Factors affecting lane change crashes

This study aims to investigate the contributing factors affecting the occurrence of crashes while lane-changing maneuvers of drivers. Two different data sets were used from the same drivers' population. The first data set was collected from the traffic police crash reports and the second data set was collected through a questionnaire survey that was conducted among 429 drivers. Two different logistic regression models were developed by employing the two sets of the collected data. The results of the crash occurrence model showed that the drivers' factors (gender, nationality and years of experience in driving), location and surrounding condition factors (non-junction locations, light and road surface conditions) and roads feature (road type, number of lanes and speed limit value) are the significant variables that affected the occurrence of lane-change crashes. About 57.2% of the survey responders committed that different sources of distractions were the main reason for their sudden or unsafe lane change including 21.2% was due to mobile usage. The drivers' behavior model results showed that drivers who did sudden lane change are more likely to be involved in traffic crashes with 2.53 times than others. The drivers who look towards the side mirrors and who look out the windows before lane-change intention have less probability to be involved in crashes by 4.61 and 3.85 times than others, respectively. Another interesting finding is that drivers who reported that they received enough training about safe lane change maneuvering during issuing the driving licenses are less likely to be involved in crashes by 2.06 times than other drivers.     

Assessing the effect of inattention-related error and anger in driving on road accidents among Iranian heavy vehicle drivers

Extensive studies have examined the effect of variables such as demographic characteristics, insomnia, and working conditions of drivers individually on inattention-related error as well as expression of anger in driving. Nevertheless, so far no study has tested the concurrent effect of these factors on crashes. This study has dealt with indirect investigation of the effect of variables including demographic characteristics, insomnia, and working conditions of drivers on inattention-related error and expression of anger in driving (as mediation model). Next, the effect of these two variables on the probability of incidence of road crashes has been assessed among truck drivers. For this purpose, 780 Iranian truck drivers were interviewed by validated questionnaires including insomnia severity index (ISI), attention related driving errors scale (ARDES), and driving anger expression (DAX). To confirm the validity of these questionnaires, confirmatory factor analysis (CFA) was used. Next, structural equation modeling (SEM) was employed for investigating the relationships between these latent variables and truck drivers' demographic characteristics, working conditions and their crash involvement. SEM results indicated that as the severity of insomnia among drivers increased, they committed more inattention-related errors, and also expressed more anger during driving. Generally, the results of this study indicated that with increase in the extent of experience and safety knowledge of drivers and improvement in their working conditions and their sleep status, it is possible to reduce inattention-related error and expression of anger during driving among heavy vehicle drivers.     

Validation of the Driver's Angry Thoughts Questionnaire (DATQ) in a sample of professional drivers in Iran

Aggressive driving has emerged as one of the most studied behaviors in the traffic safety field, due to its association with the odds of motor vehicle crashes and especially fatal crashes. Previous research has investigated the situations which provoke anger while driving, as well as the emotional (anger) and behavioral (aggression) aspects of aggressive driving. However, surprisingly the cognitive aspects of aggressive driving have largely been neglected. This study investigated the psychometric properties of the short-forms of the Driver's Angry Thoughts Questionnaire (DATQ) and the Driving Anger Expression Inventory (DAX) in a sample of professional drivers. Furthermore, the study aimed to investigate the mediation effects of aggressive thoughts, as the cognitive aspect of aggressive driving, on the relationship between traffic congestion and driving aggression. To this end, 613 public transport bus drivers completed the DATQ and DAX and were also asked to report the level of traffic congestion they normally faced in their daily driving, using six pictures. Confirmatory factor analysis (CFA) supported the four factor DAX and the five factor DATQ, which largely replicated the original factors. The four forms of maladaptive thoughts on the road were positively associated with aggressive driving, while the positive factor (coping self-instruction) was negatively associated with aggressive driving and traffic violations. Moreover, the results indicated that traffic congestion does not contribute directly to anger expression on the road, but rather through aggressive thoughts. This study suggests that cognitive interventions may help to eliminate aggressive driving and its adverse outcomes on traffic safety.     

Driver behavior formulation in intersection dilemma zones with phone use distraction via a logit-Bayesian network hybrid approach

Use of cellular phone while driving is one of the top contributing factors that induce traffic crashes, resulting in significant loss of life and property. A dilemma zone is a circumstance near signalized intersections where drivers hesitate when making decisions related to their driving behaviors. Therefore, the dilemma zone has been identified as an area with high crash potential. This article utilizes a logit-based Bayesian network (BN) hybrid approach to investigate drivers' decision patterns in a dilemma zone with phone use, based on experimental data from driving simulations from the National Advanced Driving Simulator (NADS). Using a logit regression model, five variables were found to be significant in predicting drivers' decisions in a dilemma zone with distractive phone tasks: older drivers (50–60 years old), yellow signal length, time to stop line, handheld phone tasks, and driver gender. The identified significant variables were then used to train a BN model to predict drivers' decisions at a dilemma zone and examine probabilistic impacts of these variables on drivers' decisions. The analysis results indicate that the trained BN model was effective in driver decision prediction and variable influence extraction. It was found that older drivers, a short yellow signal, a short time to stop line, nonhandheld phone tasks, and female drivers are factors that tend to result in drivers proceeding through intersections in a dilemma zone with phone use distraction. These research findings provide insight in understanding driver behavior patterns in a dilemma zone with distractive phone tasks.     

Age and road safety performance: Focusing on elderly and young drivers

The existing literature on young and elderly drivers indicates that they have the highest crash risks compared to other age groups of drivers. This study improves our understanding of the risk factors contributing to young and elderly drivers' elevated crash risk by examining self-report data from the E-Survey of Road User's Safety Attitudes (ESRA). The primary objective of this study is to compare the attitudes and behaviours of young, elderly, and middle-age drivers in Canada, the United States, and Europe. The main focus is on the practice of driving while distracted by mobile phones and driving while fatigued, as these are two dangerous behaviours that demonstrate the impact age may have. The analyses consistently showed that there are differences in the responses attributable to age. In all regions, drivers aged 18–21 years consistently reported higher rates of distracted and fatigued driving and higher rates of perceived social and personal acceptability of these behaviours than drivers aged 35–54 years. Elderly drivers aged 65+ years reported even lower rates of these behaviours and acceptability. Young drivers were also the least likely to believe that distraction and fatigue are frequent causes of road crashes, while elderly drivers were the most likely to believe this. This pattern with respect to age repeats in the support for policy measures as well; young drivers are least likely to support zero tolerance policies for mobile phone use when driving, while elderly drivers are the most likely to support this measure. Multivariate logistic regression modeling confirmed that elderly drivers were the least likely to engage in the use of mobile phones while driving or driving while fatigued. Statistically significant results showed that the middle-age group was less likely than young drivers to read a text message/email or check social media while driving and driving while fatigued.     

Investigating fatal and injury crash patterns of teen drivers with unsupervised learning algorithms

Teenagers have been emphasized as a critical driver population class because of their overrepresentation in fatal and injury crashes. The conventional parametric approaches rest on few predefined assumptions, which might not always be valid considering the complicated nature of teen drivers' crash characteristics that are reflected by multidimensional crash datasets. Also, individual attributes may be more speculative when combined with other factors. This research employed joint correspondence analysis (JCA) and association rule mining (ARM) to investigate the fatal and injury crash patterns of at-fault teen drivers (aged 15 to 19 years) in Louisiana. The unsupervised learning algorithms can explore meaningful associations among crash categories without restricting the nature of variables. The analyses discover intriguing associations to understand the potential causes and effects of crashes. For example, alcohol impairment results in fatal crashes with passengers, daytimes severe collisions occur to unrestrained drivers who have exceeded the posted speed limits, and adverse weather conditions are associated with moderate injury crashes. The findings also reveal how the behavior patterns connected with teen driver crashes, such as distracted driving in the morning hours, alcohol intoxication or using cellphone in pickup trucks, and so on. The research results can lead to effectively targeted teen driver education programs to mitigate risky driving maneuvers. Also, prioritizing crash attributes of key interconnections can help to develop practical safety countermeasures. Strategy that covers multiple interventions could be more effective in curtailing teenagers' crash risk.     

Car drivers' road safety performance: A benchmark across 32 countries

The road safety performance of a country and the success of policy measures can be measured and monitored in different ways. In addition to the traditional road safety indicators based on the number of fatalities or injured people in road traffic crashes, complementary road safety performance indicators can be used in relation to vehicles, infrastructure, or road users' behaviour. The last-mentioned can be based on data from roadside surveys or from questionnaire surveys. However, results of such surveys are seldom comparable across countries due to differences in aims, scope, or methodology.This paper is based on the second edition of the E-Survey of Road Users' Attitudes (ESRA), an online survey carried out in 2018, and includes data from more than 35,000 road users across 32 countries. The objective is to present the main results of the ESRA survey regarding the four most important risky driving behaviours in traffic: driving under the influence (alcohol/drugs), speeding, mobile phone use while driving, and fatigued driving. The paper explores several aspects related to these behaviours as car driver, such as the self-declared behaviours, acceptability and risk perception, support for policy measures, and opinions on traffic rules and penalties.Results show that despite the high perception of risk and low acceptability of all the risky driving behaviours analysed, there is still a high percentage of car drivers who engage in risky behaviours in traffic in all the regions analysed. Speeding and the use of a mobile phone while driving were the most frequent self-declared behaviours. On the other hand, driving under the influence of alcohol or drugs was the least declared behaviour. Most respondents support policy measures to restrict risky behaviour in traffic and believe that traffic rules are not being checked regularly enough, and should be stricter.The ESRA survey proved to be a valuable source of information to understand the causes underlying road traffic crashes. It offers a unique database and provides policy makers and researchers with valuable insights into public perception of road safety.     

Evaluation of risk factors for road accidents under mixed traffic: Case study on Indian highways

This paper presents an evaluation of risk factors for highway crashes under mixed traffic conditions. The basis of selecting study sites was abutting land use, roadway, and traffic characteristics. Accordingly, the study selected thirteen segments on the existing highway network in the state of West Bengal of India, covering a wide spectrum of such road attributes. A systematic investigation based on site-specific accident data to capture the highway sections' safety features revealed that the crash rate has steadily increased for years with traffic regardless of roadway category and conditions. A number of risk factors that affect road accidents were identified; they are mid-block access, pavement and shoulder conditions, vehicle involvement, time of day, and road configuration, i.e., two and multi-lane. The empirical observation indicates that the crash rate is relatively lower on multi-lane highways; however, the severity of any crash on such a road is relatively high. Notably, the crash frequencies on such roads are less during daylight hours due to the lane-based unidirectional traffic movement. This is quite the opposite during nighttime when drivers exhibit an inability to meet traffic contingencies, thereby increasing crash risk. The majority of crashes on two-lane highways are, on the other hand, due to unsafe driving manoeuvers. The study also observed that frequent mid-block accesses and poor shoulder conditions reduce scopes to rectify driving errors and increase crash risk as a consequence. The paper subsequently suggests proactive approaches to identify safety deficits at the time of planning and designing.     

Factors influencing crash involvement during early years of owning a new vehicle

Though automobile manufacturers are investing efforts to make newer vehicles safer to drive, an element of uncertainty with the new vehicle seems to persist with the drivers during the early years of ownership. This could be due to a lack of familiarity of the vehicle's power, dimensions or available technologies/features. While the uncertainty in itself is a potential cause of a crash, it is important for the policy-makers, practitioners, and automobile manufacturers to understand the factors that could further aggravate the problem. This research focuses on identifying the factors influencing the likelihood of getting involved in a crash and its severity when driving a new vehicle. Crash data for North Carolina for the years 2013 to 2018 (six years) was used develop partial proportionality odds models, compute the odds ratios, analyze the effects of explanatory variables, and identify factors influencing crashes by the age of the vehicle. The likelihood of getting involved in a severe or moderate injury crash when driving a new vehicle is less for drivers in the age group ≤19 years. Erratic driving behavior (like making wide turns, weaving and swerving in traffic, driving with headlights off, driving on center-line or lane-line, etc.) and speeding increase the risk of getting involved in a moderate injury crash when driving a new vehicle. Likewise, the odds of getting involved in a crash are high on weekends and in adverse weather conditions when driving a new vehicle. They are higher when driving a new motorcycle, heavy vehicle or farm machinery. The findings help policy-makers and practitioners formulate strategies to educate drivers on factors influencing crash risk when driving a new vehicle. Further, automobile manufacturers can establish guidance programs and documentation that explain what to expect when buying and driving a new vehicle.     

公交车驾驶人组织认同感和工作倦怠对不良驾驶行为的影响

公共交通是城市道路交通运输系统中的重要组成部分，公交车驾驶人存在的不良驾驶行为已经成为影响交通安全的最大制约因素之一，由其引发的道路交通事故给个人和社会都造成了严重损失，探索更为安全的公共交通环境显得极为重要。以公交车驾驶人为对象，探究影响公交车驾驶人驾驶行为特征的个人心理因素和组织环境因素，及其对不良驾驶行为的内在影响机制。选用工作倦怠量表（MBI-GS）、组织认同感问卷（OIQ）及驾驶行为问卷（DBQ）对844名城市公交车驾驶人展开问卷调查研究，并使用回归分析和中介检验来探究工作倦怠和组织认同感对驾驶行为的影响机制。结果表明：①32.8%的公交车驾驶人存在不良驾驶行为，错误驾驶行为显著高于违法驾驶行为。其中，在违法维度中，侵略性违法显著高于普通违法。②公交车驾驶人存在较高的组织认同感，组织认同感对不良驾驶行为具有显著的负向预测作用，对工作倦怠程度具有显著的负向预测作用；工作倦怠程度对不良驾驶行为具有显著的正向预测作用。③公交车驾驶人的工作倦怠水平在组织认同感对不良驾驶行为的影响中起到部分中介作用。该结果厘清了公交车驾驶人的工作倦怠和组织认同感对不良驾驶行为的影响机制，为进一步探究不良驾驶行为的心理干预方法提供了思路，从而达到改善城市道路公共交通安全环境的目标。     

Traffic safety culture of drivers in Canada: Implications for new traffic law implementation to enhance traffic safety

This study investigates Canada's traffic safety culture (TSC) as part of a global research project. The TSC survey data collected by an online survey is used to predict drivers' perception of changes in traffic problems in the past 3 years, driver's support, opposition towards enforcement of additional traffic laws, and drivers' perceived threat towards risky driving behaviors. A two-step procedure is followed to build models. The first step includes feature selection using the chi-square test of independence. The second step comprises building classification models using the Random Forest technique. Results suggest that drivers' personal attributes like the number of accident records, driving frequency, geographic region of nationality, and religion are top predictor variables for drivers' perception towards changes in traffic problems. In addition, compared to others most drivers perceive distracted driving as a major traffic problem today. There is strong disapproval of drivers against the following driving behaviors and strong support to implement laws against it: speeding in school zones, talking on a hand-held cell phone, tying text messages or e-mails, drowsy driving, driving without wearing their seatbelt, drive with passengers not wearing seatbelts, running through red lights, and impaired driving. In contrast, following risky driving behaviors is less of a perceived threat: speeding over limit on a freeway, on a residential street, and in an urban area and talking on a hands-free cell phone while driving. In addition, a driver's accident record is a significant indicator for a perceived threat towards risky driving behaviors followed by age and accumulated demerit points. The results from this study can be used to guide educational campaigns to transform the traffic safety culture of target groups and make more informed policy decisions.     

Predicting downgrade crash frequency with the random-parameters negative binomial model: Insights into the impacts of geometric variables on downgrade crashes in Wyoming

Road deaths, injuries and property damage place a huge burden on the economy of most nations. Wyoming has a high crash rate on mountain passes. The crash rates observed in the state is as a result of many factors mainly related to the challenging mountainous terrain in the state, which places extra burden on drivers in terms of requiring higher levels of alertness and driving skill. This study was conducted to investigate factors leading to crashes on Wyoming downgrades, with a focus on geometric variables. Traditionally, crash frequency analysis is conducted using count models such as Poisson or negative binomial models. However, factors that affect crash frequency are known to vary across observations. The use of a methodology that fails to take into account heterogeneity in observed and unobserved effects relating to roadway characteristics can lead to biased and inconsistent estimates. Inferences made from such parameter estimates may be misleading. This study employed the random-parameters negative binomial regression models to evaluate the impact of geometric variables on crash frequency. Five separate models were estimated for total, fatal/injury, property damage only (PDO), truck, and non-truck crash frequencies. Several geometric and traffic variables were found to influence the frequency of crashes on downgrades. These included segment length, vertical grade, shoulder width, lane width, presence of downgrade warning sign, vertical curve length, presence of a passing lane, percentage of trucks, number of lanes and AADT. The results suggest that segment length, lane width, presence of a passing lane, presence of a downgrade warning sign, vertical grade, and percentage of trucks are best modeled as random parameters. The findings of this study will provide transportation agencies with a better understanding of the impact of geometric variables on downgrade crashes.     

Self- and peer-assessments of ambulance drivers' driving performance

The aim of the present study was to develop and examine the quality of the Ambulance Driver Self-assessment Questionnaire (ADSQ) and the Ambulance Driver Peer-assessment Questionnaire (ADPQ) measuring aspects of, driving performance, driving style and driving competence. In addition the ADSQ measures self-reflection and safety-attitudes. The aim of the study was also to examine ambulance drivers' self- and peer-assessments as well as to examine the accuracy of self-assessments by comparing self-assessed and peer-assessed driving performance, driving style and competence. 76 ambulance drivers employed at two ambulance stations in northern Sweden completed ADSQ and ADPQ. Item analyses were conducted to examine the psychometric properties of the items, and based on the results some revisions were made to improve the questionnaires. The revised questionnaires were functioning rather well, although some subscale demonstrated low internal consistency. Subscale inter-correlations provided support for construct validity. Self- and peer-assessments indicated safe driving performance and good driver competence, which is positive from a traffic safety perspective. A comparison of mean self- and peer-assessment ratings, controlling for age, gender and driving experience showed no significant differences, except for the subscale overtaking. This indicates that ambulance drivers' self-assessments are realistic in most areas.     

Comparative study between Korea and UK: relationship between driving style and real-world fuel consumption

It is known that differences in driving styles have a significant impact on fuel efficiency and driving styles are affected by various factors such as driver characteristics, street environment, traffic situation, vehicle performance, and weather conditions. However, existing knowledge about the relationship between driving style and fuel consumption is limited. Thus, the aim of this study was to analyze the relationship beteen driving style and fuel consumption. The analysis presented in this paper used data from three on-road experiments were conducted independently in two different countries, i.e. South Korea and the United Kingdom. In this study, 91 participants, consisting 44 UK drivers and 47 Korean drivers, were asked to drive approximately 28 km of UK road and 21 km of Korean road, respectively. Driving data, including real-time fuel consumption, vehicle speed, and acceleration pedal usage were collected. The results suggested that driving styles including average vehicle speed and average throttle position were highly correlated with the real-world fuel consumption, and the cultural factors, e.g. road environment, traffic design, and driver’s characteristics affected the driving styles and, consequently, fuel efficiency.     

Drivers' perceptions regarding speeding and driving on urban residential streets with a 30 km/h speed limit

Previous studies have shown very little information regarding drivers' opinions, attitudes and behaviours with respect to speeding and driving on urban residential streets with a 30 km/h speed limit. The present research aims to address this issue by conducting a questionnaire study with a sample of 367 Japanese drivers. The results showed that drivers tended to have positive beliefs about complying with the 30 km/h speed limit and understand the negative consequences of speeding; however, a majority of the drivers considered breaking the speed limit as a way to reduce their travel time. While the extent of speeding was found to be very serious, a number of drivers still supported the use of a 30 km/h speed limit on residential streets and favoured protecting the right of vulnerable street users. The logistic regression models developed in this study identified that the drivers who did not support the 30 km/h speed limit were associated with those who had committed traffic-law violations, who had negative beliefs about complying with the speed limit, who did not consider residents' opinions, who believed it is acceptable for them to drive at a high speed, and who felt it difficult to refrain from speeding. With regard to anti-speeding countermeasures, under drivers' point of view, streets should be designed to make the 30 km/h speed limit more credible, although this study also showed evidence supporting the application of public awareness programmes and social campaigns as speeding interventions. In addition, this research investigated drivers' speed choices in various specific driving circumstances, and six underlying factors affecting drivers' speed choices were determined. On the basic of the findings, the implications and suggestions for speeding interventions were also discussed.     

Can't drive,I'm drunk – Exploring factors influencing the intention to drink and drive among Indian drivers

The crash risk of drivers increases significantly while driving under the influence of alcohol. However, the drivers' intention to drink and drive has not been explored yet in the context of a developing country like India. The present study applied an extended version of the theory of planned behaviour (TPB) to investigate the psychosocial predictors of drunk driving intentions of Indian drivers. 252 drivers participated in a self-reported survey designed for the study. Apart from the standard TPB components (attitudes, subjective norms, and perceived behavioural control), the survey also captured the extension measures such as risk perceptions, moral norms, traffic fatalism, sensation-seeking, conformity tendency, past engagement in drunk driving, crash history and driver demographics. The standard TPB model was successful in explaining 68.6% of the variance in the intention to drink and drive. The attitudes displayed the strongest influence on the intention (β = 0.696, p < 0.001), followed by perceived behavioural control (β = 0.180, p < 0.001); whereas subjective norms showed a moderate significance in influencing the intention (β = 0.062, p < 0.1). Among the extension variables, past behaviour showed the strongest influence on the intention to drink and drive (β = 0.123, p < 0.05), followed by sensation-seeking (β = 0.080, p < 0.05) and traffic fatalism (β = 0.072, p < 0.1). The extended TPB model explained 72% of the variance in the intention to drink and drive. The study findings can assist in the development of strategies/interventions to reduce drunk driving incidences.An earlier version of the paper was presented at the TRB 101st Annual Meeting, Washington, D. C., 2022.     

Development of an errorable car-following driver model

An errorable car-following driver model is presented in this paper. An errorable driver model is one that emulates human driver’s functions and can generate both nominal (error-free), as well as devious (with error) behaviours. This model was developed for evaluation and design of active safety systems. The car-following data used for developing and validating the model were obtained from a large-scale naturalistic driving database. The stochastic car-following behaviour was first analysed and modelled as a random process. Three error-inducing behaviours were then introduced. First, human perceptual limitation was studied and implemented. Distraction due to non-driving tasks was then identified based on the statistical analysis of the driving data. Finally, time delay of human drivers was estimated through a recursive least-square identification process. By including these three error-inducing behaviours, rear-end collisions with the lead vehicle could occur. The simulated crash rate was found to be similar but somewhat higher than that reported in traffic statistics.     

Modeling lane-change-related crashes with lane-specific real-time traffic and weather data

This study investigates the relationship between lane-change-related crashes and lane-specific, real-time traffic factors. It is anticipated that the real-time traffic data for the two lanes—the vehicle's lane (subject lane) and the lane to which that a vehicle intends to change (target lane)—are more closely related to lane-change-related crashes, as opposed to congregated traffic data for all lanes. Lane-change-related crash data were obtained from a 62-mile long freeway in Southeast Wisconsin in 2012 and 2013. One-minute traffic data from the 5- to 10-minute interval prior to the crashes were extracted from an immediately upstream detector station and two immediately downstream stations from the crash location. Weather information was collected from a major historical weather database. A matched case-control logistic regression was used for analysis. Results show that the following factors significantly affect the probability of a lane-change-related crash: average flow into the target lane at the first downstream station, the flow ratio at the second downstream station, and snow conditions. Additionally, the average speed in the target lane at the first downstream station contributes to the occurrence of lane-change crashes during snowy conditions. According to the model, the probability of a lane-change-related crash under real-time traffic conditions can aid in flagging potential crash-prone conditions. The identified contributing factors can help traffic operators select traffic control and management countermeasures to proactively mitigate lane-change-related crashes.     

驾驶风格对驾驶行为的影响

为了揭示驾驶风格对驾驶行为的影响规律,进而提取表征驾驶风格的特征参数,对不同风格驾驶人在感知层和操作层的驾驶行为数据进行了量化分析。首先,基于驾驶行为问卷对18名中国非职业驾驶人进行了驾驶风格问卷调查,并采用主成分分析、K-均值聚类等方法将被试驾驶人分为谨慎型、正常型和激进型3种类型。接着,被试驾驶人在搭载了SmartEye眼动仪的驾驶模拟器上开展了高速公路行车环境下的驾驶试验,同步采集了感知层的视觉特性参数和操作层的驾驶绩效参数,并采用判断抽样的方式将驾驶样本按照驾驶风格和驾驶模式（换道意图和车道保持）进行了划分,共选取了810组有效样本。最后,采用方差分析法分析了不同风格驾驶人在不同驾驶模式下的注视行为、扫视行为、横向控制特性、纵向控制特性方面相关参数的差异显著性,并提取了不同风格间存在显著差异的参数作为表征驾驶风格的特征参数。研究结果表明：驾驶风格越激进,驾驶人对周围环境关注越少,对车辆的横向控制稳定性越差,急加速和急减速行为发生的频次越高;不同风格驾驶人在意图时窗内对后视镜的注视次数（p=0.002）、方向盘转角熵值（p=0.04）、加速踏板开度（p=0.01）、制动踏板开度（p=0.02）这4个参数的差异均较为显著,因此可作为表征驾驶风格的特征参数。