly on a slippery segment that looked icy than on the segments that looked dry when they did not receive a low friction warning. When they received a warning for low friction they also lowered their speed for the segment looking like asphalt. The results provide guidelines for how to present low friction warnings to drivers. The design has substantial effects on the resulting behaviour and therefore it can have a high impact on traffic safety. So far, not much research on low friction warning systems has been reported.     

Modeling task completion time of in-vehicle information systems while driving with keystroke level modeling

The use of touchscreen-based in-vehicle information systems (IVIS) is increasing. To ensure safe driving, it is important to evaluate IVIS task performance during driving situations. Therefore, we proposed a model to assess the task completion time (TCT) of IVIS tasks while driving using a keystroke-level modeling (KLM) technique. The basic assumptions and heuristic rules of driver behaviors were considered. In addition, based on the characteristics of visual and manual IVIS interactions, we determined the basic unit operators (i.e., visual, manual, and mental operators). User experiments were conducted to determine the individual execution times of unit tasks and to measure the TCT of IVIS tasks while driving. Based on the heuristic rules for model development and individual task execution times, we derive a predictive model for the TCT of IVIS tasks. We used a regression analysis to validate the modeling procedure, showing that the observed TCT was found to have a strong positive correlation with the predicted time from the modeling process. The findings showed that the task completion time needed to perform a secondary task in a driving context can be predicted by KLM. This study provides meaningful insights into the design of touchscreen-based IVIS to enhance driving safety.     

Correlation between safety assessments in the driver-car interaction design process

With the functional revolution in modern cars, evaluation methods to be used in all phases of driver–car interaction design have gained importance. It is crucial for car manufacturers to discover and solve safety issues early in the interaction design process. A current problem is thus to find a correlation between the formative methods that are used during development and the summative methods that are used when the product has reached the customer. This paper investigates the correlation between efficiency metrics from summative and formative evaluations, where the results of two studies on sound and navigation system tasks are compared. The first, an analysis of the J.D. Power and Associates APEAL survey, consists of answers given by about two thousand customers. The second, an expert evaluation study, was done by six evaluators who assessed the layouts by task completion time, TLX and Nielsen heuristics. The results show a high degree of correlation between the studies in terms of task efficiency, i.e. between customer ratings and task completion time, and customer ratings and TLX. However, no correlation was observed between Nielsen heuristics and customer ratings, task completion time or TLX. The results of the studies introduce a possibility to develop a usability evaluation framework that includes both formative and summative approaches, as the results show a high degree of consistency between the different methodologies. Hence, combining a quantitative approach with the expert evaluation method, such as task completion time, should be more useful for driver–car interaction design.     

亮度对比及颜色组合对车载界面认知的影响

目的 对车载信息系统界面中亮度对比及颜色组合的认知机理进行分析。方法 采用知觉负载范式,实验A采用6∶1、9∶1、12∶1和18∶1共4种亮度对比水平下的16种颜色组合作为实验材料,对高、中、低载荷下的错误率进行分析。实验B在实验A基础上进行脑电研究。结果 实验A：在高、中载荷下,18∶1的亮度对比显著降低了目标搜索出错率,黄色/黑色、黄色/蓝色和白色/蓝色是搜索错误率最低的3种颜色组合;在低载荷下无显著影响。实验B：脑区地形图表明,在18∶1的亮度对比及颜色组合视觉刺激下,枕叶、前额叶及颞叶脑区激活程度更强;相对于低载荷,高、中载荷的脑区激活程度更弱。ERP的结果分析表明,在18∶1的亮度对比及颜色组合视觉刺激下,O2电极的P100波形的峰值及平均振幅显著高于其他3种亮度对比及颜色组合。结论 车载信息系统界面中的信息元素与界面背景应优先使用高亮度对比（18∶1）,色彩搭配方面应选取黑色或蓝色作为背景色、黄色或白色作为图标文字等信息元素的颜色。