Does False and Missed Lane Departure Warnings Impact Driving Performances Differently?

Lane Departure Warning Systems (LDWS) are known to be effective at preventing lane departures. The current study aimed to further investigate the influence of LDWS incorrect warnings along with the warning onset on driving performances. Performances were considered during missed warned lane departure episodes, as well as correctly warned lane departure episodes following incorrectly warned (false or/and missed warning) episodes. In the reported experiment, the incorrect warnings order of presentation was manipulated along with the warning onsets (partial and full lane departure). Results pointed out that a missed warning is impairing driving performances during the missed warned situation, whereas a false warning is impairing driving performances for the subsequent lane departure. Moreover, if false warning impairment is magnified by the occurrence of a subsequent missed warning, this multiplicative effect is restricted to the following lane departure only. These findings bring both theoretical and practical insights. From a theoretical perspective, the human–machine cooperation LDWS model was refined by the adjunction of a transitional influence of incorrect warnings on the information processing. From a practical perspective, the recommendation to avoid false warnings as much as missed warnings was made.     

Effects of single versus multiple warnings on driver performance

OBJECTIVE: To explore how a single master alarm system affects drivers' responses when compared with multiple, distinct warnings. BACKGROUND: Advanced driver warning systems are intended to improve safety, yet inappropriate integration may increase the complexity of driving, especially in high workload situations. This study investigated the effects of auditory alarm scheme, reliability, and collision event type on driver performance. METHOD: Using a 2 x 2 x 4 mixed factorial design, we investigated the impact of two alarm schemes (master vs. individual) and two levels of alarm reliability (high and low) on distracted drivers' performance across four collision event types (frontal collision warnings, left and right lane departure warnings, and warnings for a fast-approaching following vehicle). RESULTS: Participants' reaction times and accuracy rates were significantly affected by the type of collision event and alarm reliability. The use of individual alarms, rather than a single master alarm, did not significantly affect driving performance in terms of reaction time or response accuracy. CONCLUSION: Even though a master alarm is a relatively uninformative warning, it produced statistically no different reaction times or accuracy results when compared with information-rich auditory icons, some of which were spatially located. In addition, unreliable alarms negatively impacted driver performance, regardless of event type or alarm scheme. APPLICATION: These results have important implications for the development and implementation of multiple driver warning systems.     

Driving comfort,enjoyment and acceptance of automated driving – effects of drivers’ age and driving style familiarity

Automated driving has the potential to improve the safety and efficiency of future traffic and to extend elderly peoples’ driving life, provided it is perceived as comfortable and joyful and is accepted by drivers. Driving comfort could be enhanced by familiar automated driving styles based on drivers’ manual driving styles. In a two-stage driving simulator study, effects of driving automation and driving style familiarity on driving comfort, enjoyment and system acceptance were examined. Twenty younger and 20 older drivers performed a manual and four automated drives of different driving style familiarity. Acceptance, comfort and enjoyment were assessed after driving with standardised questionnaires, discomfort during driving via handset control. Automation increased both age groups’ comfort, but decreased younger drivers’ enjoyment. Younger drivers showed higher comfort, enjoyment and acceptance with familiar automated driving styles, whereas older drivers preferred unfamiliar, automated driving styles tending to be faster than their age-affected manual driving styles.

Practitioner Summary: Automated driving needs to be comfortable and enjoyable to be accepted by drivers, which could be enhanced by driving style individualisation. This approach was evaluated in a two-stage driving simulator study for different age groups. Younger drivers preferred familiar driving styles, whereas older drivers preferred driving styles unaffected by age.     

An Intelligent and Integrated Driver Assistance System for Increased Safety and Convenience Based on All-around Sensing

Advanced driver assistance systems (ADAS) support the driver’s decision making to increase safety and comfort by providing an ergonomic display of the driving environment as well as issuing the warning signals or even exerting active control in case of dangerous conditions. Most previous research and products intend to offer only a single warning service, such as lane departure warning, collision warning, lane change assistance, etc. Although each component of these functions elevates the driving safety and convenience to a certain degree, a new type of ADAS will be developed to integrate all of the important functions with an efficient human–machine interface (HMI) framework for various driving conditions. We present an all-around sensing system based on an integrated ADAS that senses all directions using 2 cameras and 8 sonars, recognizes the driving environment via lane and vehicle detection, and construct a novel bird’s-eye view HMI of the environment for easy comprehension that even gives a proper warning signal in case of imminent danger. It was tested on our experimental vehicle with a good demonstration its working. Further, it has a good potential for commercial use by virtue of the low cost of the sensors used.     

What determines drivers’ speed? A replication of three behavioural adaptation experiments in a single driving simulator study

We conceptually replicated three highly cited experiments on speed adaptation, by measuring drivers’ experienced risk (galvanic skin response; GSR), experienced task difficulty (self-reported task effort; SRTE) and safety margins (time-to-line-crossing; TLC) in a single experiment. The three measures were compared using a nonparametric index that captures the criteria of constancy during self-paced driving and sensitivity during forced-paced driving. In a driving simulator, 24 participants completed two forced-paced and one self-paced run. Each run held four different lane width conditions. Results showed that participants drove faster on wider lanes, thus confirming the expected speed adaptation. None of the three measures offered persuasive evidence for speed adaptation because they failed either the sensitivity criterion (GSR) or the constancy criterion (TLC, SRTE). An additional measure, steering reversal rate, outperformed the other three measures regarding sensitivity and constancy, prompting a further evaluation of the role of control activity in speed adaptation.

Practitioner Summary: Results from a driving simulator experiment suggest that it is not experienced risk, experienced effort or safety margins that govern drivers’ choice of speed. Rather, our findings suggest that steering reversal rate has an explanatory role in speed adaptation.     

Naturalistic study of the risky situations faced by novice riders

This article sets out to identify the typical risky situations experienced by novice motorcyclists in the real world just after licensing. The procedure consists of a follow-up of six novices during their first two months of riding with their own motorbike instrumented with cameras. The novices completed logbooks on a daily basis in order to identify the risky situations they encountered, and were given face-to-face interviews to identify the context and their shortcomings during the reported events. Data show a large number of road configurations considered as risky by the riders (248 occurrences), especially during the first two weeks. The results revealed that a lack of hazard perception skills contributed to the majority of these incidents. These situations were grouped together to form clusters of typical incident scenarios on the basis of their similarities. The most frequent scenario corresponds to a lane change in dense traffic (15% of all incidents). The discussion shows how this has enhanced our understanding of novice riders’ behaviour and how the findings can improve training and licensing. Lastly, the main methodological limitations of the study and some guidelines for improving future naturalistic riding studies are presented.

Practitioner Summary:

This article aims to identify the risky situations of novice motorcyclists in real roads. Two hundred forty-eight events were recorded and 13 incident scenarios identified. Results revealed that a lack of hazard perception contributed to the majority of these events. The most frequent scenario corresponds to a lane change in dense traffic.     

DISCRETE EVENT-DYNAMIC SYSTEMS FOR MODELING DYNAMIC VALUED NETS

The last few years have seen the development of Discrete Event-Dynamic Net Systems^1,2 as instruments for modeling complex systems. They are able to achieve the following objectives:

—formality of the modeling methodology

—ability to model static and dynamic aspects

—ability to pass between levels of differently rich structures by morphisms

—uniform representation of the communication process as

—an information process

—a decision process and

—a control process

—homogeneity of the representation and modeling methods

—ability to derive qualitative and quantitative statements.

The foundation is provided by a Discrete Event-Dynamic Net System which includes the axiomatic declaration of general Petri nets. In order to calculate the structural and dynamic aspects, so-called Petri net machines are developed. It is shown that this approach can even be used to treat the following aspects:

—use of time during the process

—increase of costs during the generation and transportation of information

—augmentation, evaluation and transformation of information objects.

Recursive formulas are derived and some examples calculated.     

The Proactive and Preventive Privacy (3P) Framework for IoT Privacy by Design

The Problem

Internet of Things (IoT) is providing new services and insights by sensing contextual data but there are growing concerns of privacy risks from users that need immediate attention.

The Reason

The IoT devices and smart services can capture Personally Identifiable Information (PII) without user knowledge or consent. The IoT technology has not reached the desired level of maturity to standardize security and privacy requirements.

The Solution

IoT Privacy by Design is a user-centric approach for enabling privacy with security and safety as a ‘win-win’ positive outcome of IoT offerings, irrespective of business domain. The Proactive and Preventive Privacy (3P) Framework proposed in this paper should be adopted by the IoT stakeholders for building trust and confidence in end users about IoT devices and smart services.     

Driving in an urban environment,the stress response and effects of exercise

Driving may be detrimental to health, with one hypothesis suggesting that driving may elicit an acute stress response and, with repeated exposures, may become a chronic stressor. The present study examined the stress response to driving and the effectiveness of a prior exercise bout in dampening this response. Twenty healthy adults performed three tasks: control, driving and exercise plus driving. Heart rate (HR), heart rate variability (HRV), blood pressure (BP) and cortisol were measured to quantify the acute stress response to each condition. Data indicated a stress response to driving: HR was elevated and HRV was reduced during the driving task compared with control. HR was elevated and HRV was reduced comparing the exercise plus driving with the driving condition. BP and cortisol were not different among conditions. The potential of interventions, such as exercise, to counter daily stressors should be evaluated to safeguard long-term health.

Practitioner Summary: this study confirms that driving induces a stress response, with the exercise intervention providing mixed results (an increase in cardiovascular measures and a decrease in cortisol measure trending significance). Given the known consequences of stress and evidence that exercise can mitigate acute stress, further evaluation of exercise interventions is recommended.     

A primal-dual approximation algorithm for the k-prize-collecting minimum vertex cover problem with submodular penalties

In this paper, we consider the k-prize-collecting minimum vertex cover problem with submodular penalties, which generalizes the well-known minimum vertex cover problem, minimum partial vertex cover problem and minimum vertex cover problem with submodular penalties. We are given a cost graph G=(V,E;c) and an integer k. This problem determines a vertex set S\subseteq V such that S covers at least k edges. The objective is to minimize the total cost of the vertices in S plus the penalty of the uncovered edge set, where the penalty is determined by a submodular function. We design a two-phase combinatorial algorithm based on the guessing technique and the primal-dual framework to address the problem. When the submodular penalty cost function is normalized and nondecreasing, the proposed algorithm has an approximation factor of 3. When the submodular penalty cost function is linear, the approximation factor of the proposed algorithm is reduced to 2, which is the best factor if the unique game conjecture holds.     

Gerontechnology acceptance by elderly Hong Kong Chinese: a senior technology acceptance model (STAM)

The purpose of this study was to develop and test a senior technology acceptance model (STAM) aimed at understanding the acceptance of gerontechnology by older Hong Kong Chinese people. The proposed STAM extended previous technology acceptance models and theories by adding age-related health and ability characteristics of older people. The proposed STAM was empirically tested using a cross-sectional questionnaire survey with a sample of 1012 seniors aged 55 and over in Hong Kong. The result showed that STAM was strongly supported and could explain 68% of the variance in the use of gerontechnology. For older Hong Kong Chinese, individual attributes, which include age, gender, education, gerontechnology self-efficacy and anxiety, and health and ability characteristics, as well as facilitating conditions explicitly and directly affected technology acceptance. These were better predictors of gerontechnology usage behaviour (UB) than the conventionally used attitudinal factors (usefulness and ease of use).

Practitioner Summary: Previous studies have not given much consideration to age-related health and associated abilities when examining acceptance of technology by the ageing population. By encompassing conventional technology acceptance constructs together with age-related health and ability characteristics, the present study was able to identify more factors affecting gerontechnology acceptance by older Hong Kong Chinese.     

Push Notifications in Diet Apps: Influencing Engagement Times and Tasks

Background: Smartphones have reached levels of popularity and penetration where they are now suitable for use in population health interventions. A key feature of smartphones is push notification or in app messaging service, which can be used to alert users to messages or instructions pertaining to an installed app. Little evidence exists as to the persuasive power of these messages.

Method: We conducted a 24-week live user evaluation of push notifications used in a behavior-based mobile app for a meal replacement program to understand the role of push notifications in persuading users to engage with self-monitoring tasks.

Results: User perception of the prompts were verified through questionnaires, which in conjunction with the interaction logs show that users were tolerant of multiple daily prompts. The decline in compliance to the tasks set, however, shows that while the participants did not object to receiving prompts, they were less likely to respond to them as the study progressed.

Conclusions: Push notifications and user tasks are appropriate mechanisms to engage users with mobile technology in the short term.     

Variability in decision-making and critical cue use by different road users at rail level crossings

Collisions at rail level crossings (RLXs) are typically high-severity and high-cost, often involving serious injuries, fatalities and major disruptions to the transport network. Most research examining behaviour at RLXs has focused exclusively on drivers and consequently there is little knowledge on how other road users make decisions at RLXs. We collected drivers’, motorcyclists’, bicyclists’ and pedestrians’ self-reported daily experiences at RLXs for two weeks, focusing on behaviour, decision-making and information use in the presence of a train and/or activated RLX signals. Both information use and behaviour differed between road users. Visual information (e.g. flashing lights) was more influential for motorists, whereas pedestrians and cyclists relied more on auditory information (e.g. bells). Pedestrians were also more likely to violate active RLX warnings and/or cross before an approaching train. These results emphasise the importance of adopting holistic RLX design approaches that support cognition and behaviour across for all road users.

Practitioner Summary: This study explores how information use and decision-making at rail level crossings (RLXs) differ between road user groups, using a two-week self-report study. Most users make safe decisions, but pedestrians are most likely to violate RLX warnings. Information use (visual vs. auditory) also differs substantially between road user groups.     

Quantitative Analysis of Situation Awareness (QASA): modelling and measuring situation awareness using signal detection theory

This paper presents a model of situation awareness (SA) that emphasises that SA is necessarily built using a subset of available information. A technique (Quantitative Analysis of Situation Awareness – QASA), based around signal detection theory, has been developed from this model that provides separate measures of actual SA (ASA) and perceived SA (PSA), together with a feature unique to QASA, a measure of bias (information acceptance). These measures allow the exploration of the relationship between actual SA, perceived SA and information acceptance. QASA can also be used for the measurement of dynamic ASA, PSA and bias. Example studies are presented and full details of the implementation of the QASA technique are provided.

Practitioner Summary: This paper presents a new model of situation awareness (SA) together with an associated tool (Quantitative Analysis of Situation Awareness – QASA) that employs signal detection theory to measure several aspects of SA, including actual and perceived SA and information acceptance. Full details are given of the implementation of the tool.     

AUTONOMOUS PLANNING UNDER UNCERTAINTY: PLANNING MODELS

This paper presents a system-theoretic approach to the general problem of autonomous planning under uncertainty. The autonomous planning problem involves an automaton (an autonomous machine) which interacts with an environment via a set of unreliable control and sensing operations. The task assigned to the automaton is to plan and execute a sequence of control and sensing operations which changes the state of the environment in a desirable way.

The paper introduces the concept of an Uncertainty Machine which models the propagation of the information from the environment to the automaton during the execution of the plans. Based on the concept of an uncertainty machine, mathematical expressions are presented for the active-sensing, the passive-sensing and the control (sensorless) entropies of an arbitrary execution instance. These entropies are shown to be useful measures of the automaton's ability to utilize its control and sensing resources in reducing its uncertainty.

In a companion paper,⁷ the concept of an uncertainty machine is utilized to synthesize strategies which enable the automaton to actively explore the environment.     

Measuring working memory load effects on electrophysiological markers of attention orienting during a simulated drive

Intersection accidents result in a significant proportion of road fatalities, and attention allocation likely plays a role. Attention allocation may depend on (limited) working memory (WM) capacity. Driving is often combined with tasks increasing WM load, consequently impairing attention orienting. This study (n = 22) investigated WM load effects on event-related potentials (ERPs) related to attention orienting. A simulated driving environment allowed continuous lane-keeping measurement. Participants were asked to orient attention covertly towards the side indicated by an arrow, and to respond only to moving cars appearing on the attended side by pressing a button. WM load was manipulated using a concurrent memory task. ERPs showed typical attentional modulation (cue: contralateral negativity, LDAP; car: N1, P1, SN and P3) under low and high load conditions. With increased WM load, lane-keeping performance improved, while dual task performance degraded (memory task: increased error rate; orienting task: increased false alarms, smaller P3).

Practitioner Summary: Intersection driver-support systems aim to improve traffic safety and flow. However, in-vehicle systems induce WM load, increasing the tendency to yield. Traffic flow reduces if drivers stop at inappropriate times, reducing the effectiveness of systems. Consequently, driver-support systems could include WM load measurement during driving in the development phase.     

A THEORETICAL STUDY ON ADAPTIVE QUALITY CONTROL SYSTEMS

This paper is a study of an adaptive quality control system from a viewpoint of quality goal. The main purpose is to introduce a conceptual framework for setting up quality goals which are in accordance with the external environment and internal capacity of quality control systems. We apply a mathematical general systems approach.

The results of our paper are summarized as follows:

1)As important decision-making in adaptive QCS, the decision-making for estimalion of fitness and examination of attainability are proposed and formalized mathematically.

2)A refinement process is formalized in which models are revised according to the changes of market.

3)Basic steps for setting quality goals are obtained which are based on the above formalization.     

Novel Autonomous Navigation Algorithms in Dynamic and Unknown Environments

Because the range of mobile robot sensors is limited and navigation maps are not always accurate, autonomous navigation in dynamic and unknown environments is a big challenge. In this article, we propose two novel autonomous navigation algorithms, which are based on the analysis of three conditions for unobserved and uncertain environments during navigation.

The algorithm for a dynamic environment uses the “known space” and “free space” conditions. It corrects false obstacles in the map when the conventional path is stuck. The navigation algorithm for unknown environments uses the “unknown space” and “free space” conditions. We use the Monte Carlo method to evaluate the performance of our algorithms and the other methods. Experimental results show that our autonomous navigation algorithms are better than the others.