Traffic congestion and ozone precursor emissions in Bilbao (Spain)

GOAL. SCOPE. BACKGROUND: In urban environments, the measured levels of ozone are the result of the interaction between emissions of precursors (mainly VOCs and NOx) and meteorological effects. In this work, time series of daily values of ozone, measured at three locations in Bilbao (Spain), have been built. Then, after removing meteorological effects from them, ozone and traffic data have been analyzed jointly. The goal was to identify traffic situations and link them to ozone levels in the area of Bilbao. METHODS: To remove meteorological effects from the selected ozone time series, the technique developed by Rao and Zurbenko was used. This is a widely used technique and, after its application, the fraction obtained from a given ozone time series represents an ozone forming capability attributable to emissions of precursors. This fraction is devoid of any meteorological influence and includes only the apportion of periodicities above 1.7 years. In the case of Bilbao, the ozone fractions obtained at three locations have been compared on that time scale with traffic data from the area. RESULTS AND DISCUSSION: For the 1993-1996 period, a regression analysis of the ozone and traffic fractions due to periodicities above 1.7 years (long-term fractions), shows that traffic is the main explanatory factor for ozone with R2 ranging from 0.916 to 0.996 at the three locations studied. Analysis of these longterm fractions has made it possible to identify two traffic regimes for the whole area, associated to different profiles of ozone forming capability. The first one favors low ozone forming capability, and is associated with a situation of fluent traffic. The second one shows high ozone forming capability and represents congestion. Joint analysis of raw data of ozone and traffic do not show any clear pattern due to the strong masking effects that seasonal-meteorological effects (mainly radiation) have on the measured ozone signal. If only immission data of ozone are available, as in this case, a comparison between ozone and traffic can only be made on the long-term time scale, since that is the only fraction embedded in the ozone time series that can exclusively be attributed to emissions of precursors. This fact stresses the need to study the different fractions embedded in the time series of ozone measured levels separately. CONCLUSION: Though the coefficients obtained in the regression are only valid for the 1993-1996 period, these traffic regimes represent long-term targets (congestion or fluent traffic) that can inspire policies for a joint management of the traffic and pollution by ozone in the area of Bilbao beyond that period. RECOMMENDATIONS AND OUTLOOK: The results of this work show the need of a joint management of ozone and traffic in Bilbao. Since an accurate knowledge of traffic was not available, the use of emission factors to relate traffic and actual ozone levels has not been possible. For this reason, this study has focused on the long-term fractions of traffic and ozone. In the future, if a more accurate knowledge of traffic is available, it will be possible to find relationships between traffic and ozone on all time scales.     

Transport company safety climate—The impact on truck driver behavior and crash involvement

Objective: The present study investigated the relationships between safety climate and driving behavior and crash involvement.

Methods: A total of 339 company-employed truck drivers completed a questionnaire that measured their perceptions of safety climate, crash record, speed choice, and aberrant driving behaviors (errors, lapses, and violations).

Results: Although there was no direct relationship between the drivers' perceptions of safety climate and crash involvement, safety climate was a significant predictor of engagement in risky driving behaviors, which were in turn predictive of crash involvement.

Conclusions: This research shows that safety climate may offer an important starting point for interventions aimed at reducing risky driving behavior and thus fewer vehicle collisions.     

Teaching infant car seat installation via interactive visual presence: An experimental trial

Objective: A large portion of child restraint systems (car seats) are installed incorrectly, especially when first-time parents install infant car seats. Expert instruction greatly improves the accuracy of car seat installation but is labor intensive and difficult to obtain for many parents. This study was designed to evaluate the efficacy of 3 ways of communicating instructions for proper car seat installation: phone conversation; HelpLightning, a mobile application (app) that offers virtual interactive presence permitting both verbal and interactive (telestration) visual communication; and the manufacturer's user manual.

Methods: A sample of 39 young adults of child-bearing age who had no previous experience installing car seats were recruited and randomly assigned to install an infant car seat using guidance from one of those 3 communication sources.

Results: Both the phone and interactive app were more effective means to facilitate accurate car seat installation compared to the user manual. There was a trend for the app to offer superior communication compared to the phone, but that difference was not significant in most assessments. The phone and app groups also installed the car seat more efficiently and perceived the communication to be more effective and their installation to be more accurate than those in the user manual group.

Conclusions: Interactive communication may help parents install car seats more accurately than using the manufacturer's manual alone. This was an initial study with a modestly sized sample; if results are replicated in future research, there may be reason to consider centralized “call centers” that provide verbal and/or interactive visual instruction from remote locations to parents installing car seats, paralleling the model of centralized Poison Control centers in the United States.     

Powered two-wheeler riders' risk of crashes associated with filtering on urban roads

Objective: The objective of this study is to estimate the crash risk per kilometer traveled by powered two-wheeler (PTW) riders filtering through traffic on urban roads.

Methods: Using the traffic injury crashes recorded by the police over a period of 3 years on 14 sections of urban roads in the city of Marseille, France, and a campaign of observations of PTWs, the crash risk per kilometer traveled by PTWs filtering was estimated and compared to the risk of PTWs that did not filter.

Results: The results show that the risk of PTW riders being involved in injury crashes while filtering is significantly higher than the risk for riders who do not filter. For the 14 sections studied, it is 3.94 times greater (95% confidence interval [CI], 2.63, 5.89). This excess risk occurred for all PTW categories. Furthermore, no space appears to be safer than the others for filtering. Riders filtering forward along the axis of the carriageway, along bus lanes, or between traffic lanes (lane-splitting) all have a crash risk greater than the risk of those who do not filter.

Conclusions: All measures limiting the practice of filtering by PTWs on urban roads would probably contribute to improving the safety of their users.     

The casualties from electric bike and motorized scooter road accidents

Objective: The objective of this study was to describe demographic and injury characteristics of hospitalized injured patients involved in e-bike and motorized scooter accidents at a national level in Israel divided by different road user groups: riders and pedestrians.

Methods: This was a retrospective study based on data from the National Trauma Registry, between January 1, 2013, and December 31, 2015. All hospitalized casualties due to the involvement of an e-bike or motorized scooter were included. The type of hospitalized road user was further categorized and described by different variables.

Results: During the study period, the Israel Trauma Registry identified 795 hospitalized patients due to an e-bike or motorized scooter accident, with a dramatic 6-fold increase from 2013 to 2015. Although the majority of the injured patients were riders, 8% were pedestrians. Among the total casualties, 33% were children aged 0–14 years and among pedestrians 42% were children and 33% were seniors (ages 60+). Five persons died in hospital, 3 riders and 2 pedestrians.

Conclusions: E-bike and motorized scooter riders represent the majority of patients hospitalized due to related traffic incident. This finding questions the social and economic advantages of electric-powered 2-wheeled vehicles.     

The effect of precrash velocity reduction on occupant response using a human body finite element model

Objective: The objective of this study is to use a validated finite element model of the human body and a certified model of an anthropomorphic test dummy (ATD) to evaluate the effect of simulated precrash braking on driver kinematics, restraint loads, body loads, and computed injury criteria in 4 commonly injured body regions.

Methods: The Global Human Body Models Consortium (GHBMC) 50th percentile male occupant (M50-O) and the Humanetics Hybrid III 50th percentile models were gravity settled in the driver position of a generic interior equipped with an advanced 3-point belt and driver airbag. Fifteen simulations per model (30 total) were conducted, including 4 scenarios at 3 severity levels: median, severe, and the U.S. New Car Assessment Program (U.S.-NCAP) and 3 extra per model with high-intensity braking. The 4 scenarios were no precollision system (no PCS), forward collision warning (FCW), FCW with prebraking assist (FCW+PBA), and FCW and PBA with autonomous precrash braking (FCW + PBA + PB). The baseline ΔV was 17, 34, and 56.4 kph for median, severe, and U.S.-NCAP scenarios, respectively, and were based on crash reconstructions from NASS/CDS. Pulses were then developed based on the assumed precrash systems equipped. Restraint properties and the generic pulse used were based on literature.

Results: In median crash severity cases, little to no risk (<10% risk for Abbreviated injury Scale [AIS] 3+) was found for all injury measures for both models. In the severe set of cases, little to no risk for AIS 3+ injury was also found for all injury measures. In NCAP cases, highest risk was typically found with No PCS and lowest with FCW + PBA + PB. In the higher intensity braking cases (1.0–1.4 g), head injury criterion (HIC), brain injury criterion (BrIC), and chest deflection injury measures increased with increased braking intensity. All other measures for these cases tended to decrease. The ATD also predicted and trended similar to the human body models predictions for both the median, severe, and NCAP cases. Forward excursion for both models decreased across median, severe, and NCAP cases and diverged from each other in cases above 1.0 g of braking intensity.

Conclusions: The addition of precrash systems simulated through reduced precrash speeds caused reductions in some injury criteria, whereas others (chest deflection, HIC, and BrIC) increased due to a modified occupant position. The human model and ATD models trended similarly in nearly all cases with greater risk indicated in the human model. These results suggest the need for integrated safety systems that have restraints that optimize the occupant's position during precrash braking and prior to impact.     

盘锦“红海滩”退化初探

本文采用海水监测、翅碱蓬野外调查及盆栽试验和室内分析方法,研究了盘锦"红海滩"翅碱蓬群落的退化死亡原因,特别是翅碱蓬退化死亡与土壤盐分的关系。结果表明,翅碱蓬适宜的土壤盐分含量在10g/kg至16g/kg之间,初步认为由于滩涂土壤盐分升高产生的盐害是引起盘锦"红海滩"翅碱蓬群落退化死亡的主要原因。     

Investigating factors affecting severity of large truck-involved crashes: Comparison of the SVM and random parameter logit model

Introduction: Reducing the severity of crashes is a top priority for safety researchers due to its impact on saving human lives. Because of safety concerns posed by large trucks and the high rate of fatal large truck-involved crashes, an exploration into large truck-involved crashes could help determine factors that are influential in crash severity. The current study focuses on large truck-involved crashes to predict influencing factors on crash injury severity. Method: Two techniques have been utilized: Random Parameter Binary Logit (RPBL) and Support Vector Machine (SVM). Models have been developed to estimate: (1) multivehicle (MV) truck-involved crashes, in which large truck drivers are at fault, (2) MV track-involved crashes, in which large truck drivers are not at fault and (3) and single-vehicle (SV) large truck crashes. Results: Fatigue and deviation to the left were found as the most important contributing factors that lead to fatal crashes when the large truck-driver is at fault. Outcomes show that there are differences among significant factors between RPBL and SVM. For instance, unsafe lane-changing was significant in all three categories in RPBL, but only SV large truck crashes in SVM. Conclusions: The outcomes showed the importance of the complementary approaches to incorporate both parametric RPBL and non-parametric SVM to identify the main contributing factors affecting the severity of large truck-involved crashes. Also, the results highlighted the importance of categorization based on the at-fault party. Practical Applications: Unrealistic schedules and expectations of trucking companies can cause excessive stress for the large truck drivers, which could leads to further neglect of their fatigue. Enacting and enforcing comprehensive regulations regarding large truck drivers’ working schedules and direct and constant surveillance by authorities would significantly decrease large truck-involved crashes.     

Behavioral pathways in bicycle-motor vehicle crashes: From contributing factors,pre-crash actions,to injury severities

Introduction: This study performed a path analysis to uncover the behavioral pathways (from contributing factors, pre-crash actions to injury severities) in bicycle-motor vehicle crashes. Method: The analysis investigated more than 7,000 bicycle-motor vehicle crashes in North Carolina between 2007 and 2014. Pre-crash actions discussed in this study are actions of cyclists and motorists prior to the event of a crash, including “bicyclist failed to yield,” “motorist failed to yield,” “bicyclist overtaking motorist,” and “motorist overtaking bicyclist.” Results: Model results show significant correlates of pre-crash actions and bicyclist injury severity. For example, young bicyclists (18 years old or younger) are 23.5% more likely to fail to yield to motor traffic prior to the event of a crash than elder bicyclists. The “bicyclist failed to yield” action is associated with increased bicyclist injury severity than other actions, as this behavior is associated with an increase of 5.88 percentage points in probability of a bicyclist being at least evidently injured. The path analysis can highlight contributing factors related to risky pre-crash actions that lead to severe injuries. For example, bicyclists traveling on regular vehicle travel lanes are found to be more likely to involve the “bicyclist failed to yield” action, which resulted in a total 44.38% (7.04% direct effect + 37.34% indirect effect) higher likelihood of evident or severe injuries. The path analysis can also identify factors (e.g., intersection) that are not directly but indirectly correlated with injury severity through pre-crash actions. Practical Applications: This study offers a methodological framework to quantify the behavioral pathways in bicycle-motor vehicle crashes. The findings are useful for cycling safety improvements from the perspective of bicyclist behavior, such as the educational program for cyclists.