Does size matter? Spacious car cockpits may increase the probability of parking violations

Abstract

Cockpit design is a core area of human factors and ergonomics (HF/E). Ideally, good design compensates for human capacity limitations by distributing task requirements over human and interface to improve safety and performance. Recent empirical findings suggest that the mere spatial layout of car cockpits may influence driver behaviour, expanding current views on HF/E in cockpit design. To assess the reliability of findings showing that an expansive driver seat space predicts parking violations, we replicated an original field study in a geographically and socio-culturally different location and included an additional covariate. After controlling for car length, brand status, and car price, driver seat space remained a positive predictor of illegal parking. This suggests that the spatial design of vehicle cockpits may indeed have an influence on driver behaviour and may therefore be a relevant dimension to be included in research and applications of HF/E in cockpit design.

Practitioner summary: In car cockpit design, ergonomists typically focus on optimising human–machine interfaces to improve traffic safety. We replicate evidence showing that increasing physical space surrounding the driver relates to an increased probability of parking violations. This suggests that spatial design should be added to the ergonomist's toolbox for reducing traffic violations.     

Aberrant driving behaviour: errors and violations

The present study was a replication of the research of Reason et al. (1990). Its aim was to confirm the distinction between driving errors and violations in a Western Australian driving population. Sixty-one male drivers and 74 female drivers completed a questionnaire containing items on driver demographics, driving penalties incurred, driving convictions and accident history and driver behavioural aberrations drawn from the Driver Behaviour Questionnaire (DBQ). In agreement with Reason et al. factor analysis revealed three factors; in the present study these were general errors, dangerous errors, and dangerous violations. Young drivers committed more dangerous errors and dangerous violations than older drivers. Females reported more dangerous errors than males. Males reported more dangerous violations than females. Drivers who reported a high level of road exposure and those who reported having been convicted for speeding reported more dangerous violations. Differences in the results of the two studies can largely by accounted for by differences in the representation of age and gender in the two populations studied.     

An evaluation of a lane support system for bus rapid transit on narrow shoulders and the relation to bus driver mental workload

The use of dedicated bus shoulders is a key method for implementing bus rapid transit (BRT) in areas that do not have the space for additional infrastructure. However, the narrow width of the bus shoulder and the need to anticipate traffic hazards in the adjacent lane can both be significant stressors for bus drivers. Bus driver mental workload and stress in response to these conditions should be a significant concern both for operational safety and driver health.

This pilot study evaluated the potential stressors of traffic density and shoulder width in the context of an express BRT service in a large US metropolitan area. In addition, the study considered the potential role of a prototype lane support system (LSS) to support vehicle control within the narrow shoulder boundaries. Ten experienced bus drivers drove an actual route with an instrumented bus equipped with and without LSS. Self-reported effort was recorded along with performance measures of speed and position control relevant to mobility and safety objectives.

Bus drivers did note stressors in the BRT environment and the prototype LSS. However, the use of the shoulder during high-density traffic conditions did improve mobility. Moreover, the LSS did enhance safety on the shoulder when there was high-density traffic in the adjacent lane. However, there was no evidence that the LSS reduced bus driver workload while operating in the narrow shoulder. Future research should consider the impact of BRT operations and support systems on bus driver mental workload and stress, and support the deployment of such devices for bus operations on shoulders during high traffic volumes.     

Traffic sign symbol comprehension: a cross-cultural study

The objective of this study was to evaluate the comprehension levels of highway traffic sign symbols used in different countries, to identify underlying rules that affect comprehension levels, and recommend approaches to deal with the problem. The need for such an evaluation was based on today's travel culture where people are often licensed in one country and then drive—without any further training—in another country. We compared the comprehension levels of different traffic sign symbols in four countries with moderate to high levels of motorization: Canada, Finland, Israel, and Poland. Five different driver populations were sampled in each country: novice drivers, college students, tourists, problem drivers, and older drivers. There were large differences in comprehension among specific sign messages, different countries, and different driver populations. Signs were comprehended best when they were consistent with general ergonomic guidelines for display design as they relate to spatial compatibility, conceptual compatibility, physical representation, familiarity, and standardization. Illustrations of compliance with these principles and violations of these principles are presented, and their implication for traffic safety are discussed. Specific recommendations for sign design that is compliant with ergonomic principles, and for greater international cooperation in sign symbol design are made.     

Traffic sign symbol comprehension: a cross-cultural study

The objective of this study was to evaluate the comprehension levels of highway traffic sign symbols used in different countries, to identify underlying rules that affect comprehension levels, and recommend approaches to deal with the problem. The need for such an evaluation was based on today's travel culture where people are often licensed in one country and then drive--without any further training--in another country. We compared the comprehension levels of different traffic sign symbols in four countries with moderate to high levels of motorization: Canada, Finland, Israel, and Poland. Five different driver populations were sampled in each country: novice drivers, college students, tourists, problem drivers, and older drivers. There were large differences in comprehension among specific sign messages, different countries, and different driver populations. Signs were comprehended best when they were consistent with general ergonomic guidelines for display design as they relate to spatial compatibility, conceptual compatibility, physical representation, familiarity, and standardization. Illustrations of compliance with these principles and violations of these principles are presented, and their implication for traffic safety are discussed. Specific recommendations for sign design that is compliant with ergonomic principles, and for greater international cooperation in sign symbol design are made.     

Errors and violations on the roads: a real distinction?

In considering the human contribution to accidents, it seems necessary to make a distinction between errors and violations; two forms of aberration which may have different psychological origins and demand different modes of remediation. The present study investigated whether this distinction was justified for self-reported driver behaviour. Five hundred and twenty drivers completed a driver behaviour questionnaire (DBQ) which asked them to judge the frequency with which they committed various types of errors and violations when driving. Three fairly robust factors were identified: violations, dangerous errors, and relatively harmless lapses, respectively. Violations declined with age, errors did not. Men of all ages reported more violations than women. Women, however, were significantly more prone to harmless lapses (or more honest) than men. These findings were consistent with the view that errors and violations are indeed mediated by different psychological mechanisms. Violations require explanation in terms of social and motivational factors, whereas errors (slips, lapses, and mistakes) may be accounted for by reference to the information-processing characteristics of the individual.     

Investigating the performance of Hadoop and Spark platforms on machine learning algorithms

One of the most challenging issues in the big data research area is the inability to process a large volume of information in a reasonable time. Hadoop and Spark are two frameworks for distributed data processing. Hadoop is a very popular and general platform for big data processing. Because of the in-memory programming model, Spark as an open-source framework is suitable for processing iterative algorithms. In this paper, Hadoop and Spark frameworks, the big data processing platforms, are evaluated and compared in terms of runtime, memory and network usage, and central processor efficiency. Hence, the K-nearest neighbor (KNN) algorithm is implemented on datasets with different sizes within both Hadoop and Spark frameworks. The results show that the runtime of the KNN algorithm implemented on Spark is 4 to 4.5 times faster than Hadoop. Evaluations show that Hadoop uses more sources, including central processor and network. It is concluded that the CPU in Spark is more effective than Hadoop. On the other hand, the memory usage in Hadoop is less than Spark.

     

Multiple thresholding and subspace based approach for detection and recognition of traffic sign

Automatic detection and recognition of traffic sign has been a topic of great interest in advanced driver assistance system. It enhances vehicle and driver safety by providing the condition and state of the road to the drivers. However, visual occlusion and ambiguities in the real-world scenario make the traffic sign recognition a challenging task. This paper presents an Automatic Traffic Sign Detection and Recognition (ATSDR) system, involving three modules: segmentation, detection, and recognition. Region of Interest (ROI) is extracted using multiple thresholding schemes with a novel environmental selection strategy. Then, the traffic sign detection is carried out using correlation computation between log-polar mapped inner regions and the reference template. Finally, recognition is performed using Support Vector Machine (SVM) classifier. Our proposed system achieved a recognition accuracy of 98.3 % and the experimental results demonstrates the robustness of traffic sign detection and recognition in real-world scenario.

     

Car driver speed choice in Scotland

Drivers who commit driving violations, such as speeding, crash more. Driving violations reduce safety margins amplifying the impact of driver errors. Speed is placed in the context of car use and its attractions. It is argued that speed choice results from the interaction of opportunities, obligations and inclinations. Data from large-scale surveys of Scottish car drivers support this and show that many drivers in Scotland prefer to drive at or below the speed limit and that many say they are currently cutting their normal driving speed. Suggestions for promoting safer and more sustainable speed choices are made.     

Traffic flow harmonization in expressway merging

Steering a vehicle is a task increasingly challenging the driver in terms of mental resources. Reasons for this include the increasing volume of road traffic and a rising quantity of road signs, traffic lights, and other distractions at the roadside (such as billboards), to name a few. The application of Advanced Driver Assistance Systems, in particular if taking advantage of Ambient Intelligence (AmI) technology, can help to increase the perceptivity of a driver, leading as a direct consequence to more relaxed mental stress of the same. One situation where we see potential in the application of such a system are merging areas on the expressway where two or more varying traffic streams converge into a single one. In order to reduce cognitive liabilities (in this work expressed as panic or anger), drivers are exposed to while merging, we have developed two behavioral rules. The first (“increased range of perception”) enables drivers to change early upstream into a spare lane, allowing the merging traffic to join into mainline traffic at reduced conflicts, the second (“inter-car distance management” in the broader area of merging) provide drivers with recommendations of when and how to change lanes at the best. From a technical point of view, the “VibraSeat” a in-house developed car seat with integrated tactile actuators, is used for delivering information about perception range and inter-car distances to the driver in a way that does not stress his/her mental capabilities. To figure out possible improvements in its application in real traffic and at a meaningful scale, cellular automaton–based simulation of a specific section of Madrid expressway M30 was performed. Results from the data-driven simulation experiments on the true to scale model indicate that AmI technology has the potential to increase road throughput or average driving speed and furthermore to decrease the panic of drivers while merging into an upper (the main) lane.     

A quarter of a century of the DBQ: some supplementary notes on its validity with regard to accidents

This article synthesises the latest information on the relationship between the Driver Behaviour Questionnaire (DBQ) and accidents. We show by means of computer simulation that correlations with accidents are necessarily small because accidents are rare events. An updated meta-analysis on the zero-order correlations between the DBQ and self-reported accidents yielded an overall r of .13 (fixed-effect and random-effects models) for violations (57,480 participants; 67 samples) and .09 (fixed-effect and random-effects models) for errors (66,028 participants; 56 samples). An analysis of a previously published DBQ dataset (975 participants) showed that by aggregating across four measurement occasions, the correlation coefficient with self-reported accidents increased from .14 to .24 for violations and from .11 to .19 for errors. Our meta-analysis also showed that DBQ violations (r = .24; 6353 participants; 20 samples) but not DBQ errors (r = ? .08; 1086 participants; 16 samples) correlated with recorded vehicle speed.

Practitioner Summary: The DBQ is probably the most widely used self-report questionnaire in driver behaviour research. This study shows that DBQ violations and errors correlate moderately with self-reported traffic accidents.     

Cognition-Driven Traffic Simulation for Unstructured Road Networks

Dynamic changes of traffic features in unstructured road networks challenge the scene-cognitive abilities of drivers, which brings various heterogeneous traffic behaviors. Modeling traffic with these heterogeneous behaviors would have significant impact on realistic traffic simulation. Most existing traffic methods generate traffic behaviors by adjusting parameters and cannot describe those heterogeneous traffic flows in detail. In this paper, a cognition-driven trafficsimulation method inspired by the theory of cognitive psychology is introduced. We first present a visual-filtering model and a perceptual-information fusion model to describe drivers’ heterogeneous cognitive processes. Then, logistic regression is used to model drivers’ heuristic decision-making processes based on the above cognitive results. Lastly, we apply the high-level cognitive decision-making results to low-level traffic simulation. The experimental results show that our method can provide realistic simulations for the traffic with those heterogeneous behaviors in unstructured road networks and has nearly the same efficiency as that of existing methods.

     

Mental load and risk in traffic behaviour

Abstract

Car driving means accomplishing a variety of continuously varying driving subtasks which constitute workload on the driver. Total workload can be analysed by type; for instance, the amount of information to be processed while driving, or the effort of car control. One of the driver's main tasks is to cope with the hazards with which he can be confronted on each particular route. This task places demands on his mental capacities. Therefore, coping with hazards is part of the total workload of car drivers. Based on this premise, the following topics are discussed in this paper.

(1)The mental-load approach in modelling traffic behaviour is described in some detail.

(2)Procedures and results of investigations into load factors in car driving are presented, emphasizing workload by reference to hazards. These include a job-analytic study of driving behaviour, a simulation study of hazard perception, and a field study of drivers' exposure to different road conditions.

(3)Hazards and risks must be perceived before making adequate decisions. Some aspects of hazard perception are therefore mentioned.

(4)To understand ‘risky decision making’ in car driving it is necessary to consider the opportunities drivers have to engage in risky situations. Those opportunities are discussed.

(5)To complement these discussions of traffic behaviour, certain issues of risk-taking behaviour in non-traffic situations are considered in order to assess whether knowledge from these areas can be applied to driving.     

An alternative approach for modelling and simulation of traffic data: artificial neural networks

It is assumed that there is a complicated relationship between the driver characteristics and involvement in traffic accidents. It is quite difficult to simulate the effects of these driver characteristics into the traffic accidents. The artificial neural networks (ANN) approach is proposed for training-predicting the database in this paper since it is a more flexible and assumption-free methodology. The networks are organised in different architectures and the results have been compared in order to determine the best fitting one. Finally, the best possible architecture is selected for a better representation of the survey data and the prediction of accident percentage. The predictions about the outputs for the inputs which are not used in the training of the ANN provide information about the drivers which cannot be reached in the database. The predictions are highly satisfactory and the ANNs have been found to be reliable processing systems for modelling and simulation in the traffic data assessments.     

Anticipating the content and circumstances of skill transfer: unrealistic expectations of driver training and graduated licensing?

There is substantial evidence that driving skills improve during driver training, but the long-term safety benefit of such formal training remains unproven. Restricting the exposure of newly licensed drivers to more hazardous driving circumstances, as in graduated driver licensing (GDL) regimes, demonstrably reduces crash risk, but drivers remain at risk after the restrictions are eased. GDL and most other licensing regimes advocate increased basic training and practice, but thereafter require neither advanced training nor systematic increase in exposure to risk. This assumes that basic skills acquired during formal training will transfer positively to new and more demanding traffic circumstances. This paper reviews the theoretical basis for these assumptions and offers a way of systematically identifying the extent of transfer desired. It is concluded that there is little theoretical or empirical foundation for the supposition that what is learned during or after training will have a safety benefit in later driving.     

基于车辆行驶数据的驾驶人行为谱分析方法

针对我国驾驶人行为谱的研究尚不完善，专业领域内没有相应的行为谱分析工具的问题，提出了一套针对营运客车的完整的驾驶人驾驶行为谱体系并设计了一套分析工具。首先，设计并定义了驾驶人行为谱的特征指标和评价指标；其次，给出了驾驶人行为谱的特征指标分析、计算方法，采用基于马尔可夫链蒙特卡洛采样和离群点剔除的K-means算法对驾驶人的驾驶风格进行分析，采用回归学习对驾驶人的驾驶技能进行分析；然后，设计了基于车联网、大数据的驾驶人行为谱的基础数据采集和预处理方法；最后，采用Java语言、Spring MVC架构开发出驾驶人行为谱分析工具。将机器学习中的数据挖掘、数据分析算法与交通安全领域相结合，对完善我国驾驶人行为谱框架体系具有理论意义，为我国驾驶人行为谱的研究提供了一个科学、定量化分析的工具，对交管部门规范驾驶人驾驶行为、提高道路安全指数、制定合理的交通安全管理策略具有指导意义。     

Insurance Classifications and Drivers' Galvanic Skin Response

Drivers' galvanic skin responses were recorded in town traffic and on country roads. Two groups of drivers were compared, those who would pay higher insurance premiums, by reason of their ago or occupation, and the rest. The high insurance group did not differ from the rest in the magnitude of the GSR. but when the ratio of the GSR in town traffic to that on a country road was considered there was a significant difference such that the high insurance group had a relatively greater GSR on the country road.

It is suggested that in town traffic most of the GSR arc generated by the actions of other drivers, whereas on the open road the GSRs are self generated by the subjects' driving. The GSR on the open road will therefore be more affected by the individual method of driving and by the risks the driver takes. The ratio of town GSR to country GSR can be used to eliminate the large unexplained differences between subjects and to expose the differences in driving behaviour     

Selective searching while driving: the role of experience in hazard detection and general surveillance

Novice drivers have been found in previous studies to display a limited search of the immediate environment, relative to experienced drivers, when manoeuvring on a dual-carriageway road. The present study investigated whether this reduction in the variance of search along the horizontal plane was a product of less frequent glancing in the car's mirrors. Novice and experienced drivers were observed as they made lane changes in relatively unobstructed conditions and when they needed to move into a lane already occupied by traffic. Novice drivers were found to rely more than experienced drivers upon their internal mirror, even when the lane-changing manoeuvre required information about traffic in the lane best reflected in the external, door-mounted mirror. Novices did increase their use of the external mirror in response to driving needs, suggesting that they did have an awareness of the situation that required inter-weaving with traffic in their destination lane. Their reliance upon the internal mirror may be a product of a habit acquired specifically for the driver licensing examination, in which exaggerated inspection of the internal mirror is regarded as being desirable.     

Research on the comprehensive traffic state evaluation model linked with drivers’ perception under the vehicle networking

Unified judgment standards and methods are often adopted to identify traffic state in certain road network based on traffic flow parameters. However, drivers often have different perceptions about the traffic state on different road sections, since their expectations on traffic state vary more or less from each other on different road sections. In particular, under the vehicle networking, out of considerations for safety and other relevant factors, requirements for the correlation and coordination of running vehicles have also raised significantly. Therefore, it is necessary to take driver’s perception about the driving conditions of certain road sections into consideration to adjust the release of traffic state. This paper has provided a comprehensive traffic state evaluation model linked with driver’s perception under the vehicle networking. The authors first establish an ANFIS model based on the T–S model and then conduct statistical analysis on drivers’ perceptions about certain traffic state. At last, the authors use the results of statistical analysis as regulatory factors to amend the parameters input through ANFIS. Through simulation, this paper has demonstrated that the model established has a high rate of convergence, a high identification precision and the generalization ability to conduct researches on the identification of traffic state.