Driver distraction based lane-keeping assistance

Driver assistance systems could be much more effective, if they were adaptive to the driver’s state. Following the idea of a lane-keeping assistance system, which is adaptive to the use of in-vehicle information systems (IVIS), two field experiments were conducted. The first experiment concerned the influence of typical IVIS tasks on lane-keeping. Most IVIS tasks increased the lateral deviations, but in the majority of cases the drivers were still able to stay in their lane.The second experiment concerned two questions: (1) how much lateral support would be needed and (2) how drivers accept this kind of support. The results show that all lateral support algorithms increased the lane-keeping performance with the algorithms providing a higher amount of assistance proving the most useful. All assistance systems were rated as helpful and were considered to increase driver safety, both by the drivers who did not have problems in lane-keeping without assistance.In light of these results an adaptation of a lateral support system to the IVIS-use seems to be useful and worthwhile.     

Did the Market Depress Happiness in the US?

Robert Lane is a seasoned critic of American consumer society. His latest book summarizes many of the arguments brought up earlier and contributes new data about developments in income, companionship and happiness in the USA between 1972 and 1994. Lane notes a considerable rise in incomes over these years and claims that companionship and happiness have declined. He attributes this decline to market forces that emphasize money at the expense of intimate bonds, resulting in a weakened capacity to deal with stress.This review challenges two of the book's hypotheses. First, it shows that happiness did not decline in the USA in these years, but was actually quite stable. Second, it mitigates the assertion that companionship has dwindled and notes that money making and companionship are not necessarily antithetical.Still, Lane could be right. Possibly market forces did depress happiness and possibly that loss was offset by improvements in other fields, like increased freedom or better health care, such as better treatment for mental problems. If so, Lane's message is that Americans could have been happier than they ultimately were.     

Information producing responses in normal and retarded children.

Normal and retarded children were given trials on several discriminations which varied in difficulty. On standard discrimination trials the retarded subjects did not differ from the MA control subjects in the number of errors made but both groups made more errors than the CA control group. On other trials if subjects were not sure which stimulus was correct they were allowed to press an information key which made the discrimination easier. The retarded subjects made significantly more informational key responses than either of the control groups. These results confirmed the findings of prior investigations dealing with outerdirectedness in an experimental situation which did not allow distractibility to be a significant factor.     

Effects of primary task predictability and secondary task modality on lane maintenance

The objective of this work was to investigate the effects of auditory and visuo-spatial secondary tasks on variability in lane position in predictable and unpredictable driving conditions. Sixty-six participants drove a simulated vehicle. Predictability was manipulated by adding wind gusts, and the secondary task load by either an auditory task (Experiment 1) or a visuo-spatial task (Experiment 2). Results demonstrated that in the predictable driving condition, lane position variability decreased when auditory secondary task load was given, but it was not affected by visuo-spatial secondary task load. In the unpredictable driving condition; however, while the auditory secondary task load did not affect lane position variability, visuo-spatial secondary task load increased it. The data suggests that the effects of cognitive load on lane maintenance may depend on the type of the secondary task beside predictability of primary task.     

Crash avoidance and driver assistance technologies – Are they used?

Crash avoidance technologies have potential to mitigate collisions, and actual crash reductions have been identified for some systems. This study measured observed on-off rates of these technologies as an indicator of use, with a focus on lane maintenance systems (i.e., designed to keep vehicles within lanes by warning, braking, and/or steering) and studied factors that might increase their acceptance and use. Vehicles from nine manufacturers fitted with lane maintenance systems were observed at service departments during 2016. Systems were turned on in 51% of 983 vehicles. The activation rate was higher for systems with braking/steering interventions and vibrating warnings and decreased with total mileage. Large proportions of front crash prevention (93%), blind spot monitoring (99%), rear cross-traffic alert (97%), and driver monitoring alert (90%) systems were enabled, and most optional settings were set to factory defaults. Owner surveys linked to observations showed that drivers who had lane maintenance systems turned off believed warnings were distracting and unnecessary compared with drivers whose systems were on.     

Modelling the human lane-change execution behaviour through Multilayer Perceptrons and Convolutional Neural Networks

Driving is a highly complex task that involves the execution of multiple cognitive tasks belonging to different levels of abstraction. Traffic emerges from the interaction of a big number of agents implementing those behaviours, but until recent years, modelling it by the interaction of these agents in the so called micro-simulators was a nearly impossible task as their number grows. However, with the growing computing power it is possible to model increasingly large quantities of individual vehicles according to their individual behaviours. These models are usually composed of two sub-models for two well-defined tasks: car-following and lane-change. In the case of lane-change the literature proposes many different models, but few of them use Computational Intelligence (CI) techniques, and much less use personalization for reaching individual granularity. This study explores one of the two aspects of the lane-change called lane-change acceptance, where the driver performs or not a lane-change given his intention and the vehicle environment. We demonstrate how the lane-change acceptance of a specific driver can be learned from his lane change intention and surrounding environment in an urban scenario using CI techniques such as feed-forward Artificial Neural Network (ANN). We work with Multilayer Perceptron (MLP) and Convolutional Neural Networks (CNN) architectures. How they perform one against the other and how the different topologies affect both to the generalization of the problem and the learning process are studied.     

“What Makes a Cooperative Driver?” Identifying parameters of implicit and explicit forms of communication in a lane change scenario

An automated vehicle needs to learn how human road users communicate with each other in order to avoid misunderstandings and prevent giving a negative outward image during interactions. The aim of the present work is to develop an autonomous driving system which communicates its intentions to change lanes based on implicit and explicit rules used by human drivers. To reach this goal, we aimed at gaining a deeper understanding of which aspects of lane change behaviour makes them cooperative from the perspective of other drivers. Therefore a vehicle used various lane change announcement strategies by varying combinations of driving parameters in a static driving simulator. (First study: Start indicator signal, Waittime, lane change duration; Second study: Longitudinal acceleration). It’s impact on the perception and behaviour of other road users was observed in two studies (N = 25 per study). The results showed that the earlier the merging vehicle was indicating its intentions, the more cooperative it was perceived. When turning on the indicator at a later time participants considered it as more cooperative to merge with a slower or faster lane change duration or to wait longer in the lane before starting to move to the other lane. An early longitudinal acceleration when starting to change lanes is perceived more cooperative. These findings can be used to model a lane change strategy based on human behaviour, which will eventually lead to more acceptable and safer interactions between automated and non-automated road users.     

Developmental changes in attention-deployment skills

The ability to efficiently allocate attention between two tasks differing in payoff was investigated developmentally. Ten subjects from each of three grade levels (second, fourth, and college) performed an auditory and a visual memory task simultaneously. Modality of the primary task, difficulty of the primary task, and difficulty of the secondary task were varied factorially within subjects. The difference between primary and secondary performances increased with age: All college students, about half of the fourth graders, and none of the second graders showed a meaningful degree of differentiation between primary and secondary tasks.     

Temporal fluctuations in driving demand: The effect of traffic complexity on subjective measures of workload and driving performance

Traffic density has been shown to be a factor of traffic complexity which influences driver workload. However, little research has systematically varied and examined how traffic density affects workload in dynamic traffic conditions. In this driving simulator study, the effects of two dynamically changing traffic complexity factors (Traffic Flow and Lane Change Presence) on workload were examined. These fluctuations in driving demand were then captured using a continuous subjective rating method and driving performance measures. The results indicate a linear upward trend in driver workload with increasing traffic flow, up to moderate traffic flow levels. The analysis also showed that driver workload increased when a lane change occurred in the drivers’ forward field of view, with further increases in workload when that lane change occurred in close proximity. Both of these main effects were captured via subjective assessment and with driving performance parameters such as speed variation, mean time headway and variation in lateral position. Understanding how these traffic behaviours dynamically influence driver workload is beneficial in estimating and managing driver workload. The present study suggests possible ways of defining the level of workload associated with surrounding traffic complexity, which could help contribute to the design of an adaptive workload estimator.