Are older drivers’ driving patterns during an on-road driving task representative of their real-world driving patterns?

Abstract

Objective: The current study investigated whether older drivers’ driving patterns during a customized on-road driving task were representative of their real-world driving patterns.

Methods: Two hundred and eight participants (male: 68.80%; mean age?=?81.52 years, SD?=?3.37 years, range?=?76.00–96.00 years) completed a customized on-road driving task that commenced from their home and was conducted in their own vehicle. Participants’ real-world driving patterns for the preceding 4-month period were also collected via an in-car recording device (ICRD) that was installed in each participant’s vehicle.

Results: During the 4-month period prior to completing the on-road driving task, participants’ median real-world driving trip distance was 2.66?km (interquartile range [IQR]?=?1.14–5.79?km) and their median on-road driving task trip distance was 4.41?km (IQR?=?2.83–6.35?km). Most participants’ on-road driving task trip distances were classified as representative of their real-world driving trip distances (95.2%, n?=?198).

Conclusions: These findings suggest that most older drivers were able to devise a driving route that was representative of their real-world driving trip distance. Future research will examine whether additional aspects of the on-road driving task (e.g., average speed, proportion of trips in different speed zones) are representative of participants’ real-world driving patterns.     

Comparative judgements of crash risk and driving ability for speeding behaviours

Introduction: Preliminary research has indicated that numerous drivers perceive their risk of traffic crash to be less than other drivers, while perceiving their driving ability to be better. This phenomenon is referred to as ‘comparative optimism’ (CO) and may prove to inhibit the safe adoption of driving behaviors and/or dilute perceptions of negative outcomes. The objective of this study was to investigate comparative judgments regarding crash risk and driving ability, and how these judgments relate to self-reported speeding. Method: There were 760 Queensland motorists comprised of 51.6% males and 48.2% females, aged 16–85 (M = 39.60). Participants completed either a paper or online version of a survey. Judgments of crash risk and driving ability were compared to two referents: the average same-age, same-sex driver, and the average same-age, same-sex V8 supercar champion. Results: Drivers displayed greater optimism when comparing their crash risk and driving ability to the average same-age, same- sex driver (respectively, 72%, 72.4%), than when comparing to a V8 supercar champion (respectively, 60%, 32.9%). When comparing judgements of crash risk and driving ability to a similar driver, it appears that participants in the present study are just about as optimistic about their risk of crash (i.e. 72%) as they are optimistic about their driving ability (i.e. 74.2%).     

Measures of speeding from a GPS-based travel behavior survey

Objective: Lacking information about actual driving speed on most roads in the Minneapolis–St. Paul region, we determine car speeds using observations from a Global Positioning System (GPS)-based travel survey. Speed of travel determines the likelihood and consequences of collisions. We identify the road segments where speeding occurs. This article then analyzes the relationship between link length, traveler characteristics, and speeding using GPS data collected from 152 individuals over a 7-day period as part of the Minneapolis–St. Paul Travel Behavior Inventory.

Methods: To investigate the relationship, we employed an algorithm and process to accurately match the GPS data with geographic information system (GIS) databases. Comparing actual travel speed from GPS data with posted speed limits, we measure where and when speeding occurs and by whom. We posit that link length and demographics shape the decision to speed.

Results: Speeding is widespread under both high speed limits (e.g., 60?mph [97?km/h]) and low speed limits (less than 25?mph [40?km/h]); in contrast, speeding is less common at 30–35?mph (48–56?km/h). The results suggest that driving patterns depend on the road type. We also find that when there are many intersections, the average link speed (and speeding) drops. Long links are conducive to speeding. Younger drivers and more educated drivers also speed more, and speeding occurs more often in the evening.

Conclusions: Road design and link length (or its converse, frequency of intersections) affect the likelihood of speeding. Use of increasingly available GPS data allows more systematic empirical analysis of designs and topologies that are conducive to road safety.     

Modeling the contribution of speeding and impaired driving to insurance claim counts and costs when contributing factors are unknown

PROBLEM: There are no specific indicators for distinguishing insurance claims related to speeding and impaired driving in the information warehouse at the Insurance Corporation of British Columbia. Contributing factors are only recorded for that part of the claim data that is also reported by the police. Most published statistics on crashes that are related to alcohol or speeding are based on police-reported data, but this represents only a fraction of all incidents. METHOD: This paper proposes surrogate models to estimate the counts and the average costs associated with speeding and impaired driving to insurance claims when contributing factors are unknown. Using police-reported data, classification rules and logistic regression models are developed to form such estimates. One approach applies classification rules to categorize insurance claims into those related to speeding, impaired driving, and other factors. The counts and the costs of insurance claims for each of these strata and overall are then estimated. A second method models the probability that an insurance claim is related to speeding or impaired driving using logistic regression and uses this to estimate the overall counts and the average costs of the claims. The two methods are compared and evaluated using simulation studies. RESULTS: The logistic regression model was found to be superior to the classification model for predicting insurance claim counts by category, but less efficient at predicting average claim costs. IMPACT: Having estimates of counts and costs of insurance claims related to impaired driving or speeding for all reported crash events provides a more accurate basis for policy-makers to plan changes and benefits of road safety programs.     

Taxi driver speeding: Who,when, where and how? A comparative study between Shanghai and New York City

Objective: The 3 objectives of this study are to (1) identify the driving style characteristics of taxi drivers in Shanghai and New York City (NYC) using taxi Global Positioning System (GPS) data and make a comparative analysis; (2) explore the influence of different driving style characteristics on the frequency of speeding (who and how?) and (3) explore the influence of driving style characteristics, road attributes, and environmental factors on the speeding rate (when, where, and how?)

Methods: This study proposes a driver–road–environment identification (DREI) method to investigate the determinant factors of taxi speeding violations. Driving style characteristics, together with road and environment variables, were obtained based on the GPS data and auxiliary spatiotemporal data in Shanghai and NYC.

Results: The daily working hours of taxi drivers in Shanghai (18.6 h) was far more than in NYC (8.5 h). The average occupancy speed of taxi drivers in Shanghai (21.3 km/h) was similar to that of NYC (20.3 km/h). Speeders in both cities had shorter working hours and longer daily driving distance than other taxi drivers, though their daily income was similar. Speeding drivers routinely took long-distance trips (>10 km) and preferred relatively faster routes. Length of segments (1.0–1.5 km) and good traffic condition were associated with high speeding rates, whereas central business district area and secondary road were associated with low speeding rates. Moreover, many speeding violations were identified between 4:00 a.m. and 7:00 a.m. in both Shanghai and NYC and the worst period was between 5:00 a.m. and 6:00 a.m. in both cities.

Conclusions: Characteristics of drivers, road attributes, and environment variables should be considered together when studying driver speeding behavior. Findings of this study may assist in stipulating relevant laws and regulations such as stricter offense monitoring in the early morning, long segment supervision, shift rule regulation, and working hour restriction to mitigate the risk of potential crashes.     

Changes in driving performance after first and second eye cataract surgery: A driving simulator study

Introduction: This study investigated the separate impact of first eye and second eye cataract surgery on driving performance, as measured on a driving simulator. Method: Forty-four older drivers with bilateral cataract aged 55+ years, awaiting first eye cataract surgery participated in a prospective cohort study. They completed a questionnaire, visual tests and a driving simulator assessment at three time points: before first eye, after first eye, and after second eye cataract surgery. Generalized Estimating Equation Poisson or linear regression models were undertaken to examine the change in four driving outcomes of interest after adjusting for cataract surgery and other potential confounders. Results: The rate of crashes/near crashes decreased significantly by 36% (incidence rate ratio (IRR) 0.64, 95% CI 0.47–0.88, p = 0.01) after first eye surgery and 47% (IRR 0.53, 95% CI 0.35–0.78, p < 0.001) after second eye surgery, compared to before first eye cataract surgery, after accounting for confounders. The rate of crashes/near crashes also decreased with better contrast sensitivity (IRR 0.69, 95% CI 0.48–0.90, p = 0.041). A separate model found that time spent speeding 10 kilometers per hour or more over the limit after second eye surgery was significantly less (0.14 min, p = 0.002), compared to before first eye surgery, after accounting for confounders. As contrast sensitivity improved, the duration of speeding also decreased significantly by 0.46 min (p = 0.038). There were no statistically significant changes in lane excursions or speed variation. Practical applications: The findings highlight the importance of timely first and second eye cataract surgery to ensure driver safety, especially as older drivers wait for second eye cataract surgery. It also provides further evidence that contrast sensitivity is probably a better predictor of driving ability in older drivers with cataract than visual acuity, the measure on which driver licensing requirements are currently based, and should also be used when assessing fitness to drive.     

Effects of in-vehicle monitoring on the driving behavior of teenagers

Objectives

The objective was to determine if teenage driving behavior improves when a monitoring and feedback device is installed in the teen's vehicle.

Methods

Vehicles of 85 teenage drivers were fit with a device that detected all instances of sudden braking/acceleration, speeding, and nonuse of seat belts. Drivers were assigned randomly to one of four research groups, differing in whether or not an alert sounded in the vehicle and whether or not parents were given access to websites containing notification records. Time trends in event rates per mile traveled were compared using Poisson regression.

Results

Seat belt use improved when violations were reported to the parent websites, and improved even more when in-vehicle alerts were activated. Consistent reductions in speeding were achieved only when teenagers received alerts about their speeding behavior, believed their speeding behavior would not be reported to parents if corrected, and when parents were being notified of such behavior by report cards.

Conclusions

Electronic monitoring of teenage drivers can reduce the incidence of risky behavior, especially seat belt nonuse. More complicated behavior is more difficult to change, however.

Impact on Industry

Parent participation is key to successful behavioral modification, but it is yet to be determined how best to encourage such participation.     

To speed or not to speed: Thematic analysis of American driving narratives

IntroductionSpeeding is a major cause of unintentional roadway death in the United States. Existing data show that U.S. drivers tend to speed less as they age, but reasons for this change remain largely unknown. Limited research has examined why U.S. drivers decide to speed or why U.S. drivers decide not to speed, and none to date has determined why speeding behaviors change over the life course. Research into these issues can provide insight that may be harnessed for more effective anti-speeding interventions that catalyze decisions not to speed. Methods: The current study asked a national sample of U.S. drivers (N = 309) about their driving behaviors and how they have changed over time using an open-ended prompt in an online survey. The authors qualitatively coded responses using a narrative analysis lens to identify common themes. Results: Results show U.S. drivers often make deliberate choices to speed and some do not consider speeding to be dangerous after achieving perceived mastery of driving skills. Participants tended to report speeding less over time, citing increased concern for family and other roadway users, which may help explain national speeding data trends. Several other themes emerged identifying individual cognitive factors, environmental contexts, and key persons impacting speeding decisions. Practical Applications: Findings show that the most effective means of encouraging U.S. drivers to decide not to speed may be multi-pronged intervention approaches highlighting how speeding reduces roadway driver control, connecting speeding with safety, and encompassing road design and law enforcement strategies.     

城市间运输货车行驶工况构建与应用

为研究城市间运输货车行驶工况特性与典型工况构建方法。运用车载数据采集系统采集了在珠三角区域城市间运输的货运车辆行驶车速等瞬态数据。基于13个工况特征参数解析工况特性,运用运动学片段理论将工况速度数据分成284个工况片,基于主成分分析和聚类分析法将工况片分成5类,选出12片代表工况片,按工况片平均速度从小到大的顺序排列,再将工况时长等比例压缩至1 800 s后最终构建出典型行驶工况。构建工况与实测样本的各项特征参数符合度大于80%,结果表明提出的典型工况构建方法可行,构建工况符合城市间货运车辆实际运行特性。构建工况的最大车速为80 km/h,主要分布在60~80 km/h,C-WTVC工况在0~90 km/h较均匀分布,平均车速为41.0 km/h,较构建工况低15.8%。基于构建工况进行重型货车排放性能仿真测算,得出CO_(2e)排放因子为764.81 g/km,较C-WTVC工况测算值低10.97%,表明运行工况不同导致碳排放测算值有较大差异。     

Near crash characteristics among risky drivers using the SHRP2 naturalistic driving study

Problem: Previous research have focused extensively on crashes, however near crashes provide additional data on driver errors leading to critical events as well as evasive maneuvers employed to avoid crashes. The Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study contains extensive data on real world driving and offers a reliable methodology to study near crashes. The current study utilized the SHRP2 database to compare the rate and characteristics associated with near crashes among risky drivers. Methods: A subset from the SHRP2 database consisting of 4,818 near crashes for teen (16–19 yrs), young adult (20–24 yrs), adult (35–54 yrs), and older (70+ yrs) drivers was used. Near crashes were classified into seven incident types: rear-end, road departure, intersection, head-on, side-swipe, pedestrian/cyclist, and animal. Near crash rates, incident type, secondary tasks, and evasive maneuvers were compared across age groups. For rear-end near crashes, near crash severity, max deceleration, and time-to-collision at braking were compared across age. Results: Near crash rates significantly decreased with increasing age (p < 0.05). Young drivers exhibited greater rear-end (p < 0.05) and road departure (p < 0.05) near crashes compared to adult and older drivers. Intersection near crashes were the most common incident type among older drivers. Evasive maneuver type did not significantly vary across age groups. Near crashes exhibited a longer time-to-collision at braking (p < 0.01) compared to crashes. Summary: These data demonstrate increased total near crash rates among young drivers relative to adult and older drivers. Prevalence of specific near crash types also differed across age groups. Timely execution of evasive maneuvers was a distinguishing factor between crashes or near crashes. Practical Applications: These data can be used to develop more targeted driver training programs and help OEMs optimize ADAS to address the most common errors exhibited by risky drivers.     

Evaluation of an in-vehicle monitoring system (IVMS) to reduce risky driving behaviors in commercial drivers: Comparison of in-cab warning lights and supervisory coaching with videos of driving behavior

ProblemRoadway incidents are the leading cause of work-related death in the United States.MethodsThe objective of this research was to evaluate whether two types of feedback from a commercially available in-vehicle monitoring system (IVMS) would reduce the incidence of risky driving behaviors in drivers from two companies. IVMS were installed in 315 vehicles representing the industries of local truck transportation and oil and gas support operations, and data were collected over an approximate two-year period in intervention and control groups. In one period, intervention group drivers were given feedback from in-cab warning lights from an IVMS that indicated occurrence of harsh vehicle maneuvers. In another period, intervention group drivers viewed video recordings of their risky driving behaviors with supervisors, and were coached by supervisors on safe driving practices.ResultsRisky driving behaviors declined significantly more during the period with coaching plus instant feedback with lights in comparison to the period with lights-only feedback (ORadj = 0.61 95% CI 0.43–0.86; Holm-adjusted p = 0.035) and the control group (ORadj = 0.52 95% CI 0.33–0.82; Holm-adjusted p = 0.032). Lights-only feedback was not found to be significantly different than the control group's decline from baseline (ORadj = 0.86 95% CI 0.51–1.43; Holm-adjusted p > 0.05).ConclusionsThe largest decline in the rate of risky driving behaviors occurred when feedback included both supervisory coaching and lights.Practical applicationsSupervisory coaching is an effective form of feedback to improve driving habits in the workplace. The potential advantages and limitations of this IVMS-based intervention program are discussed.     

Adolescents' perspectives on distracted driving legislation

Purpose: Distracted driving is a growing global epidemic, with adolescent drivers reporting frequent engagement in distracted driving behaviors. Public health initiatives and legislative efforts designed to decrease the prevalence of these unwanted driving behaviors have demonstrated small, but significant reductions in crash risk. Non-compliance is a known problem among drivers of all ages, but may be especially problematic for novice, adolescent drivers. Using a construct from the Health Belief Model, the relations between demographic factors, perceived threat to safety, and peer influences were investigated with adolescents' support for three types of distracted driving legislation regarding: (a) reading or sending text messages/emails while driving; (b) hand-held cell phone use while driving; and (c) using non-driving-related-in-vehicle (NDIV) technology while driving. Investigating adolescents' perceptions provides an opportunity to understand distracted driving enforcement and legislation. Methods: Three hundred and seventy-nine adolescents aged 15–19 (M = 16.12, SD = 0.56) were recruited from public high schools. Demographics, perceptions, and support regarding distracted driving were assessed using self-report surveys. Statistical analyses included bivariate correlations and adjusted odds ratios to investigate influences of adolescent support for distracted driving legislation. Results:Female adolescents were at 2 times greater odds of supporting a law against texting/emailing while driving compared to male adolescents. Greater perceived threat to safety was associated with all three types of distracted driving legislation (aOR = 1.10, 1.33). Minimal association was found with peer influences. Conclusions: Perceived threat to safety and gender were associated with legislative support in adolescents. Practical application: Interventions and public health campaigns that incorporate elements related to perceived threat may be more successful with female adolescent drivers than male adolescents. Future experimental research will help to determine what factors affect adolescents' perspectives on distracted driving to promote compliance with related legislation.     

Introducing a multi-variate classification method: Risky driving acceptance among different heterogeneous driver sub-cultures

Introduction: Heterogeneous driving populations with many different origins are likely to have various sub-cultures that comprise of drivers with shared driver characteristics, most likely with dissimilar traffic safety cultures. An innovative methodology in traffic safety research is introduced which is beneficial for large datasets with multiple variables, making it useful for the multi-variate classification of drivers, driving attitudes and/or (risky) driving behaviours. Method: With the application of multidimensional scaling analysis (MDS), this study explores traffic safety culture in the State of Qatar using a questionnaire and investigates the similarity patterns between the questionnaire items, aiming to classify attitudes towards risky driving behaviours into themes. MDS is subsequently applied to classify drivers within a heterogeneous driving sample into sub-cultures with shared driver characteristics and different risky driving attitudes. Results: Results show that acceptance of speeding is highest among the young Arabic students and acceptance of distraction and drivers’ negligence such as phone use and not wearing a seatbelt is highest among male Arab drivers. Acceptance of extreme risk-taking like intoxicated driving and red-light running is highest among South-Asian business drivers. Conclusion: It is important and practical to understand risky behavioural habits among sub-cultures and thereby focussing on groups of drivers instead of individuals, because groups are easier to approach and drivers within sub-cultures are found to influence each other. By indicating which groups of drivers are most likely to perform specific risky driving themes, it is possible to target these groups and effectively emphasise certain subsets of risky driving behaviours during training or traffic safety education. Practical Applications: This study provides guidance for the improvement of driver education and targeted traffic safety awareness campaigns, intending to make changes to attitudes and habits within specific driver sub-cultures with the aim to improve traffic safety on the longer term.     

Using SHRP2 naturalistic driving data to examine driver speeding behavior

Problem: Speeding-related crashes continue to be a serious problem in the United States. According to the National Highway Traffic Safety Administration, 26% of all fatal crashes in 2017 had speeding as a contributing factor. Method: Vehicle speed data recorded during the Strategic Highway Research Program 2 (SHRP 2) Naturalistic Driving Study were analyzed to identify the frequency of speeding episodes. Up to 100 trips were sampled from 2,910 individual drivers aged 16–64. Vehicle speed data from individual trips were parsed into continuous speeding episodes (SEs) and Free-Flow Episodes (FFEs), which approximated opportunities to speed. Results & Discussion: Driving 10 mph above the posted speed limit (PSL) was common, and 99.8% of drivers had at least one occurrence SE within their trip sample, yielding an average of 2.75 SEs per trip (623,202 SEs in total). The analysis focused on a subset of higher-speed SEs in which the vehicle reached speeds of at least 15 mph above the PSL during the SE (71,113 SEs in total). Average maximum speeds for most higher-speed SEs ranged between 12 mph to 15 mph above the PSL, and most also lasted less than 2 min. Most drivers spent less than 5% of the FFE time speeding, and only a small number of drivers spent more than 10% of the time speeding. There was also a clear trend towards the younger group having higher overall percentages of SE time relative to FFE time. Practical Applications: The methods and measures developed in this study provide the foundation for future analyses to determine if there are different types of speeding that vary in terms of risky characteristics, and further, if certain drivers are more likely to engage in riskier speeding behavior. Identifying higher-risk speeders is an important step for developing countermeasures and strategies targeting drivers that are at greatest risk of speed-related crashes.     

Covariability in three dimensions of teenage driving risk behavior: impaired driving,risky and unsafe driving behavior,and secondary task engagement

Objective: This research examined the extent to which teenagers who engaged in one form of risky driving also engaged in other forms and whether risky driving measures were reciprocally associated over time.

Methods: The data were from waves 1, 2, and 3 (W1, W2, and W3) of the NEXT Generation study, with longitudinal assessment of a nationally representative sample starting with 10th graders starting in 2009–2010. Three measures of risky driving were assessed in autoregressive and cross-lagged analyses: driving while alcohol/drug impaired (DWI), Checkpoints Risky Driving Scale (risky and unsafe driving), and secondary task engagement while driving.

Results: In adjusted autoregression models, the risk variables demonstrated high levels of stability, with significant associations observed across the 3 waves. However, associations between variables were inconsistent. DWI at W2 was associated with risky and unsafe driving at W3 (β = 0.21, P < .01); risky and unsafe driving at W1 was associated with DWI at W2 (β = 0.20, P < .01); and risky and unsafe driving at W2 is associated with secondary task engagement at W3 (β = 0.19, P < .01). Over time, associations between DWI and secondary task engagement were not significant.

Conclusions: Our findings provide modest evidence for the covariability of risky driving, with prospective associations between the Risky Driving Scale and the other measures and reciprocal associations between all 3 variables at some time points. Secondary task engagement, however, appears largely to be an independent measure of risky driving. The findings suggest the importance of implementing interventions that addresses each of these driving risks.     

Prevalence and trends of distracted driving in Canada

Introduction: This study evaluates prevalence and trends in distracted driving in Canada based on multiple indicators collected from the Road Safety Monitor (RSM) and Canada’s National Fatality Database maintained by the Traffic Injury Research Foundation (TIRF). Method: Data from the RSM on self-reported distracted driving behaviors were analyzed using multivariate techniques including logistic regression analysis in various years spanning from 2004 to 2019. Data from TIRF’s National Fatality Database from 2000 to 2016 were also analyzed using piecewise regression analysis to evaluate trends and prevalence of driver distraction. Results: Significantly more Canadians reported talking on their phone hands-free or handheld phone while driving in 2019 compared to 2010. There was a 102% increase in the percentage that reported texting while driving in 2019 (9.7%) compared to 2010 (4.8%). For every 10-year increase in age, drivers were 44% less likely to text, 38% less likely to use a handheld phone, and 28% less likely to use a hands-free phone. Males were 62% more likely to use a handheld phone and 50% more likely to use a hands-free phone than females. Findings related to drivers’ perceived danger of distracted driving and attitudes are also presented. Although the number of distraction-related fatalities has not increased substantially from 2000 to 2016, the percentage of all fatalities where distraction was a contributing factor has increased. Unlike drinking drivers, distracted drivers more often kill other road users in crashes than kill themselves. Conclusions: In conclusion, while most Canadians appear to understand that one of the high-risk forms of distracted driving (i.e., texting while driving) is indeed dangerous, there is a minority who are unaware of, or resistant to, this fact. Practical Applications: Enforcement activities and education initiatives to combat distracted driving ought to be tailored to the target audience based on the patterns uncovered.     

Identifying compensatory driving behavior among older adults using the situational avoidance questionnaire

IntroductionDriving self-regulation is considered a means through which older drivers can compensate for perceived declines in driving skill or more general feelings of discomfort on the road. One form of driving self-regulation is situational avoidance, the purposeful avoidance of situations perceived as challenging or potentially hazardous. This study aimed to validate the Situational Avoidance Questionnaire (SAQ, Davis, Conlon, Ownsworth, & Morrissey, 2016) and identify the point on the scale at which drivers practicing compensatory avoidance behavior could be distinguished from those whose driving is unrestricted, or who are avoiding situations for other, non-compensatory reasons (e.g., time or convenience).MethodSeventy-nine Australian drivers (M_age = 71.48, SD = 7.16, range: 55 to 86 years) completed the SAQ and were classified as a compensatory-restricted or a non-restricted driver based on a semi-structured interview designed to assess the motivations underlying avoidance behavior reported on the SAQ.ResultsUsing receiver-operator characteristic (ROC) analysis, the SAQ was found to have high diagnostic accuracy (sensitivity: 85%, specificity: 82%) in correctly classifying the driver groups. Group comparisons confirmed that compensatory-restricted drivers were self-regulating their driving behavior to reduce the perceived demands of the driving task. This group had, on average, slower hazard perception reaction times, and reported greater difficulty with driving, more discomfort when driving due to difficulty with hazard perception skills, and greater changes in cognition over the past five years.ConclusionsThe SAQ is a psychometrically sound measure of situational avoidance for drivers in baby boomer and older adult generations.Practical applicationsUse of validated measures of driving self-regulation that distinguish between compensatory and non-compensatory behavior, such as the SAQ, will advance our understanding of the driving self-regulation construct and its potential safety benefits for older road users.     

考虑驾驶员反应时间的车辆碰撞预警模型

为了保证车辆在行驶过程中的安全性,提出了一种考虑驾驶员反应时间的车辆碰撞预警模型,改进了传统模型中驾驶员反应时间定值化的缺点。首先,依据车辆的制动过程分析了驾驶员反应时间对制动距离的影响。其次,设计驾驶员反应时间的模糊推理算法,选取驾龄、疲劳强度和应变能力3个主要因素作为评价指标来计算反应时间。最后,采用分等级的预警策略建立考虑驾驶员反应时间的碰撞预警模型,并通过Carsim-Matlab/Simulink联合仿真与传统模型进行对比分析。结果表明,设计的预警模型可以对不同类型的驾驶员进行差异化碰撞预警,在30 km/h和80 km/h两种车速下实际停车距离与理论值的最大误差为8%。     

Examination of personality traits and social problem-solving skills of individuals whose driving licenses have been confiscated due to drunk driving

Objective: Drunk driving is one of the major behavioral issues connected with problematic alcohol consumption. The objective of this study was to evaluate the relationship between personality traits and social problem-solving skills of individuals who drive while intoxicated.

Method: One hundred forty-four individuals apprehended twice while driving drunk and sent to a driver behavior training program (9 females and 135 males) participated in our study. The Eysenck Personality Questionnaire Revised–Abbreviated (EPQ-RA) composed of 4 subscales (Extroversion, Neuroticism, Psychoticism, and Lying) and the Social Problem Solving Inventory (SPSI) composed of 7 subscales (Cognitive, Emotion, Behavior, Problem Definition and Formulation, Creating Solution Options, Solution Implementation and Verification, and Decision Making) were used to evaluate the participants.

Results: A positive relationship was found between the Extroversion subscale of the EPQ-RA and the Cognition subscale (P <.01), Emotion subscale (P <.01), Behavior subscale (P <.01), Generation of Alternatives subscale (P <.01), Decision Making subscale (P <.05), and Solution Implementation and Verification subscale (P <.01). For individuals who repeated intoxicated driving, all subscales of the EPQ-RA (Extroversion, Lying, Neuroticism, and Psychoticism subscales) explained 12% of the scores of the Cognition subscale and 16.2% (P <.001) of the Emotion subscale of the SPSI. There was no significant relationship between the first and second incident alcohol blood levels (P >.05).

Conclusion: Drinking and driving behaviors appear to be negative or maladaptive behaviors closely related to personality traits and may represent an effort to avoid negative emotions. Evaluation of negative emotions may have an important place in training programs intended to change drunk driving behavior.     

Crash risk perception of sleepy driving and its comparisons with drink driving and speeding: Which behavior is perceived as the riskiest?

Objective: Driver sleepiness is a major crash risk factor but may be underrecognized as a risky driving behavior. Sleepy driving is usually rated as less of a road safety issue than more well-known risky driving behaviors, such as drink driving and speeding. The objective of this study was to compare perception of crash risk of sleepy driving, drink driving, and speeding.

Methods: Three hundred Australian drivers completed a questionnaire that assessed crash risk perceptions for sleepy driving, drink driving, and speeding. Additionally, the participants' perceptions of crash risk were assessed for 5 different contextual scenarios that included different levels of sleepiness (low, high), driving duration (short, long), and time of day/circadian influences (afternoon, nighttime) of driving.

Results: The analysis confirmed that sleepy driving was considered a risky driving behavior but not as risky as high levels of speeding (P < .05). Yet, the risk of crashing at 4 a.m. was considered as equally risky as low levels of speeding (10 km over the limit). The comparisons of the contextual scenarios revealed driving scenarios that would arguably be perceived as quite risky because time of day/circadian influences were not reported as high risk.

Conclusions: The results suggest a lack of awareness or appreciation of circadian rhythm functioning, particularly the descending phase of circadian rhythm that promotes increased sleepiness in the afternoon and during the early hours of the morning. Yet, the results suggested an appreciation of the danger associated with long-distance driving and driver sleepiness. Further efforts are required to improve the community's awareness of the impairing effects from sleepiness and, in particular, knowledge regarding the human circadian rhythm and the increased sleep propensity during the circadian nadir.