The validity of a low-cost simulator for the assessment of the effects of in-vehicle information systems

This study explored the validity of using a low-cost simulator for the assessment of driver distraction arising from the use of an in-vehicle information system. Eighteen participants drove on a rural road whilst carrying out distractor tasks of various levels of difficulty, in both a low-cost simulator (with gaming console steering wheel and pedals with single monitor display) and a medium-cost one (fixed-base, complete vehicle cab, wrap-around visuals). The distractor tasks were presented at identical locations in each of the drives and an identical suite of driver performance and subjective rating measures were elicited to allow a robust comparison between the two simulator environments. As expected, there was a reduction in mean speed when drivers were completing the distraction tasks and this effect was observed in both simulators. However, drivers spent more time at shorter headways in the low-cost version and demonstrated more erratic steering behaviour in the low-cost version. This could be due to a reduced peripheral view and inferior kinaesthetic feedback through the driver controls, but low-cost simulators could play a significant role in the early stages of design and evaluation of in-vehicle information systems.     

Understanding driver distractions in fatal crashes: An exploratory empirical analysis

Introduction: Driver distraction has become a significant problem in transportation safety. As more portable wireless devices and driver assistance and entertainment systems become available to drivers, the sources of distraction are increasing. Method: Based on the results of different studies in the literature review, this paper categorizes different distraction enablers into six subcategories according to their fundamental characteristics and how they would affect a driver's likelihood of engaging in non-driving related activities. The review also discusses the characteristics and influence of external and internal distractions. The objective of this study is to examine the effect of different distraction sources in fatal crashes with the consideration of a driver's age and sex. Tukey test, chi-square test of independence, Nemenyi post-hoc test, and Marascuilo procedure have been used to investigate the top distraction sources, the trend of distraction-affected fatal crashes, the effect of different distractions on drives in different age groups, and their influence on female and male drivers. Results: It was found that inner cognitive inferences accounted for the greatest proportion of driver engagement in distractions. Young drivers show a larger probability of being distracted by in-vehicle technology-related devices/objects. Within the group of young drivers, female drivers showed a higher probability than their male counterparts of engaging in distracted driving caused by in-vehicle technology-related devices. Among six subcategories of distractions, drivers older than 80 years old were found to be most likely affected by inner cognitive interferences.     

Evaluation of driver performance with a prototype cyber physical mid-block crossing advanced warning system

Introduction: Using connected vehicle technologies, pedestrian to vehicle (P2V) communication applications can be installed on smart devices allowing pedestrians to communicate with drivers by broadcasting discrete safety messages, received by drivers in-vehicle, as an alternative to expensive fixed-location physical safety infrastructure. Method: This study consists of designing, developing, and deploying an entirely cyber-physical P2V communication system within the cellular vehicle to everything (C-V2X) environment at a mid-block crosswalk to analyze drivers’ reactions to in-vehicle advanced warning messages, the impacts of the advanced warning messages on driver awareness, and drivers’ acceptance of this technology. Results: In testing human subjects with, and without, advanced warning messages upon approaching a mid-block crosswalk, driver reaction, acceptance, speed, eye tracking data, and demographic data were collected. Through an odds ratio comparison, it was found that drivers were at least 2.44 times more likely to stop for the pedestrian with the warning than without during the day, and at least 1.79 times more likely during the night. Furthermore, through binary logistic regression analysis, it was found that driver age, time of the day, and the presence of the advanced warning message all had strong, significant impacts with a confidence value of at least 98% (p < 0.02) on the rate at which drivers stopped for the pedestrian. Conclusions: The results from this study indicate that the advanced warning message sent within the C-V2X had a strong, positive impact on driver behavior and understanding of pedestrian intent. Practical Applications: Pedestrian crashes and fatality rates at mid-block crossings continue to increase over the years. Connected vehicle technology utilizing smart devices can be used as a means for communications between pedestrians and drivers to deliver safety messages. State and local city planners should consider geofencing designated mid-block crossings at which this technology operates to increase pedestrian safety and driver awareness.     

Effect prediction of time-gaps for adaptive cruise control (ACC) and in-vehicle tasks on bus driver performance

Researchers have devoted a great deal of attention to the effects of driver assist systems on driver performance. This article describes a modeling approach to simulate the effects of time-gaps for adaptive cruise control (ACC) and manual in-vehicle tasks on bus-driver performance. A concept model was built with the knowledge of modularization, parameterization, and parallel processing. By running the model, the predictions for the effects of five levels of time-gaps and two types of in-vehicle tasks were collected in three measures: (1) mean gap, (2) minimum gap, and (3) collision rate. The model performed well in prediction, especially when driving with in-vehicle tasks. Predictions from the model were validated by the experiment with a verified fixed-base bus-driving simulator, used in the authors’ previous studies. Throughout the modeling approach, this research provides a theoretical and accurate way to assess effects of time-gaps and vehicle-equipped interfaces. In follow-up research, the authors will apply this approach to evaluate other driving assist systems (e.g. collision warning systems and navigation systems) to create a customized software kit.     

A critical overview of driver recording tools

Introduction: Technological advancements during recent decades have led to the development of a wide array of tools and methods in order to record driving behavior and measure various aspects of driving performance. The aim of the present study is to present and comparatively assess the various driver recording tools that researchers have at their disposal. Method: In order to achieve this aim, a multitude of published studies from the international literature have been examined based on the driver recording methodologies that have been implemented. An examination of more traditional survey methods (questionnaires, police reports, and direct observer methods) is initially conducted, followed by investigating issues pertinent to the use of driving simulators. Afterwards, an extensive section is provided for naturalistic driving data tools, including the utilization of on-board diagnostics (OBD) and in-vehicle data recorders (IVDRs). Lastly, in-depth incident analysis and the exploitation of smartphone data are discussed. Results: A critical synthesis of the results is conducted, providing the advantages and disadvantages of utilizing each tool and including additional knowledge regarding ease of experimental implementation, data handling issues, impacts on subsequent analyses, as well as the respective cost parameters. Conclusions: New technologies provide undeniably powerful tools that allow for seamless data handling, storage, and analysis, such as smartphones and in-vehicle data recorders. However, this sometimes comes at considerable costs (which may or may not pay off at a later stage), while legacy driver recording methods still have their own niches to fill in research. Practical Applications: The present research supports researchers when designing driver behavior monitoring studies. The present work enables better scheduling and pacing of research activities, but can also provide insights for the distribution of research funds.     

Age of licensure and monitoring teenagers' driving: survey of parents of novice teenage drivers

OBJECTIVE: To assess parental decision making regarding the timing of teenagers initiating driving and monitoring teenagers' driving after licensure. METHODS: About 300 parents were interviewed during spring 2006 in Minnesota, North Carolina, and Rhode Island, states with varying licensing provisions, while teenagers took their first on-road driving tests. RESULTS: States' differences in ages of obtaining learner's permits and licenses reflected different licensing laws, but most teenagers obtained permits and took road tests within the first few months after they became eligible. Common reasons for delaying obtaining permits were fulfilling driver education requirements and lack of readiness/immaturity. Insufficient practice driving most often delayed licensure. Among the parents interviewed, 33-49% believed the minimum licensure age should be 17 or older. Almost all parents planned to supervise teenagers' driving after licensure, and most wanted to know about speeding or distractions. When asked about in-vehicle devices to monitor teenagers' driving, 37-59% of parents had heard of them. Parents were least interested in using video cameras and about equally interested in computer chips and cell-phone-based GPS systems. Disinterest in monitoring devices most often was attributed to trusting teenagers or respecting their privacy. CONCLUSIONS: Licensing laws influence ages of initiating driving. Although many parents support licensing at 17 or older - higher than in all but one state - most teenagers initiate driving soon after reaching the minimum age. Parents plan to supervise teenagers' driving, and many say they are open to using in-vehicle monitoring devices. IMPACT ON INDUSTRY: Many parents support a minimum licensing age of 17 or older and would consider in-vehicle devices to extend their supervision of teenager's driving.     

Use of manual speed alerting and cruise control devices by car drivers

A number of in-vehicle technologies have been developed that have significant potential to reduce the incidence and severity of speed-related crashes. Two of the most widely implemented of these are conventional cruise control and manual speed alerting devices. However, almost nothing is known about the extent to which drivers use these devices and whether they are effective in helping drivers reduce speeding. This study assessed the use, acceptability and effectiveness in reducing speeding of manual speed alerting and cruise control devices to a sample of drivers from the Australian state of New South Wales. Four focus groups were conducted; two in Sydney (metropolitan) and two in Wagga Wagga (rural), involving 31 drivers aged 25–49 years, who were either users or non-users of the devices. The participants held positive attitudes towards manual speed alerting and cruise control systems and felt that these devices are generally effective in helping them to control and maintain their speed. However, the rural participants use cruise control more regularly than metropolitan participants, while the metropolitan participants reported that they use their speed alerting system more than rural participants. Preliminary recommendations deriving from the research are made.     

Using event-triggered naturalistic data to examine the prevalence of teen driver distractions in rear-end crashes

IntroductionWhile teen driver distraction is cited as a leading cause of crashes, especially rear-end crashes, little information is available regarding its true prevalence. The majority of distraction studies rely on data derived from police reports, which provide limited information regarding driver distraction.MethodThis study examined over 400 teen driver rear-end crashes captured by in-vehicle event recorders. A secondary data analysis was conducted, paying specific attention to driver behaviors, eyes-off-road time, and response times to lead-vehicle braking.ResultsAmong teens in moderate to severe rear-end crashes, over 75% of drivers were observed engaging in a potentially distracting behavior. The most frequently seen driver behaviors were cell phone use, attending to a location outside the vehicle, and attending to passengers. Drivers using a cell phone had a significantly longer response time than drivers not engaged in any behaviors, while those attending to passengers did not. Additionally, in about 50% of the rear-end crashes where the driver was operating/looking at a phone (e.g., texting), the driver showed no driver response (i.e., braking or steering input) before impact, compared to 10% of crashes where the driver was attending to a passenger.ConclusionsThe high frequency of attending to passengers and use of a cell phone leading up to a crash, compounded with the associated risks, underlines the importance of continued investigation in these areas.Practical applicationsParents and teens must be educated regarding the frequency of and the potential effects of distractions. Additional enforcement may be necessary if Graduated Driver Licensing (GDL) programs are to be effective. Systems that alert distracted teens could also be especially helpful in reducing rear-end collisions.     

Associations of distraction involvement and age with driver injury severities

IntroductionThis paper investigates the associations between the severity of injuries sustained by a driver who is involved in a two-vehicle crash, the existence and type of driver distraction as well as driver's age. Few studies investigated distraction as it relates to injury severity. Moreover, these studies did not consider driver age which is a significant factor related to driving behavior and the ability to respond in a crash situation.MethodsAn ordered logit model was built to predict injury severity sustained by drivers using data from the U.S. National Automotive Sampling System's General Estimates System (2003 to 2008). Various factors (e.g., weather, gender, and speeding) were statistically controlled for, but the main focus was on the interaction of driver age and distraction type.ResultsThe trends observed for young and mid-age drivers were similar. For these age groups, dialing or texting on the cell phone, passengers, and in-vehicle sources resulted in an increase in a likelihood of more severe injuries. Talking on the cell phone had a similar effect for younger drivers but was not significant for mid-age drivers. Inattention and distractions outside the vehicle decreased the odds of severe injuries. For older drivers, the highest odds of severe injuries were observed with dialing or texting on a cell phone, followed by in-vehicle sources and talking on the cell phone. All these sources were associated with an increased likelihood of injury severity. Similar to young and mid-age drivers, distractions outside the vehicle decreased the odds of severe injuries. Other distraction types did not have a significant effect for the older age group.ConclusionsThe results support previous literature and extend our understanding of crash injury severity.Practical applicationsThe findings have implications for policy making and the design of distraction mitigation systems.     

Human factors and safety in the design of intelligent vehicle-highway systems (IVHS)

Intelligent Vehicle-Highway Systems (IVHS) have been proposed in the wake of rapid worldwide growth in traffic volume and density. These systems involve the application of advanced sensor, communications, computational, and control technologies to the design of highways and vehicles to improve traffic flow and safety. Similar technologies have been applied in other transportation systems such as aviation and air-traffic control, and it is suggested that the human factors insights derived from these systems can be usefully applied, proactively rather than retroactively, in IVHS design. Several safety and human factors issues relevant to the design of IVHS technologies, both near-term and long-term, are discussed, including: (a) the optimization of driver mental workload in highly-automated “hybrid” systems; (b) the design of in-vehicle navigation aids and the resolution of display conflicts; (c) individual and group differences in driver behavior and their implications for training and licensure; (d) the evolution and integration of IVHS technologies; and (e) traffic management and the regulation of driver trust in IVHS. Successful resolution of these issues and their incorporation in IVHS design will provide for fully functional systems that will serve the twin needs of reducing traffic congestion and improving highway safety.     

Post-trip safety interventions: State-of-the-art,challenges, and practical implications

Introduction: Currently, risky driving behaviour is a major contributor to road crashes and as a result, wide array of tools have been developed in order to record and improve driving behaviour. Within that group of tools, interventions have been indicated to significantly enhance driving behaviour and road safety. This study critically reviews monitoring technologies that provide post-trip interventions, such as retrospective visual feedback, gamification, rewards or penalties, in order to inform an appropriate driver mentoring strategy delivered after each trip. Method: The work presented here is part of the European Commission H2020 i-DREAMS project. The reviewed platform characteristics were obtained through commercially available solutions as well as a comprehensive literature search in popular scientific databases, such as Scopus and Google Scholar. Focus was given on state-of-the-art-technologies for post-trip interventions utilized in four different transport modes (i.e. car, truck, bus and rail) associated with risk prevention and mitigation. Results: The synthesized results revealed that smartphone applications and web-based platforms are the most accepted, frequently and easiest to use tools in cars, buses and trucks across all papers considered, while limited evidence of post-trip interventions in -rail was found. The majority of smartphone applications detected mobile phone use and harsh events and provided individual performance scores, while in-vehicle systems provided delayed visual reports through a web-based platform. Conclusions: Gamification and appropriate rewards appeared to be effective solutions, as it was found that they keep drivers motivated in improving their driving skills, but it was clear that these cannot be performed in isolation and a combination with other strategies (i.e. driver coaching and support) might be beneficial. Nevertheless, as there is no holistic and cross-modal post-trip intervention solution developed in real-world environments, challenges associated with post-trip feedback provision and suggestions on practical implementation are also provided.     

Determining the risk of driver-at-fault events associated with common distraction types using naturalistic driving data

Introduction: Studies thus far have focused on automobile accidents that involve driver distraction. However, it is hard to discern whether distraction played a role if fault designation is missing because an accident could be caused by an unexpected external event over which the driver has no control. This study seeks to determine the effect of distraction in driver-at-fault events. Method: Two generalized linear mixed models, one with at-fault safety critical events (SCE) and the other with all-cause SCEs as the outcomes, were developed to compare the odds associated with common distraction types using data from the SHRP2 naturalistic driving study. Results: Adjusting for environment and driver variation, 6 of 10 common distraction types significantly increased the risk of at-fault SCEs by 20-1330%. The three most hazardous sources of distraction were handling in-cabin objects (OR = 14.3), mobile device use (OR = 2.4), and external distraction (OR = 1.8). Mobile device use and external distraction were also among the most commonly occurring distraction types (10.1% and 11.0%, respectively). Conclusions: Focusing on at-fault events improves our understanding of the role of distraction in potentially avoidable automobile accidents. The in-cabin distraction that requires eye-hand coordination presents the most danger to drivers’ ability in maintaining fault-free, safe driving. Practical Applications: The high risk of at-fault SCEs associated with in-cabin distraction should motivate the smart design of the interior and in-vehicle information system that requires less visual attention and manual effort.     

Crashes and near-crashes on horizontal curves along rural two-lane highways: Analysis of naturalistic driving data

IntroductionPrior research has shown the probability of a crash occurring on horizontal curves to be significantly higher than on similar tangent segments, and a disproportionally higher number of curve-related crashes occurred in rural areas. Challenges arise when analyzing the safety of horizontal curves due to imprecision in integrating information as to the temporal and spatial characteristics of each crash with specific curves.MethodsThe second Strategic Highway Research Program(SHRP 2) conducted a large-scale naturalistic driving study (NDS),which provides a unique opportunity to better understand the contributing factors leading to crash or near-crash events. This study utilizes high-resolution behavioral data from the NDS to identify factors associated with 108 safety critical events (i.e., crashes or near-crashes) on rural two-lane curves. A case-control approach is utilized wherein these events are compared to 216 normal, baseline-driving events. The variables examined in this study include driver demographic characteristics, details of the traffic environment and roadway geometry, as well as driver behaviors such as in-vehicle distractions.ResultsLogistic regression models are estimated to discern those factors affecting the likelihood of a driver being crash-involved. These factors include high-risk behaviors, such as speeding and visual distractions, as well as curve design elements and other roadway characteristics such as pavement surface conditions.ConclusionsThis paper successfully integrated driver behavior, vehicle characteristics, and roadway environments into the same model. Logistic regression model was found to be an effective way to investigate crash risks using naturalistic driving data.Practical ApplicationsThis paper revealed a number of contributing factors to crashes on rural two-lane curves, which has important implications in traffic safety policy and curve geometry design. This paper also discussed limitations and lessons learned from working with the SHRP 2 NDS data. It will benefit future researchers who work with similar type of data.     

Detecting fatigue in car drivers and aircraft pilots by using non-invasive measures: The value of differentiation of sleepiness and mental fatigue

Introduction: Fatigue is one of the most crucial factors that contribute to a decrease of the operating performance of aircraft pilots and car drivers and, as such, plays a dangerous role in transport safety. To reduce fatigue-related tragedies and to increase the quality of a healthy life, many studies have focused on exploring effective methods and psychophysiological indicators for detecting and monitoring fatigue. However, those fatigue indicators rose many discrepancies among simulator and field studies, due to the vague conceptualism of fatigue, per se, which hinders the development of fatigue monitoring devices. Method: This paper aims to give psychological insight of the existing non-invasive measures for driver and pilot fatigue by differentiating sleepiness and mental fatigue. Such a study helps to improve research results for a wide range of researchers whose interests lie in the development of in-vehicle fatigue detection devices. First, the nature of fatigue for drivers/pilots is elucidated regarding fatigue types and fatigue responses, which reshapes our understanding of the fatigue issue in the transport industry. Secondly, the widely used objective neurophysiological methods, including electroencephalography (EEG), electrooculography (EOG), and electrocardiography (ECG), physical movement-based methods, vehicle-based methods, fitness-for-duty test as well as subjective methods (self-rating scales) are introduced. On the one hand, considering the difference between mental fatigue and sleepiness effects, the links between the objective and subjective indicators and fatigue are thoroughly investigated and reviewed. On the other hand, to better determine fatigue occurrence, a new combination of measures is recommended, as a single measure is not sufficient to yield a convincing benchmark of fatigue. Finally, since video-based techniques of measuring eye metrics offer a promising and practical method for monitoring operator fatigue, the relationship between fatigue and these eye metrics, that include blink-based, pupil-based, and saccade-based features, are also discussed. To realize a pragmatic fatigue detector for operators in the future, this paper concludes with a discussion on the future directions in terms of methodology of conducting operator fatigue research and fatigue analysis by using eye-related parameters.     

Evaluating an intervention to improve belt fit for adult occupants

IntroductionPrevious laboratory studies have demonstrated that some drivers position their seat belts suboptimally. Specifically, the lap portion of the belt may be higher and farther forward relative to the pelvis than best practice, and the shoulder portion of the belt may be outboard or inboard of mid-shoulder. This study evaluated the performance of a video-based intervention for improving the belt fit obtained by drivers.MethodTwenty-nine adult drivers participated in this study. Belt fit was measured before and after the intervention in participants’ vehicles and in a laboratory mockup.ResultsData from both the in-vehicle and laboratory belt measures found that 95% of participants sampled improved some aspect of lap belt fit. For the in-vehicle test conditions, participants who lowered the lap belt location (Z) after the intervention showed an improvement of 26 mm on average. Among those participants who shifted the horizontal lap belt location rearward (closer to the pelvis), an average improvement of 36 mm was observed. No significant differences were observed between baseline and post-intervention shoulder belt fit.ConclusionsThe results provide preliminary evidence that an intervention improves driver belt fit. More research is needed to establish what aspects of this intervention affected behavior and how effective such an intervention is in the context of public health.Practical applicationsThese findings can help better inform intervention initiatives to improve occupant belt fit.     

Evaluation of a video-based measure of driver heart rate

IntroductionInternal driver events such as emotional arousal do not consistently elicit observable behaviors. However, heart rate (HR) offers promise as a surrogate measure for predicting these states in drivers. Imaging photoplethysmography (IPPG) can measure HR from face video recorded in static, indoor settings, but has yet to be examined in an in-vehicle driving environment.MethodsParticipants (N = 10) completed an on-road driving task whilst wearing a commercial, chest-strap style heart rate monitor (“baseline”). IPPG was applied to driver face video to estimate HR and the two measures of HR were compared.ResultsFor 4 of 10 participants, IPPG produced a valid HR signal (± 5 BPM of baseline) between 48 and 75% of trip duration. For the remaining participants, IPPG accuracy was poor (< 20%).ConclusionsIn-vehicle IPPG is achievable, but significant challenges remain.Practical applicationsThe relationship between IPPG accuracy and various confounding factors was quantified for future refinement.     

Comparison of self-report and objective measures of driving behavior and road safety: A systematic review

IntroductionThis research systematically reviewed the existing literature in regards to studies which have used both self-report and objective measures of driving behavior. The objective of the current review was to evaluate disparities or similarities between self-report and objective measures of driving behavior.MethodsSearches were undertaken in the following electronic databases, PsycINFO, PubMed, and Scopus, for peer-reviewed full-text articles that (1) focused on road safety, and (2) compared both subjective and objective measures of driving performance or driver safety. A total of 22,728 articles were identified, with 19 articles, comprising 20 studies, included as part of the review.ResultsThe research reported herein suggested that for some behaviors (e.g., driving in stressful situations) there were similarities between self-report and objective measures while for other behaviors (e.g., sleepiness and vigilance states) there were differences between these measurement techniques. In addition, findings from some studies suggested that in-vehicle devices may be a valid measurement tool to assess driving exposure in older drivers.ConclusionsFurther research is needed to examine the correspondence between self-report and objective measures of driving behavior. In particular, there is a need to increase the number of studies which compare “like with like” as it is difficult to draw comparisons when there are variations in measurement tools used.Practical applicationsIncorporating a range of objective and self-report measurements tools in research would help to ensure that the methods used offer the most reliable measures of assessing on-road behaviors.     

"The little squealer" or "the virtual guardian angel"? Young drivers' and their parents' perspective on using a driver monitoring technology and its implications for parent-young driver communication

Introduction

In-vehicle driving monitoring technologies have the potential to enable young drivers to learn from self-assessment. However, their use is largely dependent on parental involvement.

Method

A total of 79 interviews were conducted with young drivers and parents regarding this technology and its use. Most had the experience of having an in-vehicle data recorder installed in the vehicle driven by the young drivers. Parents and the young drivers expressed both appreciation as well as reservations about its potential as a means to enhance the driving safety of young drivers.

Results

A surprising finding was that some parents did not check the feedback and said they relied on the young driver to do so. Main concerns related to privacy, parent-young driver relationship, self-esteem and confidence, constructive use of the feedback data, and the limitations of the documentation that can be done by the technology.

Conclusions

Providing parents and young drivers with a support system and tools to discuss and utilize the feedback are underscored. Challenges include addressing the invasion of young drivers’ privacy and gender differences, and using the monitoring-capacity of the technology to enhance safe driving practices. Implications for programs to enhance communication and a dialogical approach between parents and young drivers are discussed.     

Distractions and the risk of car crash injury: the effect of drivers' age

PROBLEM: Motor-vehicle accidents are one of the major causes of injury in most motorized countries. Driver distractions have been suggested as a contributor to traffic accidents. Moreover, age of the driver seems to have a role in the relationship between distractions and car crashes. But very few studies have investigated the effect of driver's age on this relationship. This exploratory study investigated the association between distractions, both inside and outside the vehicle, and the increased risk of car crash injury among drivers across different ages. METHOD: This study used a case series design to analyze data routinely collected by the NSW police in Australia. A special focus of this study was on how drivers' age affects the risk of car crash injury, which was determined by using a well-documented risk estimation methodology. RESULTS: The results obtained indicated that drivers of all ages, on the whole, are more susceptible to distractions inside the vehicle than distractions coming from outside. Age was shown to affect the relationship between in-vehicle distraction and the risk of car crash injury. A separate analysis was also conducted on hand-held phone usage while driving with results supplementing previous findings reported in the literature. IMPACT TO INDUSTRY: Safety strategies to countermeasure in-vehicle distractions have been suggested and discussed.     

Examination of drivers' cell phone use behavior at intersections by using naturalistic driving data

IntroductionMany driving simulator studies have shown that cell phone use while driving greatly degraded driving performance. In terms of safety analysis, many factors including drivers, vehicles, and driving situations need to be considered. Controlled or simulated studies cannot always account for the full effects of these factors, especially situational factors such as road condition, traffic density, and weather and lighting conditions. Naturalistic driving by its nature provides a natural and realistic way to examine drivers' behaviors and associated factors for cell phone use while driving.MethodIn this study, driving speed while using a cell phone (conversation or visual/manual tasks) was compared to two baselines (baseline 1: normal driving condition, which only excludes driving while using a cell phone, baseline 2: driving-only condition, which excludes all types of secondary tasks) when traversing an intersection.ResultsThe outcomes showed that drivers drove slower when using a cell for both conversation and visual/manual (VM) tasks compared to baseline conditions. With regard to cell phone conversations, drivers were more likely to drive faster during the day time compared to night time driving and drive slower under moderate traffic compared to under sparse traffic situations. With regard to VM tasks, there was a significant interaction between traffic and cell phone use conditions. The maximum speed with VM tasks was significantly lower than that with baseline conditions under sparse traffic conditions. In contrast, the maximum speed with VM tasks was slightly higher than that with baseline driving under dense traffic situations.Practical applicationsThis suggests that drivers might self-regulate their behavior based on the driving situations and demand for secondary tasks, which could provide insights on driver distraction guidelines. With the rapid development of in-vehicle technology, the findings in this research could lead the improvement of human-machine interface (HMI) design as well.