Ecological Landscape Design and Evaluation in Public Charging Facilities for Electric Vehicles.

The deterioration of the environment in the 21st century has made environmental issues one of the most severe tests for modern society. With this comes a change in energy structure from high-carbon to low-carbon direction, and electric vehicles are gradually developing into the darling of a city with low-carbon transportation and safe travel. This paper carries out a systematic analysis of landscape design and environmental protection in the development of new energy electric vehicle charging facilities in urban habitat. By categorizing the content and provisions of published domestic and international standards, new requirements for standardization are obtained, including barrier-free design, electromagnetic radiation, child safety protection, and urban landscape integration. Among them, ecological landscape public charging facilities can enhance the overall quality of urban environment. This paper analyzes the necessity of landscape design in charging facilities, explores the ecological concepts extended by macroscopic landscape design principles and the problems of public charging facilities, and proposes a design and evaluation method of ecologically landscaped public charging facilities based on hierarchical analysis and neural networks. The hierarchical analysis method is introduced to establish a landscape design assessment index system, and then a neural network is introduced to describe the characteristics of electric vehicle charging, and the landscape design assessment learning samples are trained to establish a landscape design assessment model. Finally, a comparison experiment is conducted with other landscape design assessment methods using specific examples, and the results show that the proposed method has more obvious advantages in ecological landscape public charging facility design assessment with high accuracy, faster landscape design assessment, charging efficiency, and environmental protection.

Using satellite imagery to estimate heavy vehicle volume for ecological injury analysis in India.

A major limitation of road injury research in low- and-middle income countries is the lack of consistent data across the settings, such as traffic counts, to measure traffic risk. This study presents a novel method in which traffic volume of heavy vehicles - trucks and buses - is estimated by identifying these vehicles from satellite imagery of Google Earth. For Rajasthan state in India, a total of ∼44,000 such vehicles were manually identified and geo-located on national highways (NHs), with no distinction made between trucks and buses. To estimate population living in proximity to NHs, defined as those living within 1 km buffer of NH, we geocoded ∼45,000 villages and ∼300 cities using Google Maps Geocoding Application Programming Interface (API). We fitted a spatio-temporal Bayesian regression model with the number of road deaths at the district level as the outcome variable. We found a strong Pearson correlation of 0.84 (p < 0.001) between Google Earth estimates of heavy vehicles and freight vehicle counts reported by a national-level study for different road sections. The regression results show that the volume of heavy vehicles and rural population in proximity to highways are positively associated with fatality risk in the districts. These effects have been estimated after controlling for other modes of travel.

Advanced vehicle technologies and road safety: A scoping review of the evidence.

The proliferation of Advanced Vehicle Technologies (AVTs) has generated both excitement and concern among researchers, policymakers, and the general public. An increasing number of driver assistance systems are already available in today's automobiles; many of which are expected to become standard. Therefore, synthesizing the available evidence specific to the safety of AVTs is critical. The goal of this scoping review was to summarize this evidence with a focus on AVTs that require some driver oversight (i.e., Levels 0-3 as per the Society of Automotive Engineers (SAE) levels of automation taxonomy). A scoping review of research literature on AVTs was conducted for studies up to March 2018. Inclusion criteria consisted of: any study with empirical data of AVTs that included male and female drivers aged 16 years and older, healthy people (i.e., without impairments), passenger vehicles, driving simulators and/or large databases with road safety information that could be analyzed for the purpose of examining AVTs (SAE Levels 0-3), as well as measures of driving outcomes. A total of 324 peer-reviewed studies from 25 countries met the inclusion criteria for this review with over half published in the last 5 years. Data was extracted and summarized according to the following categories: measures used to evaluate the effect of AVTs on road safety (objective) and driver perceptions of the technology (subjective), testing environment, and study populations (i.e., driver age). The most commonly reported objective measures were longitudinal control (50 %), reaction time (40 %), and lateral position (23 %). The most common subjective measures were perceptions of trust (27 %), workload (20 %), and satisfaction (17 %). While most studies investigated singular AVTs (237 of 324 studies), the number of studies after 2013 that examined 2 or more AVTs concurrently increased. Studies involved drivers from different age groups (51 %) and were conducted in driving simulators (70 %). Overall, the evidence is generally in favour of AVTs having a positive effect on driving safety, although the nature and design of studies varied widely. Our examination of this evidence highlights the opportunities as well as the challenges involved with investigating AVTs. Ensuring such technologies are congruent with the needs of drivers, particularly younger and older driver age groups, who are known to have a higher crash risk, is critical. With automotive manufacturers keen to adopt the latest AVTs, this scoping review highlights how testing of this technology has been undertaken, with a focus on how new research can be conducted to improve road safety now and in the future.

Speeding and Speed Modification of Older Drivers: Does Vehicle Type Make a Difference?

The purpose of this study was to examine whether vehicle type based on size (car vs. other = truck/van/SUV) had an impact on the speeding, acceleration, and braking patterns of older male and female drivers (70 years and older) from a Canadian longitudinal study. The primary hypothesis was that older adults driving larger vehicles (e.g., trucks, SUVs, or vans) would be more likely to speed than those driving cars. Participants (n = 493) had a device installed in their vehicles that recorded their everyday driving. The findings suggest that the type of vehicle driven had little or no impact on per cent of time speeding or on the braking and accelerating patterns of older drivers. Given that the propensity for exceeding the speed limit was high among these older drivers, regardless of vehicle type, future research should examine what effect this behaviour has on older-driver road safety.

The adaptability and challenges of autonomous vehicles to pedestrians in urban China.

China is the world's largest automotive market and is ambitious for autonomous vehicles (AVs) development. As one of the key goals of AVs, pedestrian safety is an important issue in China. Despite the rapid development of driverless technologies in recent years, there is a lack of researches on the adaptability of AVs to pedestrians. To fill the gap, this study would discuss the adaptability of current driverless technologies to China urban pedestrians by reviewing the latest researches. The paper firstly analyzed typical Chinese pedestrian behaviors and summarized the safety demands of pedestrians for AVs through articles and open database data, which are worked as the evaluation criteria. Then, corresponding driverless technologies are carefully reviewed. Finally, the adaptability would be given combining the above analyses. Our review found that autonomous vehicles have trouble in the occluded pedestrian environment and Chinese pedestrians do not accept AVs well. And more explorations should be conducted on standard human-machine interaction, interaction information overload avoidance, occluded pedestrians detection and nation-based receptivity research. The conclusions are very useful for motor corporations and driverless car researchers to place more attention on the complexity of the Chinese pedestrian environment, for transportation experts to protect pedestrian safety in the context of AVs, and for governors to think about making new pedestrians policies to welcome the upcoming driverless cars.

Cognitive States Matter: Design Guidelines for Driving Situation Awareness in Smart Vehicles.

Situation awareness (SA) is crucial for safe driving. It is all about perception, comprehension of current situations and projection of the future status. It is demanding for drivers to constantly maintain SA by checking for potential hazards while performing the primary driving tasks. As vehicles in the future will be equipped with more sensors, it is likely that an SA aiding system will present complex situational information to drivers. Although drivers have difficulty to process a variety of complex situational information due to limited cognitive capabilities and perceive the information differently depending upon their cognitive states, the well-known SA design principles by Endsley only provide general guidelines. The principles lack detailed guidelines for dealing with limited human cognitive capabilities. Cognitive capability is a mental capability including planning, complex idea comprehension, and learning from experience. A cognitive state can be regarded as a condition of being (e.g., the state of being aware of the situation). In this paper, we investigate the key cognitive attributes related to SA in driving contexts (i.e., attention focus, mental model, workload, and memory). Endsley proposed that those key cognitive attributes are the main factors that influence SA. In those with higher levels of attributes, we found eight cognitive states which mainly influence a human driver in achieving SA. These are the focused attention state, inattentional blindness state, unfamiliar situation state, familiar situation state, insufficient mental resource state, sufficient mental resource state, high time pressure state, and low time pressure state. We then propose cognitive state aware SA design guidelines that can help designers to effectively convey situation information to drivers. As a case study, we demonstrated the usefulness of our cognitive state aware SA design guidelines by conducting controlled experiments where an existing SA interface is compared with a new SA interface designed following the key guidelines. We used the Situation Awareness Global Assessment Technique (SAGAT) and Decision-Making Questionnaire (DMQ) to measure the SA and decision-making style scores, respectively. Our results show that the new guidelines allowed participants to achieve significantly higher SA and exhibit better decision making performance.

A priori acceptance of highly automated cars in Australia, France, and Sweden: A theoretically-informed investigation guided by the TPB and UTAUT.

To assess and explain finely drivers' a priori acceptance of highly automated cars, this study used the Theory of Planned Behaviour (TPB) and the Unified Theory of Acceptance and Use of Technology (UTAUT). Further, the current study sought to extend upon previous research to assess if intentions to use highly automated cars in the future differed according to country (i.e., Australia, France, & Sweden). These three countries were selected to enable comparisons of a priori acceptance between countries of differing levels of exposure to highly automated cars. Participants (N = 1563; 62.1 % male) were recruited in Australia (n = 558), France (n = 625), and Sweden (n = 380) to complete a 20 min online questionnaire. The findings differed according to country of residence. Individuals residing in France reported significantly greater intentions to use highly automated cars when they become publicly available compared to individuals residing in Australia and in Sweden. Of the TPB constructs entered at step 1 in the hierarchical regression, attitudes, subjective norms, and perceived behavioural control (capability and controllability) were significant predictors of intentions to use highly automated cars for participants residing in Australia and France. For participants residing in Sweden, only attitudes and PBC-capability were significant predictors of intentions. Of the UTAUT constructs entered at step 2, performance expectancy and effort expectancy were significant predictors of intentions for participants residing in France and only performance expectancy a significant predictor of intentions for participants residing in both Australia and Sweden. Age and gender did not add to the prediction of intentions when entered at step 3. However, pre-existing knowledge was a significant negative predictor of intentions when entered at step 3 for participants residing in Australia. Overall, the findings found some support for applying the TPB and UTAUT to assess intentions to use highly automated cars in different countries. The findings also highlight differences in a priori acceptance across countries and the factors which predict such acceptance.

Optimizing the safety-efficiency balancing of automated vehicle car-following.

This paper proposes an approach to rationally set automated vehicles' car following behavior that explicitly balances between the competing considerations of safety (i.e. small probabilities of a high-consequence crash) and efficiency (guaranteed but small impacts on journey arrival time due to the choice of car following distance). The specification of safety and efficiency are both based on empirically supported concepts and data. In numerical analyses with empirical vehicle trajectories at two sites, we demonstrate intuitive response to systematic variation in numerical values selected as inputs, as well as whether the scope of the efficiency consideration is selfish or systemwide. The proposed balancing is aligned with the standard "Hand Rule" criterion to demonstrate that a duty of care has been met, in which a burden must be borne if it is less than the product of the probability of loss to a third party and the magnitude of loss. Thus the proposed approach is intended to be useful for designers of control algorithms for AVs to establish that they have met their duty of care, taking both safety and efficiency into account.

Exploring the who, what, when, where, and why of automated vehicle disengagements.

Automated vehicles are emerging on the transportation networks as manufacturers test their automated driving system (ADS) capabilities in complex real-world environments in testing operations like California's Autonomous Vehicle Tester Program. A more comprehensive understanding of the ADS safety performances can be established through the California Department of Motor Vehicle disengagement and crash reports. This study comprehensively examines the safety performances (159,840 disengagements, 124 crashes, and 3,669,472 automated vehicle miles traveled by the manufacturers) documented since the inauguration of the testing program. The reported disengagements were categorized as control discrepancy, environmental conditions and other road users, hardware and software discrepancy, perception discrepancy, planning discrepancy, and operator takeover. An applicable subset of disengagements was then used to identify and quantify the 5 W's of these safety-critical events: who (disengagement initiator), when (the maturity of the ADS), where (location of disengagement), and what/why (the facts causing the disengagement). The disengagement initiator, whether the ADS or human operator, is linked with contributing factors, such as the location, disengagement cause, and ADS testing maturity through a random parameter binary logit model that captured unobserved heterogeneity. Results reveal that compared to freeways and interstates, the ADS has a lower likelihood of initiating the disengagement on streets and roads compared to the human operator. Likewise, software and hardware, and planning discrepancies are associated with the ADS initiating the disengagement. As the ADS testing maturity advances in months, the probability of the disengagement being initiated by the ADS marginally increases when compared to human-initiated. Overall, the study contributes by understanding the factors associated with disengagements and exploring their implications for automated systems.

A numerical investigation of factors affecting lumbar spine injuries in frontal crashes.

Recent field data analyses have shown that lumbar spine fractures occurred more frequently in late model vehicles than the early ones in frontal crashes. Therefore, the objective of this study was to investigate risk factors associated with lumbar spine fractures in frontal crashes. Parametric simulations were conducted using a set of validated vehicle driver compartment model, restraint system model, and a HIII mid-size male crash test dummy model. Risk factors considered in the study included occupant seating posture, crash pulse, vehicle pitch angle, seat design, anchor pre-tensioner, dynamic locking tongue, and shoulder belt load limiter. ANOVA and ANCOVA were used to test the statistical significance (p < 0.05). Simulation results showed that all the factors that reduced the risk of submarining increased the lumbar spine forces, indicating a direct conflict between submarining and lumbar spine fractures. Among all the factors selected, seat structure is the most significant factor in determining the lumbar spine force (p < 0.001). Crash pulse severity, time at which the peak crash deceleration reached, and pitch angle are also crucial for lumbar spine force. Specifically, increase in vehicle pitch angle increased lumbar spine force, but reduced injury measures to other body regions; while a crash pulse with early peak produced greater lumbar spine force than that with a late peak. On average, more reclined posture increased the lumbar spine force compared to upright posture, and decreases in the coefficient of friction between the pelvis and the seat cushion reduced the lumbar spine force. However, they are not statistically significant. This study provided better understanding of effects from design countermeasures to reduce occupant lumbar spine injuries in new generation of vehicle models.

"Beasts"-New Zealand's utility vehicles: their climate change emissions and macho marketing.

Vehicle emissions are an important contributor to the growth of greenhouse gas emissions in New Zealand. Here we explore the role of sports utility vehicles (SUVs) and light utility vehicles (utes) in this problem. Marketed as macho symbols of toughness and dominance, often through comparisons with savage predators, these vehicles are promoted largely to male consumers. Eight out of 10 of the highest-selling new light vehicles in 2018 were SUVs or diesel-powered utes, with the latter standing out as the heaviest emitters of CO2, as well as posing health hazards through their emissions of fine particulates and NOx. The current popularity of these vehicles may create resistance to some of the substantive regulatory steps which will be needed if New Zealand is to meet its climate change commitments under the 2015 Paris Agreement. An example of such an initiative is the current government proposal for a Clean Car Standard and Clean Car Discount-a 'feebate' scheme which confers a price advantage on new electric vehicles and smaller cars.

Effect of Static Magnetic Field of Electric Vehicles on Driving Performance and on Neuro-Psychological Cognitive Functions.

Human neuropsychological reactions and brain activities when driving electric vehicles (EVs) are considered as an issue for traffic and public safety purposes; this paper examined the effect of the static magnetic field (SMF) derived from EVs. A lane change task was adopted to evaluate the driving performance; and the driving reaction time test and the reaction time test were adopted to evaluate the variation of the neuro-psychological cognitive functions. Both the sham and the real exposure conditions were performed with a 350 µT localized SMF in this study; 17 student subjects were enrolled in this single-blind experiment. Electroencephalographs (EEGs) of the subjects were adopted and recorded during the experiment as an indicator of the brain activity for the variations of the driving performance and of the cognitive functions. Results of this study have indicated that the impact of the given SMF on both the human driving performance and the cognitive functions are not considerable; and that there is a correlation between beta sub-band of the EEGs and the human reaction time in the analysis.

Potential benefits of controlled vehicle braking to reduce pedestrian ground contact injuries.

Protecting struck pedestrians during the ground contact phase has been a challenge for decades. Recent studies have shown how ground related injury is influenced by pedestrian kinematics. In this paper we further developed this approach by assessing the potential of controlling vehicle braking to reduce pedestrian ground contact injuries. Applying a recently proposed Simulation Test Sample, a series of simulations were run using the MADYMO software environment. The approach considered 6 vehicle shapes, 4 pedestrian models, 3 impact velocities and 2 pedestrian gaits and each case was considered with two different vehicle braking approaches. The first was full braking, while the second applied controlled braking, for which a strategy based on pedestrian kinematics was applied. The effect of vehicle braking was evaluated using the Weighted Injury Cost (WIC) of overall pedestrian injuries and the pedestrian-ground impact velocity change. The proximity of the vehicle and pedestrian at the instant of ground contact was also evaluated to assess the potential of future vehicle based intervention methods to cushion the ground contact. Finally real-world videos of pedestrian collisions were analyzed to estimate the available free vehicle stopping distances. Results showed substantial median reductions in WIC and head impact velocity for all vehicle shapes except the Van. The proximity of the pedestrian to the vehicle front at the instant of ground contact under controlled braking is less than 1.5 m in most cases, and the required stopping distance for the vehicle under controlled braking was within the available stopping distance estimated from the video footage in about 74% of cases. It is concluded that controlled braking has significant potential to reduce the overall burden of pedestrian ground contact injuries, but future efforts are required to establish an optimized braking strategy as well as a means to handle those cases where controlled braking is not beneficial or even harmful.

Exploring relationships between observed activation rates and functional attributes of lane departure prevention.

Objective: Drivers' use of lane departure warning and prevention systems is lower than use of other crash avoidance technologies and varies significantly by manufacturer. One factor that may affect use is how well a system prevents unintended departures. The current study evaluated the performance of systems that assist in preventing departures by providing steering or braking input in a 2016 Chevrolet Malibu, 2016 Ford Fusion, 2016 Honda Accord, and 2018 Volvo S90. These vehicles were selected because a prior observational study found that the percentage of privately owned vehicles that had lane departure prevention systems turned on varied among these 4 automakers. Method: In each vehicle, a test driver induced 40 lane drifts on left and right curves by steering the vehicle straight into the curve so that vehicles departed in the opposite direction and 40 lane drifts on straightaways by slight steering input to direct the vehicle to left and right lane markers. Results: Vehicles from automakers with higher observed lane departure prevention use rates (Volvo, Chevrolet) featured systems that provided steering input earlier and more often avoided crossing lane markers by more than 35 cm compared to vehicles from automakers with lower observed use rates (Ford, Honda). Conclusion: The study identified functional characteristics (i.e., timing of steering input, prevention of departures more than 35 cm) of lane departure prevention systems that were strongly associated with observed activation of these systems in privately owned vehicles. Although this relationship does not imply causation, the findings support the hypothesis that functional characteristics of lane departure prevention systems affect their use. Designers may be able to use these results to maximize driver acceptance of future implementations of lane departure prevention.

Sickness absence, disability pension and permanent medical impairment among 64 000 injured car occupants of working ages: A two-year prospective cohort study.

OBJECTIVE: There is a lack of knowledge regarding sickness absence (SA) and disability pension (DP) as consequences of road traffic injuries, and on the association between DP and permanent medical impairment (PMI). Therefore, the aim of this study was to investigate SA, DP, and PMI among injured passenger car occupants two years after a crash, and how they are associated, accounting for sociodemographics, crash-related factors, and previous SA/DP. METHODS: This prospective cohort study included 64 007 injured car occupants aged 17-62 years at the time of a crash occurring in 2001-2013, involving a car insured at Folksam Insurance Group in Sweden. Information on sociodemographics, crash-related factors, SA (in SA spells >14 days) and DP status at inclusion and at two-year follow-up, and PMI assessed by the insurance company was used. PMI grades were categorized as 1-4, 5-9, 10-19, or >19%. Logistic regression was performed to calculate odds ratios (OR) with 95% confidence intervals (CI) for DP at follow-up and for PMI, respectively. RESULTS: At the time of the crash 13% were already on SA or DP. At follow-up two years after the crash, 6% among those not already on SA/DP at the time of the crash were on SA and 2% on DP. Furthermore, 8% of the total cohort had a determined PMI. Among those not already on DP at the crash, 3% with no PMI had DP at follow-up. This proportion was higher the higher PMI grade. Among individuals without already ongoing DP at the crash date, 10% of those with a PMI 1-4 ha d DP, compared to 76% among PMI ≥ 20. Already ongoing SA at the time of the crash (OR = 39.16, 95% CI 34.89-43.95) and PMI grade (PMI ≥ 5 OR = 27.44, 95% CI 23.88-31.52, reference group PMI 0) were found to be associated with DP at two years after crash. The factor most strongly associated with PMI was the model year of the car. The older the car, the higher the risk of PMI (Model year ≤ 1990 OR = 3.36, 95% CI 2.67-4.23, reference group model year 2006-2010). An association with the same direction was also found between the model year of the car and DP at follow-up. CONCLUSIONS: The association between PMI grade and DP status at follow-up among occupants not on DP at the crash date indicates that both could be used to measure long-term consequences of road traffic injury. In this cohort, already ongoing SA at the crash date was associated with DP at the two-year follow-up, emphasizing the importance of accounting for this factor in future research.

Evaluating individual risk proneness with vehicle dynamics and self-report data - toward the efficient detection of At-risk drivers.

Vehicle-dynamics data, now more readily available thanks to moderate-cost, embedded data logging solutions, have been used to study drivers' behavior (acceleration, braking, and yaw rate) through naturalistic driving research aimed at detecting critical safety events. In addition, self-reported measures have been developed to describe these events and to assess various individual risk factors such as sensation seeking, lack of experience, anger expression while driving, and sensitivity to distraction. In the present study, we apply both of these methods of gathering driving data in order to assess risk proneness as accurately as possible. Data were obtained from 131 drivers, who filled in an introductory questionnaire pertaining to their driving habits. Their vehicles were equipped with an external, automatic data-capture device for approximately two months. During that period, the participants reported critical safety events that occurred behind the wheel by (a) pressing a button connected to the device and (b) describing the events in logbooks. They also filled in weekly questionnaires, and at the end of the participation period, a final questionnaire with various self-reported measures pertaining to their driving activity. We processed the data by (a) performing a multiple correspondence analysis of the characteristics assessed via the automatic data capture and self-reports, and (b) categorizing the participants via hierarchical clustering of their coordinates on the dimensions obtained from the correspondence analysis. This allowed us to identify a group of drivers (n = 43) at risk, based on several self-reported measures, in particular, their recent crash involvement, and the frequency of critical acceleration/deceleration events as an objective measure. However, the at-risk drivers did not themselves report more critical safety events than the other two groups.

Vehicle registration year, age, and weight - Untangling the effects on crash risk.

The aim of the present study was to investigate the effects of passenger cars' first year of registration, weight, and age on the number of killed or seriously injured (KSI) car drivers, pedestrians, and cyclists. Poisson regression models were developed of injury crashes involving passenger cars in Norway in 2000-2016, with the following predictor variables: The cars' first year of registration and weight, either crash year or car age, the drivers age and gender, and in models for car-car collisions the crash partner cars' weight and either registration year or age. The results show that there are fewer KSI car drivers in more recent, newer, and heavier cars. It is estimated that the number of KSI car drivers in all types of crashes on average decreases by 6.7% for each consecutive registration year (-7.2% in car-car collisions and -6.0% in single vehicle crashes), increases by 3.7% for each consecutive year of age (+2.1% in car-car collisions and +5.3% in single vehicle crashes), and decreases by 4.9% on average for each 100 kg weight increase (-11.1% in car-car collisions and -2.3% in single vehicle crashes). In car-car collisions there are fewer KSI car drivers when the crash partner car is more recent (-4.4% for each consecutive registration year), and more KSI car drivers when the crash partner car is older (+4.1% for each consecutive year of age), or heavier (+6.8% per 100 kg weight increase). In collisions with pedestrians or cyclists, there are fewer KSI pedestrians/cyclists when the car is more recent (-3.3% per consecutive registration year) and more KSI pedestrians/cyclists when the car is heavier (+4.6% per 100 kg weight increase). Due to the large effects of safety improvements in more recent cars, an increased renewal rate in the passenger car fleet can be expected to contribute to large safety improvements. The increasing weight of more recent cars may contribute to improved safety for those who drive heavier cars, but overall the effect of increasing weight is probably small or even negative because heavier vehicles impose greater risk on other car drivers, pedestrians, and cyclists.

Probabilistic, safety-explicit design of horizontal curves on two-lane rural highways based on reliability analysis of naturalistic driving data.

The high collision rates on horizontal curves compared to other roadway elements make them one of the most critical elements in a transportation network. In this regard, it is important to develop models to predict the safety performance of the horizontal curves. A considerable number of studies have been conducted to develop safety performance functions based on several concepts such as geometric characteristics, design consistency, reliability analysis, and comfort threshold. However, these models do not account for all horizontal curve design criteria or consider several cases such as driving in adverse weather conditions or on pavement of low available friction. This paper develops a probabilistic, safety explicit approach of horizontal curve design using reliability analysis of four design criteria: vehicle stability, driver comfort, sight distance, and vehicle rollover. Two situations were considered in the analysis: driving in clear weather (dry pavement) and raining weather (wet pavement) to develop safety performance functions for annual and five-year collision frequency. Four types of regression models, Poisson, negative binomial, zero-inflated Poisson, and zero-inflated negative binomial, were used in the analysis. The AIC, BIC, and Vuong test were used in evaluating the developed models.

Difference in severity and distribution of bodily injuries following collision between drivers of K-cars and standard vehicles.

BACKGROUND: Although K-cars, small four-wheeled vehicles with an engine capacity of <660 cc, have been used almost exclusively in Japan, they have recently become increasingly popular in other countries. Therefore, reporting the characteristics of bodily injuries sustained by K-car drivers after road traffic accidents (RTAs) may be important not only for health professionals but also for car manufacturers. METHODS: A single-center, retrospective observational study was conducted using prospectively acquired data. Between January 2010 and December 2017, 494 restrained drivers (331 men/163 women with a mean age of 45.1 years) whose vehicles had been severely damaged in RTAs underwent whole-body computed tomography prospectively. They were subsequently dichotomized into 221 K-car drivers and 273 standard vehicle drivers and compared for severity and distribution of bodily injuries. RESULTS: K-car drivers tended to be older and were significantly more likely to be female than standard vehicle drivers. The frequency of subjects with severe bodily injuries significantly higher among K-car drivers than among standard vehicle drivers (21.7% vs. 14.3%; p = 0.04), and the frequency of bowel/mesentery injuries tended to be higher in the former (9.0% vs. 4.4%; p = 0.06). However, the frequency of abdominal solid viscus injuries did not differ significantly between the two groups. Multivariable regression analysis showed that age [odds ratio (OR): 1.022; 95% confidence interval (CI): 0.998-1.047; p = 0.07] and K-cars (OR: 3.708; 95% CI: 0.984-6.236; p = 0.05) tended to be associated with bowel/mesentery injuries in restrained drivers. The frequency of pelvic/hip fractures also tended to be higher in K-car drivers than in standard vehicle drivers (5.9% vs. 2.6%; p = 0.10). By contrast, the severity and frequency of the upper torso injuries were similar between the two groups. CONCLUSIONS: Compared to standard vehicle drivers, K-car drivers seem to experience more severe bodily injuries after severe RTAs. Despite there being no answer for the increased frequency of only hollow viscus injuries but not solid viscus injuries among restrained K-car drivers, advanced age may, at least in part, be responsible. Given the limitations inherent to this study's single-center, retrospective design, multi-center prospective studies are warranted to verify our findings.