Differences In Driving Behavior Research Articles

Cultural implications on driver behaviour and road safety: insights from Kano State, Nigeria

This study investigates the cultural implications of driver behaviour and its impact on road safety through the lens of Driver Behaviour Questionnaire (DBQ). The survey includes 741 drivers aged 18 and above from Kano State, Nigeria. Our analysis identifies a three-factor model: Violations, Errors, and Aggressive Violations. The study compares these findings with two others from different regions and state in Nigeria, revealing significant differences in driver behaviour, thereby highlighting the influence of cultural factors. Our analysis finds significant correlations between driver demographics and risky behaviours, with older drivers showing a higher risk of crashes. This indicates the importance of tailored road safety measures for different demographics. Efforts to curb risky behaviours encompass a multi-faceted approach. Improvements in road infrastructure, including lane expansion and pedestrian-friendly designs, foster safety while discouraging violations. Addressing factors like hawking and trading on roads is paramount to maintain driver focus. Furthermore, investment in comprehensive driver education, awareness campaigns, and advanced training programs is vital to reduce errors and aggressive driving behaviours. Recognising the cultural differences that influence driver behaviour in Nigeria is vital for creating a safer and more respectful traffic environment. Interventions tailored to specific cultural contexts are likely to be more effective than one-size-fits-all approaches. In conclusion, this study advocates for a holistic approach, integrating law enforcement, infrastructure enhancements, and driver education campaigns, to mitigate risky behaviours among drivers and enhance road safety.

Differences in Driver Behavior between Manual and Automatic Turning of an Inverted Pendulum Vehicle

Personal mobility vehicles (PMVs) are compact and lightweight compared to automobiles; hence, human dynamic behavior affects a vehicle's postural stability. In this study, the dynamic behaviors of drivers of inverted pendulum vehicles (IPV) under manual and automatic driving were investigated. One particular feature of applying automatic driving to IPV is constant posture stabilization control. In this study, the drivers' center of gravity (COG)/center of foot pressure position (COP) and joint moments during turning were investigated experimentally. It was found that the drivers' COG shifted backward during turning and deceleration. For COP, it was found that drivers maintained balance by moving their inner foot more inward and their outer foot more outward during turning. These results are significant for understanding the steps taken to withstand centrifugal forces during turning. The joint moments of the foot were more significant in automatic turning than in manual turning to prevent falling owing to centrifugal force. These findings can facilitate the development of an automatic control method that shifts the COG of a driver, as in manual turning.

A panel data-based discrete-continuous modelling framework to analyze longitudinal driver behavior in homogeneous and heterogeneous disordered traffic conditions

ABSTRACT We propose a panel data-based discrete-continuous modeling framework to analyze driver behavior in two disparatetrajectory datasets – one from a heterogeneous disorderly (HD) traffic streamin India and another from a homogeneous traffic stream in the United States. Thepanel data-based framework allows the analyst to isolate the subject vehicle-and driver-specific unobserved factors that influence driver behavior. Doing sohelps reduce the confounding effects of such unobserved factors on analyzingthe influence of observed factors, such as relative speeds and spacing betweenthe subject vehicle and other vehicles, on driver behavior. The empiricalresults reveal both similarities and differences in driver behavior between thetwo trajectory datasets. In addition, the analysis sheds light on the suitability of different lengthsof influence zones on driver behavior in the two datasets. The insights from this study can help improve driver behavior modelsand traffic simulation frameworks for both traffic conditions..

Driving under the influence of cannabis among recreational and medical cannabis users: A population study

BackgroundComparisons of individuals using cannabis for medical versus recreational purposes have identified differences in health status, alcohol and drug use, and perceived risk of drug use. All of these factors are associated with aggressive and impaired driving and collision risk. Yet, few studies comparing medical and recreational cannabis users have considered differences in driver behaviour and road safety. AimThis study examined the association between type of cannabis use (medical versus recreational-only) and engaging in driving under the influence of cannabis (DUIC), controlling for suspected confounding variables. MethodData were derived from a regionally stratified cross-sectional general population telephone survey of adults (18+ years) in Ontario, Canada conducted from 2014 to 2019. Respondents reporting past-year operation of a vehicle and past-year use of cannabis were selected (N = 1392). A binary logistic regression was conducted to assess the association between type of cannabis user (medical versus recreational-only) and self-reported DUIC, controlling for cannabis use frequency, hazardous drinking, perceived general and mental health, demographic characteristics, driving exposure, and interview year. ResultsIn total, 9.7 percent of recreational-only users reported DUIC compared to 27.0 percent of medical users. Adjusting for covariates, medical cannabis users had almost two times greater odds of DUIC than recreational-only users (AdjOR = 1.78, p = .037, 95%CI = 1.03, 3.05). DiscussionA higher proportion of medical cannabis users, relative to recreational-only users, engaged in DUIC. This finding has important implications for improving the effectiveness of public health interventions designed to reduce DUIC. Further research examining the harms of medical versus recreational cannabis use for road safety is needed.

Naturalistic driving study for Automated Driver Assistance Systems (ADAS) evaluation in the Chinese, Swedish and American markets.

In recent years, Automated Driver Assistance Systems (ADAS) have received great promotion and acceptance in the European market. However, transferring ADAS to other markets may affect driver behavior due to the cultural and contextual differences in various markets. Methods used for capturing these differences are based on subjective data collection. This study shows how vehicle data collected in the ND study helps to identify and investigate further the differences in driver behavior and the driving context in the Chinese, Swedish and US markets. This paper discusses a better way to consider the infrastructural and cultural differences in ADAS design.

Driver profiles based on values and traffic safety climate and their relationships with driver behaviors

Drivers have an important place in the traffic system when the human factor is taken into consideration. Drivers from different cultures are exposed to different values, norms, and traffic systems, and these differences may form various driver behaviors. Thus, traffic climate and individual values can impact driver behaviors. In this study, the relationships between Schwartz’s individual values and traffic climate dimensions were examined. Clusters were then created from the traffic climate dimensions and individual values, and the differences in driver behavior within these clusters were investigated. In order to examine similarities and differences between countries, the results from 5 countries (Estonia, Greece, Kosovo, Russia, and Turkey) are presented. Correlational analyses indicated that, while internal requirements and self-transcendence are positively related in all countries, external affective demands and conservation are positively related in Estonia, Kosovo, Russia, and Turkey. Additionally, external affective demands and self-transcendence are positively related in Greece, Kosovo, Russia, and Turkey. A three-cluster structure fitted the data well in all of the five countries. Within-country differences were observed in clusters of Russian and Turkish data in terms of driver behaviors. The detailed results are presented and discussed in relation to the literature.

Modeling of individual differences in driver behavior

Computational transportation is a scientific discipline which uses traffic flow simulation for intervention design and analysis. Realistic traffic flow simulation depends on realistic computational modeling of individual agents such as drivers. Whereas, realistic agent model relies on realistic modeling of microscopic driver behaviors. IDM and MOBIL are considered de-facto car-following and lane change models respectively. All the prominent microscopic models have been developed with engineering perspective i.e. to reproduce perfect driving behavior. Whereas human driving behavior exhibit individual difference and is prone to risks and errors. This study focuses on development of a personality-based model of driver behavior. The parameters that have been modeled to represent driving preferences have been identified. In their existing forms, model parameters could be assigned arbitrary values from a prescribed range to define different driver profiles. This way, theoretically, infinite driver profiles could be created, many of which does not exist in real. Whereas, literature of traffic psychology suggests that there are few prevalent classes of drivers which exhibit certain behavioral patterns. These classes are characterized with the help of human personality. In proposed study, a relationship between personality traits and model parameters have been modeled. This enhancement may reproduce individual differences in driving behaviors.

SU124DE NOVO VARIANTS IN CHILDHOOD-ONSET-PSYCHOSIS

Drivers have an important place in the traffic system when the human factor is taken into consideration. Drivers from different cultures are exposed to different values, norms, and traffic systems, and these differences may form various driver behaviors. Thus, traffic climate and individual values can impact driver behaviors. In this study, the relationships between Schwartz’s individual values and traffic climate dimensions were examined. Clusters were then created from the traffic climate dimensions and individual values, and the differences in driver behavior within these clusters were investigated. In order to examine similarities and differences between countries, the results from 5 countries (Estonia, Greece, Kosovo, Russia, and Turkey) are presented. Correlational analyses indicated that, while internal requirements and self-transcendence are positively related in all countries, external affective demands and conservation are positively related in Estonia, Kosovo, Russia, and Turkey. Additionally, external affective demands and self-transcendence are positively related in Greece, Kosovo, Russia, and Turkey. A three-cluster structure fitted the data well in all of the five countries. Within-country differences were observed in clusters of Russian and Turkish data in terms of driver behaviors. The detailed results are presented and discussed in relation to the literature.

Assessing rear-end collision risk of cars and heavy vehicles on freeways using a surrogate safety measure

This study analyzes rear-end collision risk of cars and heavy vehicles on freeways using a surrogate safety measure. The crash potential index (CPI) was modified to reflect driver’s reaction time and estimated by types of lead and following vehicles (car or heavy vehicle). CPIs were estimated using the individual vehicle trajectory data from a segment of the US-101 freeway in Los Angeles, U.S.A. It was found that the CPI was generally higher for the following heavy vehicle than the following car due to heavy vehicle’s lower braking capability. This study also validates the CPI using the simulated traffic data which replicate the observed traffic conditions a few minutes before the crash time upstream and downstream of the crash locations. The observed data were obtained from crash records and loop detectors on a section of the Gardiner Expressway in Toronto, Canada. The result shows that the values of CPI were consistently higher during the traffic conditions immediately before the crash time (crash case) than the normal traffic conditions (non-crash case). This demonstrates that the CPI can be used to capture rear-end collision risk during car-following maneuver on freeways. The result also shows that rear-end collision risk is lower for heavy vehicles than cars in the crash case due to their shorter reaction time and lower speed when spacing is shorter. Thus, it is important to reflect the differences in driver behavior and vehicle performance characteristics between cars and heavy vehicles in estimating surrogate safety measures. Lastly, it was found that the CPI-based crash prediction model can correctly identify the crash and non-crash cases at higher accuracy than the other crash prediction models based on detectors.

Identifying effects of driving and secondary task demands, passenger presence, and driver characteristics on driving errors and traffic violations – Using naturalistic driving data segments preceding both safety critical events and matched baselines

Researchers have identified various factors that likely affect aberrant driving behaviors and therefore crash risk. However, it remains unclear which of these factors poses the greatest risk for committing either errors or violations under naturalistic driving conditions. This study investigated important variables contributing to driving errors and traffic violations based on naturalistic driving data from the second Strategic Highway Research Program (SHRP 2). The analyzed driving segments preceded both safety critical events and matched baselines. Results showed that intersection influence, high-risk visually distracting secondary tasks, and the severities of the safety critical events were the main factors associated with driving errors. The primary factors linked to violations were intersection influence, persistent individual differences in driver behavior, and the severities of the safety critical events. Furthermore, the number of aberrant driving behaviors in trip segments preceding crashes was higher than in the matched segments unrelated to safety critical events. However, the most common aberrant driving behavior types in the respective segment groups appeared to resemble each other. This suggests that crashes became more likely due to drivers committing more violations and errors overall as opposed to drivers making one certain type of error or violation.

Identifying the main factors contributing to driving errors and traffic violations – Results from naturalistic driving data

Researchers have identified various factors that likely affect aberrant driving behaviors and therefore crash risk. However, it remains unclear which of these factors poses the greatest risk for either errors or violations under naturalistic driving conditions. This study investigated important variables contributing to driving errors and traffic violations based on naturalistic driving data from the second Strategic Highway Research Program (SHRP 2). In addition, this study identified factors determining the drivers’ willingness to perform common secondary tasks while driving, which have been associated with different degrees of crash risk. Results showed that anger, passenger presence, and persistent individual differences in driver behavior were the main factors associated with committed violations; surprise, high-risk visually distracting secondary tasks, and the driving task demand passing through an interchange were the main factors associated with errors. The willingness to engage in risky secondary tasks while driving appeared to be related to an overall tendency to engage in risky driving behaviors. However, drivers considered the driving context particularly when engaging in visually distracting secondary tasks. This study’s comprehensive approach should be a step towards generating a complete model of the variables that contribute to, or mitigate dangers in traffic.

Examining the safety impacts of narrow lane widths on urban/suburban arterials: Estimation of a panel data random parameters negative binomial model

ABSTRACTDesign practices in the United States generally allow substantial flexibility in the design of cross-sectional elements of urban and suburban arterial roadways. The operational and safety performance of such facilities is influenced by a variety of design controls, which influence the selection of important cross-sectional components, such as the number of lanes, lane widths, and the presence of shoulders, medians, or on-street parking. This study assesses the effects of lane width on the safety performance of urban and suburban arterial segments in the State of Nebraska. Ten years of traffic crash, volume, and roadway geometry data are analyzed to discern differences in the frequency of sideswipe-same direction and rear-end collisions across four functional classes of urban arterials. Crashes generally decreased as lane width increased, with 10-ft. lanes experiencing 18.1% more rear-end crashes and 27% more same-direction sideswipe collisions. In general, 12-ft. lanes showed fewer crashes than 11-ft. lanes. However, there was significant variability across the sample as 11-ft. lanes sometimes demonstrated fewer crashes, as well. These differences may be reflective of geometric characteristics that were not available in the dataset or of general differences in driver behavior across segments with varying cross-sectional characteristics.

Risky driving and recorded driving offences: A 24-year follow-up study

Permanent individual differences in driver behavior and accident risk have long been under active debate. Cognitive and personality factors have correlated with risky driving indicators in cross-sectional studies, and prospective cohort studies are now increasingly revealing early antecedents of risky behavior and injury mortality in adult age, with connections to stable personality traits. However, long-term stability in driver behavior or accident involvement has not been documented in a general driver population.This study reports 24-year follow-up data from a study that compared the recorded offenses between 134 drivers stopped by the police because of sustained risky driving and 121 control drivers stopped at the same locations at the same time in 1987 (Rajalin, 1994. Accid. Anal. Prev., 26, 555–562). Data were compiled from national driver records and accident statistics for the same drivers again 24 years later, and their yearly mileage and speed behavior was requested in a mail survey. The results showed that the two groups of drivers sampled on one trip a quarter of a century ago still differ from each other. The offenders still have more entries in their driver record, also when adjusted for age and mileage (OR=1.59, CI=1.03–2.46), they still report in the survey that they drive faster and overtake other cars more often. The results show that individual differences in driver behavior persist for decades, perhaps for life. However, in this on-road sample, the effect seems to be moderated by occupation which also presumably explains the lower mortality among the offenders during this 24-year follow-up.

Driver perspectives of open and tunnel expressways

Urban road tunnels are becoming more extensive due to land scarcity in city areas, and accident rates in these tunnels are comparatively lower than those on open roads. This study examines drivers' perspectives of open and tunnel expressways for 114 active drivers in Singapore using the free association technique. The driver perspectives of open and tunnel expressways were found to be different using t-tests on the frequency of associations to each category, and through multidimensional scaling analysis. Drivers perceive speed, traffic condition, and scenery to be most prevalent for open expressways; while lighting, enforcement, and safety are most prevalent for tunnel expressways. Road qualities important to the driver are identified in this study and the findings are discussed. Analysis of response valence reveals that tunnels are generally perceived less positively as compared to open expressways, and ANOVA found that frequent tunnel users do not perceive tunnel expressways more positively than infrequent users. The response valence is also found to correlate well with the reported quality of experience in each environment. The differences in driver perspectives may help explain differences in driver behaviour. Findings from this study also provide insight to road planners in meeting quality needs of drivers.

An International Review of Roundabout Capacity Modelling

Roundabouts are an increasingly common form of road junction worldwide, and their effective design requires a detailed analysis of maximum vehicle throughput capacities. In this paper, the worldwide state-of-the-art in roundabout capacity modelling is examined, covering the three main methodologies on which models are based: fully-empirical, gap acceptance and simulation. It is shown that due to their limitations, each of these methodologies on their own cannot completely explain the complex behavioural and physical processes involved in roundabout entries, hence all the models require strong semi-empirical or fully-empirical bases using data obtained from their countries of origin. Differences in driver behaviour and methodologies thus result in differences in predicted capacities by the various models, and although local calibration allows some transferability, it is often limited by the availability of data or an incomplete understanding of the relationships between model parameters and capacity.

An investigation of driver attitudes and behaviour in rural and urban areas in Norway

This study aimed to investigate differences in self-reported driver attitudes and behaviour in rural, peri-urban and urban areas in Norway. Age, gender and education were controlled for. An additional aim was to investigate the relations between demographics, personality variables, driver attitudes and behaviour in the complete sample and across the different geographical areas. To obtain these aims, a questionnaire was distributed by mail to a randomly selected sample from the Norwegian population registry ( N = 6203). Of the distributed questionnaires the response rate was 30%. Differences in attitudes and self-reported behaviour were significant due to type of geographical area. However, the results showed that gender, age and education caused stronger differences than type of geographical area in attitudes to driving and driver behaviour. SEM-analysis failed to reject the notion that the strength of the structural relations was similar in the geographical areas. This could imply that demographic characteristics, and their compositions in rural, peri-urban and urban areas, are more important for differences in driver behaviour and attitudes than characteristics of the traffic environment.

Analysis of driver behaviour for presentation of adaptive implementation strategies of assistance systems

Assistance systems, whose intervention strategies are based on average expected values, give away potential both in terms of driving safety as well as the expected user acceptance, since they neither meet the expectations nor the support needs of all drivers. One approach to comply with the intra- and inter-individual differences in driver behaviour is the analysis of the driving style and the derivation of situation and driver-oriented assistance. At the Department of Automotive Engineering at the Berlin Institute of Technology an approach was developed that shows the potential of driver-adaptive support using a brake assist system as example. The diploma thesis to this topic won the German award “Hermann Appel Preis 2007”, which is powered by the IAV GmbH.

AN INTELLIGENT AGENT MOBILE EMISSIONS MODEL FOR URBAN ENVIRONMENTAL MANAGEMENT

In this study, we developed a microcosmic mobile emissions model based on an intelligent agent model of vehicles. The intelligent agent was first introduced into a micro-traffic flow system. Individual differences in driver behavior were considered, and the theory of probability was applied to reflect the distribution of drivers' stochastic characteristic dispositions. Each vehicle expressed its intelligence through its own character by perceiving the leading vehicle. From an operational perspective, differences in drivers' dispositions were reflected by a weighted coefficient. Finally, a hybrid microcosmic mobile emissions model was proposed. Its coefficients were determined using traffic data and experiments. Because it addresses more aspects of the car-following process, this model is theoretically superior to previous models, as verified by a numerical simulation. The proposed model was applied to a case study of the emissions from ten vehicles in an urban setting. The model effectively estimated mobile emissions rates. The results indicate that the model can reflect individual differences among drivers and demonstrate that reckless drivers generate more emissions.

Do laboratory frontal crash test programs predict driver fatality risk? Evidence from within vehicle line variation in test ratings

A number of studies have examined whether the National Highway Traffic Safety Administration's (NHTSA) frontal crash test results reliably indicate the risk of fatality or injury in serious crashes. The conclusions of these studies are mixed. Generally, studies that examine crashes in the circumstances as close as possible to those of the laboratory test find that crash test results do predict real-world risk, but studies of crashes outside those specific circumstances find either no support for the predictive validity of crash test results or limited support with important inconsistencies. We provide a new test of the predictive validity of the crash test results using information from multiple crash tests within vehicle lines, thus controlling for systematic differences in driver behavior across vehicle lines. Among drivers of passenger cars, we find large, statistically significant differences in fatality risk for vehicles with one- to four-star NHTSA ratings versus a five-star rating. We also examine the Insurance Institute for Highway Safety's frontal offset crash test, though our sample of vehicle lines tested twice or more is considerably smaller than for NHTSA ratings. Our results also support the predictive validity of the frontal offset crash test results for passenger cars, but not for trucks.

Traffic Characteristics of Protected/Permitted Left-Turn Signal Displays

At least four variations of the permitted indication in protected/permitted left-turn (PPLT) control have been developed in an attempt to improve the level of driver understanding and safety. These variations replace the green ball permitted indication with a flashing red ball, a flashing yellow ball, a flashing red arrow, or a flashing yellow arrow indication. In addition, the Manual on Uniform Traffic Control Devices allows several PPLT signal display arrangements. The variability in indication and arrangement has led to a myriad of PPLT displays throughout the United States. The level of driver understanding related to each PPLT display type, and the associated impact on traffic operations and safety, has not been quantified. A study was conducted to evaluate the operational characteristics associated with different PPLT signal displays. Specifically, the study quantified saturation flow rate, start-up lost time, response time, and follow-up headway associated with selected PPLT displays. No differences in saturation flow rate and start-up lost time were found due to the type of PPLT signal display. Saturation flow rates ranged from 1,770 to 2,400 vehicles per hour of green per lane and were related to differences in driver behavior between geographic locations. The variation in start-up lost time and response time between locations was primarily related to differences in phase sequence. The flashing red permitted indications were associated with the longest follow-up headway times, since drivers are required to stop before turning left with a flashing red permitted indication. The shortest follow-up headway was associated with the five-section cluster display using a green ball indication.