Inexperienced Drivers Research Articles

Young drivers’ perception of hazards: Variation with experience and day versus night

Young novice drivers have a relatively high crash risk for several years following initial licensing, and while all drivers are at greater risk at night, the night-time increase is greater for inexperienced drivers. Poor hazard perception has been identified as an important contributor to inexperienced drivers’ risk, but research on day-night differences in hazard perception for drivers varying in experience is lacking. This exploratory study investigated the nature of hazards reported by young inexperienced drivers versus more experienced and slightly older drivers. Hazards were not pre-identified by researchers; participants were simply provided with a general definition of ‘hazard’. Analysis focused on how experience level affected qualitative differences in the kinds of hazards reported, with particular focus on day-night differences.The 53 participants ranged in driving experience from learners through to 5+years post licensing, and in age from 16 to 30 years. They viewed 14 day- and night-time video clips of a diverse range of driving situations, pausing the video whenever they identified a hazard and then explaining why they had paused it at that point. Their responses were recorded. Content analysis of responses showed that more experienced drivers reported visibility-related hazards significantly more often than inexperienced ones, and significantly more so at night. They also commented significantly more on hazards related to tight bends in the road and significantly less on hazards concerning compliance with rules. Comments tended to be fewer with higher vehicle speeds, particularly for the least experienced drivers.Results are discussed in terms of how experience-related differences in drivers’ cognitive schemata and mental models are likely to affect hazard perception and crash risk, particularly at night. Some implications for driver training and license testing are suggested.

Detection of driver health condition by monitoring driving behavior through machine learning from observation

This paper describes our investigation to determine whether undesirable health conditions of an automobile driver can be identified in real time solely by monitoring and assessing his/her driving behavior. The concept has great potential to reduce the accident rate on roadways, especially for young inexperienced drivers who may be suffering from chronic health conditions that when uncontrolled, can result in dangerous driving actions. Our approach involves building models of “normal” and “abnormal” driving by an individual through machine learning from observation (MLfO, or simply LfO). Conceptually, discrepancies between actual driving actions taken by a driver in real time and the actions prescribed by a model of her/his normal driving, and/or similarities to a model of his/her abnormal driving, could indicate a dangerous medical condition. If appropriate, the system could alert the driver and/or the appropriate authorities (e.g., EMTs, police, or parents if a minor) of the potential for danger. More specifically, our research created models of human driving through the use of an LfO system developed previously in our laboratory called Force-feedback Approach to Learning from Coaching and Observation with Natural and Experiential Training (Falconet). Time-stamped traces of actions taken by 12 human test subjects in a driving simulator were collected and used to create the models of human driving behavior through Falconet. Then the overall actions prescribed by the models (called the agents) were compared to the original traces to ascertain whether similarities and/or differences between the human test subject behaviors and the agent behaviors could be indicative of the target conditions. In our use case presented here, the target condition was Attention Deficit/Hyperactivity Disorder (ADHD), a condition that afflicts many driving age teenagers and which can be detrimental to safe driving when not under control through medication. The work described in this paper is exploratory in nature, with the objective of showing scientific feasibility. The results of extensive testing indicate that the agents created with the Falconet system produced promising results, being able to correctly characterize traces in up to nearly 82% of the test cases presented. Nevertheless, as is typical in such exploratory works, we found that much further work remains to be done before this concept becomes ready for commercial application. In this paper we describe the approach taken, the agents created and the extensive quantitative experiments conducted, as well as any insights learned. Areas of further research are also identified and discussed.

Yellow light decision based on driving style: Day or night?

Drivers' driving decisions at yellow lights are an important cause of accidents at intersections. As proved by existing studies, driving style is an important basis for a driver to decide to pass a yellow light or not. This study, therefore, aims to investigate the effects of different driving styles on driving decisions at yellow lights under different lighting conditions. Specifically, 64 licensed drivers were recruited to comparative study the effects of different driving styles on the decision to pass through yellow lights under both daytime and nighttime lighting conditions using a driving simulator and a VR device. The results showed that maladjusted drivers more likely to pass the yellow light faster than adapted drivers (81.25% vs 43.75%) during both day and night. Male drivers had higher overall driving style scores than female drivers, and male drivers were faster and more likely to pass a yellow light than female drivers (56.25% vs 31.25%). This study also found that inexperienced drivers were faster and more likely to pass a yellow light than experienced drivers (50% vs 37.5%). Overall, maladjusted drivers are more likely to pass yellow lights, which can be improved and society properties by enhancing driving learning for maladjusted drivers.

Quantifying the Impact of Traffic on Electric Vehicle Efficiency

While the influence of several factors on battery electric vehicle (BEV) efficiency has been investigated in the past, their impact on traffic is not yet fully understood, especially when driving in a natural environment. This paper investigates the influence of driving in intense traffic conditions while considering the ambient temperature and driving behavior on BEV energy efficiency in a field study. A total of 30 BEV inexperienced drivers test drove a 2017 Volkswagen eGolf on a route with various road types in two different traffic intensity scenarios: During morning commute hours with higher traffic congestion and lower congestion hours throughout the middle of the day. Results support the hypothesis that traffic conditions significantly impact the vehicle’s efficiency, with additional consumption of approximately 4–5% in the high traffic scenario. By creating and comparing driving in traffic to an underlying base case scenario, the additional range potential by avoiding traffic for this particular vehicle can be quantified as up to seven miles. New patterns of BEV efficiencies emerged, which can help stakeholders understand how eco-driving can be strategically improved by selecting trip times and routes that avoid high traffic intensity.

Study on Risk Tolerance of Passenger Car Drivers Aged 18–25

A universal problem of the impact of behaviour of less experienced young drivers on the rate of road accidents referring to the Russian Federation in comparison to other countries.In the Russian Federation, in recent years, there has been a decrease in the total number of road accidents and in the number of deaths in them. This speaks of the effective preventive work of the traffic police and other related services, but at the same time, a fairly large number of car accidents persists.One problem is the high incidence of accidents among inexperienced young drivers. According to research conducted in different countries, the likelihood of road accidents is especially high during the first year after obtaining a driver’s license. The overwhelming majority of drivers responsible for road accidents with less than six months of driving experience belong to the age category of 18–25 years. One of the main reasons for the increased likelihood of road accidents is their excessive risk inclination.It is obvious that risky driving is common in young people, which also affects the operation of the car. Risk inclination is directly related to the number of errors made, which significantly increases the likelihood of an accident.Objective of the work was to assess the risk tolerance among drivers aged 18–25 years. Research methods comprise a survey of young people of the indicated age and the analysis of the results obtained. The figures obtained during the survey indicate that the majority of respondents (82 %) have a «mean level of risk tolerance». But there are also quite a few «risky drivers» (15 %). Moreover, these 15 % are in the youngest age group from 18 to 21 years old. Based on the results of the work, it is proposed: during training at a driving school, the future driver should receive not only theoretical knowledge and practical driving lessons, but also undergo a psychological analysis to determine his fitness to participate in road traffic; introduce certain restrictions «for young and novice drivers» into the Road Traffic Regulations. It is necessary to limit the permitted power of the car and the permissible speed (adoption of a multiplying coefficient for fines for speeding), prohibit the use of the car in the dark and in difficult road conditions, as well as passenger transportation.

Prediction of TBM Operational Parameters Using an Integrated Data Mining Framework

Tunnel Boring Machine (TBM) is widely used in tunnel construction because of its high safety, less effect on surroundings and rapid excavation speed. However, its performance is highly dependent on the adjustment of operational parameters during tunnelling. In many cases, the project delays even the accidents take place due to the mis-operation of inexperienced drivers. To improve the adaptability of a TBM in complex geological conditions, this study proposes an integrated data mining framework to perform near real-time prediction of two operational parameters including thrust and torque. The integrated framework provides a set of data processing methods including data cleaning, partition of full tunnelling cycles, feature extracting and model establishment. These data mining methods were applied to analyse the in-situ data of a water conveyance project. The results showed that the proposed framework performed well in predicting those two parameters with the determination coefficient R2 all exceeding 0.9, which illustrated the feasibility of using the proposed framework to assist driving in TBM construction.

Reducing vehicle fuel consumption and exhaust emissions from the application of a green-safety device under real driving

Vehicle emissions have a significantly negative impact on climate change, air quality and human health. Drivers of vehicles are the last major and often overlooked factor that determines vehicle performance. Eco-driving is a relatively low-cost and immediate measure to reduce fuel consumption and emissions significantly. This paper reports investigation of the effects of an on-board green-safety device on fuel consumption and emissions for both experienced and inexperienced drivers. A portable emissions measurement system (PEMS) was installed on a diesel light goods vehicle (LGV) to measure real-driving emissions (RDE), including total hydrocarbons (THC), CO CO2, NO, NO2 and particulate matter (PM). In addition, driving parameters (e.g. vehicle speed and acceleration) and environmental parameters (e.g. ambient temperature, humidity and pressure) were recorded in the experiments. The experimental results were evaluated using the Vehicle Specific Power (VSP) methodology to understand the effects of driving behavior on fuel consumption and emissions. The results indicated that driving behavior was improved for both experienced and inexperienced drivers after activation of the on-board green-safety device. In addition, the average time spent was shifted from higher to lower VSP modes by avoiding excessive speed, and aggressive accelerations and decelerations. For experienced drivers, the average fuel consumption and NO, NO2 and soot emissions were reduced by 5%, 56%, 39% and 35%, respectively, with the on-board green-safety device. For inexperienced drivers, the average reductions were 6%, 65%, 50% and 19%, respectively. Moreover, the long-term formed habits of experienced drivers are harder to be changed to accept the assistance of the green-safety device, whereas inexperienced drivers are likely to be more receptive to change and improve their driving behaviors.

A driving simulation study on the effects of different wine types on the performance of young drivers

BackgroundAlcohol consumption is responsible for a significant number of road fatalities. To contrast this phenomenon, a more responsible attitude to the wine consumption, especially among young, inexperienced drivers prone to risky behaviour on the road must be promoted. MethodThis is a simplified single-blind, placebo-controlled experiment aimed at evaluating 44 young drivers monitored during a driving simulation following the consumption of natural and conventional wines, with a reference blood alcohol concentration (BAC) of 0.5 g/l. Two hypotheses are tested: (1) the legal consumption of wine has no significant impact on young drivers’ performance in both ordinary and unusual road events; (2) natural and conventional wines are expected to produce negligible and acceptable impairments in young drivers the same BAC. Two reference groups (BAC = 0 g/l), one a placebo-controlled group with drivers treated with a dealcoholized wine, were included. Results and ConclusionsSignificant differences between the groups in terms of perception and reaction times (PRT) to visual and auditory stimuli, and to speeding were observed, with young drivers treated with conventional wine displaying more aggressive behaviours. In contrast, participants treated with natural wine showed PRT which were not significantly different from those belonging to control groups. The gaze attention levels of wine treated drivers were found to be dose dependant, with young drivers of the two control groups and those of the treated ones with BAC < 0.3 g/l able to focus on wider area ahead and, thereby, collect more information from the road environment.

Risky Decision-Making and Hazard Prediction are Negatively Related and Could Be Assessed Independently Using Driving Footage.

IntroductionTraffic collisions are a principal cause of death in Europe, disproportionately affecting young drivers. Driving safety depends not only on our ability to anticipate and respond to dangers on the road but also on the level of risk we are willing to engage within our own driving behaviour.MethodsHazard prediction (HPr) and risky decision-making (RDM) tests were given to three groups of young Spaniards (169 participants): 54 non-drivers (M=20), 65 novice (M=21) and, 50 experienced drivers (M=26 years old). Both tests presented participants with video clips of driving recorded from the driver’s perspective. The HPr test contained hazardous situations caused by the actions of another road user (eg, a pedestrian crossing the road). Each HPr clip was occluded as a hazard began to unfold and participants were asked to predict “what happens next?” They selected their answer from four on-screen options. The RDM test used clips where any imminent danger would be provoked by the film-car driver’s risky behaviour (eg, overtaking illegally). Participants were asked to report the probability of following certain types of risky behaviour (eg, “Would you go forward with the lights on amber?” or “Would you overtake the cyclist/lorry/bus at this point?”). In addition, the effect of the locality of the driving scenarios was manipulated: they could take place in the participant’s native country (Spain) or in a different country (UK).ResultsNon-drivers and novice drivers were less able to predict upcoming hazards and more likely to make risky decisions. Driving scenarios from another country (UK) provoked riskier decisions than those from the participants’ home country (Spain).ConclusionImprovement in HPr skills among novice or new drivers poses a huge challenge as far as driver training is concerned, though it is only part of the solution. Young inexperienced drivers’ willingness to engage in risky behaviour also needs to be tackled. Our results suggest that such RDM can be assessed in a similar way to HPr skill, using a naturalistic approach, which raises the possibility of assessing and training drivers on a wider range of safety-related behaviours.

Impact of Driver Age and Experience in Software Usage on Driving Safety and Usability of Car-Sharing Software

Car-sharing economy has caused new driving safety and usability problems, which have not been well studied. This study aims at analyzing the effects of users age and the user experience (UX) of the car-sharing software (e.g., DiDi travel app) on overall usability and the level of distraction for drivers. To this end, 48 experienced Chinese drivers were recruited to perform various tasks with the car-sharing software using a driving simulator. The variables of driving safety and usability were analyzed by two-way analysis of variance (ANOVA) and independent sample Kruskal–Wallis nonparametric test. As expected, it was found that car-sharing software has a significant negative impact on driving distraction and usability. The overall performance of young drivers is better than that of the elderly, but it seems that young drivers are more likely to be led to errors by car-sharing software. In most aspects, experienced drivers perform better than inexperienced drivers and have a better in-depth understanding of car-sharing software weaknesses. However, inexperienced drivers performed better regarding braking time and interaction time. Although young inexperienced drivers performed worst in driving safety, they exhibited the lowest cognitive load and the highest interaction efficiency. The experience of using car-sharing software may improve driver’s ability to deal with driving distractions. The above conclusions provide theoretical support for optimizing the UX of car-sharing software and some references for driver’s screening and training.

Effect of time pressure on steering control of the drivers in a car-following situation

The current study focused on analyzing steering control of the drivers during a car-following situation under increasing time pressure conditions. A driving simulator experiment was conducted on ninety-two participants to assess steering performance measures. Five different steering control measures: Variability in Steering Angle (VSA), Steering Reversal Rate (SRR), Steering Speed (SS), Stability of Steering Control (SSC), and Maximum Steering Swerve (MSS) were examined under No Time Pressure (NTP), Low Time Pressure (LTP), and High Time Pressure (HTP) driving conditions. Repeated measures ANOVA (for continuous data) and Friedman’s test (count data) with post-hoc analysis and Generalized Estimating Equation (GEE) modeling technique were used to investigate the influence of time pressure and different predictor variables. The statistical analysis showed that time pressure driving conditions significantly affected steering control of the drivers. The pairwise comparison of time pressure conditions revealed that HTP significantly affected most of the steering control measures as compared to LTP. Further, a GEE model also exhibited similar results where steering control measures were substantially influenced by HTP as compared to LTP. Moreover, in addition to time pressure conditions, demographic characteristics showed significant influence on steering control measures. The GEE model results showed that female drivers performed 13% more steering corrections (5° SRR) which led to better SSC by 124.44% than male drivers. Additionally, it was discovered that young-aged and experienced drivers took extra steering efforts to control lateral position of the vehicle by increasing 53.50% SS and 1% SRR compared to middle-aged and inexperienced drivers. The findings from the current study revealed that drivers undergo fast and abrupt steering maneuvers under time pressure conditions. The research approach demonstrated in the current study can be beneficial to discriminate minimum requirement of steering efforts and set-up threshold values for various steering evasion techniques to control and maintain safe lateral position during car-following maneuvers.

Hazard Perception, Presence, and Simulation Sickness-A Comparison of Desktop and Head-Mounted Display for Driving Simulation.

Driving simulators are becoming increasingly common in driver training and assessment. Since virtual reality is generally regarded as an appropriate environment for measuring risk behavior, simulators are also used to assess hazard perception, which is considered to be one of the most important skills for safe driving. Simulators, which offer challenges that are indeed comparable to driving in real traffic, but at a very low risk of physical injury, have the potential to complement theoretical and practical driver trainings and tests. Although configurations and fidelity differ considerably between driving simulators, studies comparing the impact of their distinct features on driving performance and test validity remain rare. In this context, prior research demonstrated that a wider field of view (three monitors compared to a single monitor) led to earlier speed adjustments in response to potential hazards—especially for experienced drivers. The wider field of view was assumed to cause the drivers to be more present in the virtual world, which in turn provoked more natural scanning of the road and therefore, earlier hazard detection in experienced drivers. Research on spatial presence in other contexts support this assumption. The present experiment investigated whether this effect could be enhanced by an even more immersive presentation technique for driving simulation: a head-mounted display (HMD). Moreover, we studied the interplay between display mode, sense of presence and simulation sickness. Eighty experienced and less experienced drivers completed six simulation-based hazard perception scenarios, which were displayed either via a triple-monitor set-up or an HMD. Results indicate that the experienced drivers showed very similar driving and risk behavior as the inexperienced drivers in both experimental conditions. However, there were significant differences between the two display conditions. The use of an HMD resulted in a clearer and more abrupt speed reduction, more virtual presence, and a higher degree of simulation sickness. However, the interrelation between these three variables could not be conclusively clarified in the present study and thus represents a research aim that could be addressed in future studies.

Self-Reported Habitual Practices and Perceptions of Young Drivers in Sri Lanka

Crashes on the road have become a significant socio-economic problem. Younger generations, who have lesser experience in driving, are at greater risks of facing road accidents. It is therefore important to identify driving practices and perceptions of young and inexperienced drivers at an early phase of exposure so that factors that improve safe driving can be identified.This study analysed 400 young and inexperienced drivers’ self-reported habitual practices and perceptions based on a questionnaire survey. The questionnaire focused on supervision of early driving, limitation made by parents, accident and traffic offenses by these youngsters as drivers as well as other habitual driving practices. Analyses were done using reliability statistics, inter-item correlation, likelihood ratio tests, and parameter estimates. The highest inter-item correlation value was 0.467 for the pair of overtaking vehicles in restricted areas and taking the chance to speed and run a yellow light when it is about to change to red. Driving after alcohol consumption, mobile phone usage, taking an illegal U-turn at restricted areas, non-use of signals when changing lanes and overtaking a slow driver from the left side were influenced non-use of seat-belts by young drivers. These habitual practices while driving highlighted the importance of early intervention to improve road safety.In conclusion, there is always one or more habitual driving practices that have affect the other driving habits of a young driver.

Statistical Evaluation of BIS-11 and DAQ Tools in the Field of Traffic Psychology

This paper focuses on the statistical evaluation of two independent research tools in the field of traffic psychology. Our research focuses on young drivers in the Slovak Republic and conducts an international comparison. At present, these young drivers make up only about 7% of the total number of drivers, but they cause about 20% of accidents. The paper analyzes the traffic accident rate of young as well as inexperienced drivers. All drivers in the survey had a short period of driving experience. The traffic-psychological survey obtained detailed data via two independent tools. We aimed to find relations between the factors and subfactors of the tools used, namely the BIS-11 (Barratt Impulsiveness Scale) and DAQ (Driver Attitude Questionnaire). The researchers also used these tools in other countries, so it was possible to compare the results obtained. The results from these tools should reveal the psychological causes of as many traffic accidents as possible. Our paper shows the possibilities for the evaluation of the tools used with correlation analysis. The results of our research are shown in symmetrical matrixes of correlation coefficients. Our study also compares its values with the results of foreign authors. Such research has revealed some facts about young drivers’ violations connected with drunk driving, speeding, and other traffic offenses. Our aim was to find connections between the driver’s history (skills, traffic accidents, age, etc.) and psychological characteristics, and we have answered several research questions. In conclusion, we have highlighted the most significant relationships between the factors of driver psychology.

Motor vehicle driver injury severity analysis utilizing a random parameter binary probit model considering different types of driving licenses in 4-legs roundabouts in South Australia

A roundabout may not provide an acceptable level of control and can be confusing to inexperienced drivers. Therefore, the purpose of this study is to identify the contributing factors that lead to specific driver injury severity by utilizing a random parameter binary probit model sustained by different experiences of motor drivers at 4-legs roundabouts in South Australia. Four models were estimated based on seven years of crash data (2012–2018), considering different types of motorist-driving license: learner, provisional, full, and for all datasets, including unknown licensures. The model estimates variables have been categorized into a driver, crash, temporal, spatial, vehicle, roadway characteristics, and vehicle movements. The results showed there are differences between resulting crash-injury severities when driver experience has been observed. Besides, several parameters were found to be random and normally distributed: safety equipment, crash type (rear-end crash), number of involved vehicles, weekdays indicator, stats area (crash occurred within metropolitan), vehicle type (passenger car), and posted speed limit (more than 50 km/hr.). In addition, the log-likelihood and the transferability test indicated that the data should be separated and analyzed according to the driver's license. Findings can help authorities to improve driver safety considering the influence of the driver experience.

Dispatch optimisation in O2O on-demand service with crowd-sourced and in-house drivers

O2O (Online to Offline) services enable customers to place orders online and receive products/services offline. In addition to traditional in-house drivers, the emergence of crowd-sourced drivers provides an opportunity to re-organise offline delivery services. In practice, three types of workforce, namely, in-house, full-time, and part-time crowd-sourced drivers, coexist in the system while exhibiting different characteristics. This situation creates challenges for the management of order assignment and routing. In particular, we study three settings in response to different driver preferences: the guaranteed minimum daily number of orders for full-time drivers; the maximally allowed number of orders per trip; and the detour proportion for part-time drivers. This paper aims to provide a method for O2O platforms to optimise order assignment and routing, considering these designs about driver preferences. We further validate our model and study managerial insights using real datasets. Specifically, the results show that among all designed parameters for the O2O on-demand delivery system, two parameters – the maximally allowed number of orders per trip and the detour proportion – are critical for the design. Moreover, we find that incentive mechanisms for inexperienced and experienced drivers are different because of their service capacities. The managerial insights are expected to guide practitioners.

Non-Parametric Association Rules Mining and Parametric Ordinal Logistic Regression for an In-Depth Investigation of Driver Speed Selection Behavior in Adverse Weather using SHRP2 Naturalistic Driving Study Data

Human error is considered to be one of the major causes of crashes, especially in inclement weather. Although many studies have investigated the effect of adverse weather on traffic safety and operations, there is a lack of research into the differences in driving behavior and performance during adverse weather, particularly at a trajectory level. With this research gap in mind, this study presents a novel approach for an in-depth investigation of driver speed selection behavior in adverse weather utilizing trajectory-level data acquired from the SHRP2 Naturalistic Driving Study using a promising association rules data mining technique. The preliminary analysis revealed that drivers reduced their speeds by 3.9% in the presence of light rain, by 10.2% in heavy rain, 15.2% in light snow, 29.8% in heavy snow, 1.8% with distant fog, and 7.4% with near fog. The findings from the association rules mining approach indicated that driving more than 5 mph above the speed limit was closely associated with clear weather as well as young and inexperienced drivers; whereas a reduction in speed to more than 5 mph below the speed limit was closely associated with snowy road surfaces combined with affected visibility. These findings are also in line with the results from the ordered logistic regression, which revealed that drivers were 1.4 times more likely to reduce their speeds in light rain, 1.7 times in heavy rain, 4.3 in light snow, 12.2 in heavy snow, 1.7 with distant fog, and 2.0 with near fog. The findings from this study provide an unprecedented opportunity to develop a Human-in-the-Loop Variable Speed Limit algorithm.

Aetiology, prevalence, fracture site and management of maxillofacial trauma.

Maxillofacial fractures are often associated with severe morbidity, functional deficit, disfigurement and significant financial implications. The aim of this review was to investigate whether the aetiology, prevalence and management modalities of facial trauma can identify the common causes of facial trauma with a view to recommending measures to the appropriate governing bodies to change the current practice wherever possible. The records of 1,112 patients referred to our oral and maxillofacial unit in Andhra Pradesh, India, between February 2008 and October 2017 were analysed retrospectively. Data including age, sex, aetiology, fracture site and treatment were evaluated. Men aged 20-40 years were the most common victims of facial trauma. Road traffic accidents (RTAs) were responsible in 70% of cases. Mandibular fractures constituted 47% of the overall fractures, and 55% of the total fractures were treated with open reduction and internal fixation. The main cause of maxillofacial injury among patients reporting to our hospital was RTAs. Mandibular fractures were the most common, accounting for almost half of the cases. Over half (55%) of all maxillofacial fractures were treated with open reduction and internal fixation. Reasons for this high frequency may include the large number of poorly maintained, overloaded vehicles on unsuitable roads, violation of traffic regulations (particularly by inexperienced young drivers), abuse of alcohol or other intoxicating agents and the sociocultural behaviours of some drivers.

Expansion of NASS/CDS for characterizing run-off-road crashes

Objective Run-off-road (ROR) crashes account for one-third of all annual crash fatalities in the US. The National Automotive Sampling System Crashworthiness Data System (NASS/CDS) is a dataset which may be used to understand the nature of ROR crashes. Despite the wealth of coded data available in NASS/CDS, this dataset lacks coded information about the roadside environment and the off-road trajectory of the vehicle. This information would be useful for determining lane departure warning (LDW) benefits, residual safety problems, performance of current safety hardware, lane marking inventory, LDW test procedure development, radius of curvature characterization, and effectiveness of ESC. The purpose of this paper is to demonstrate a methodology for expanding the data available in NASS/CDS to form and validate a specialized road departure database. Methods Observed, measured, and reconstructed data elements were extracted from NASS/CDS and compiled into the National Cooperative Highway Research Program (NCHRP) 17-43 database. Observed variables were primarily coded from the scene photographs and included information such as the lane markings, and geometry of the roadside cross-section. Additional variables were measured from the scaled scene diagrams including the path of the vehicle, road dimensions, and roadside object positions. The vehicle impact speed and departure speed were reconstructed using the WinSMASH delta-v, roadside object characteristics, and vehicle path. Two studies were conducted to demonstrate the usefulness of the NCHRP 17-43 database in evaluating both vehicle-based and infrastructure-based ROR countermeasures. Results The resulting NCHRP 17-43 database includes 1,581 NASS/CDS cases representing 510,154 ROR crashes. Analysis of the database found that drivers which crashed following an overcorrection were younger than drivers which did not overcorrect. This may indicate that inexperienced drivers are more likely to overcorrect when departing the roadway. The 85th percentile impact severity of ROR crashes, which occur on roads with a speed limit greater than 65 mph, is higher than the practical worst-case test conditions for roadside barriers. Conclusions The NCHRP 17-43 database contains information extracted from NASS/CDS cases to better understand the nature of ROR crashes, driver behavior in these crashes, and the potential benefits of both vehicle-based and infrastructure-based ROR countermeasures.

Traffic Congestion Issues, Perceptions, Experience and Satisfaction of Car Drivers/Owners on Urban Roads

Traffic congestion is a major issue of Asian megacities which causes the irritation, anger and frustrations among drivers and owners of vehicles during driving in these cities. This paper aims at understanding traffic congestion issues from the perception and experiences of car drivers and owners and their satisfaction level concerning accessibility of circulation within urban roads of Karachi. The issues addressed in this respect are road construction, traffic flow, road crossing, shopping malls along roads, traffic blockage due to VIP movement, congestion during school timing, animal presence on roads, traffic police behavior, marriage halls along the roads, peak hour traffic jams, traffic jams during sociopolitical and religious rallies, road disputes, traffic congestion due to young inexperienced drivers, alternate road availability and pedestrian bridges. The method of investigating these issues is through 42 questionnaire surveys with car drivers and car owners from June to October 2018 on urban roads of Karachi. The analysis of feedback from respondents showed that, more than 90% respondents were satisfied with construction of pedestrian bridges and annoyed with sociopolitical and religious rallies on main urban roads. More than 80% respondents were satisfied with marriage halls along the roads, felt congestion during peak hours and preferred alternate routes to go home. More than 70% agreed that, young and inexperienced drivers cause traffic congestion and felt unsatisfied and displeased with disputes on the streets among residents, traffic police and drivers. More than 60% respondents were satisfied with the road construction but annoyed with VIP protocol and felt congestion during school timings and quite uncomfortable while crossing the road. More than 50% respondents were unsatisfied with shopping malls on both sides of the road, presence of animals on main roads and behavior of traffic police during traffic jams. Finally, concerning traffic flow the respondents were equally divided in their perception. Thus this research presents a detailed perspective of people regarding traffic congestion issues in Karachi for the appropriate response by decision makers of urban transport planning and urban traffic management institutions in city.