Ride-hailing with kids: Who's got their back?

INTRODUCTION: As transportation network companies (TNC) are on the rise, assessing the safety of children traveling in these vehicles is imperative. For this reason, this study developed and adopted a scoring system to assess states' safety standards for children traveling in TNC vehicles. METHODS: The scoring was based on two parameters pertaining to child car seat laws for TNCs: clarity and stringency. For each parameter, three criteria that could impact child safety in TNC vehicles were formulated. If a state met a certain criterion it got 1 point and 0 otherwise. The authors gathered all the necessary information by reviewing state statutes in Nexus Uni, a legal research database. These reviews took place between December 2019 and October 2020, and this study evaluated state laws in effect on October 28, 2020. RESULTS: During this assessment, the authors observed a lack of clarity in state child car seat laws, which could compromise safety of children traveling in TNC vehicles. For clarity of laws, Georgia and Indiana received the highest scores (3 out of 3 points), while 16 states scored only 1 point, which was the lowest score in this category. In terms of stringency of laws, Pennsylvania received the highest score (3 out of 3 points), while Indiana scored the least (0 points). CONCLUSIONS: Besides one state (Oregon), all other states defined TNCs in their state laws. All states except for Indiana and Washington required child car seats in TNC vehicles. The responsibility for child car seat use was clearly defined in 35 states. The fine for child car seat violation was $50 or more in 28 states. Practical Application: This study will help TNCs, policymakers, and stakeholders identify states that need to improve their standards for child safety in TNC vehicles, and comprehensively address the issue.

COVID-19 effects on shared-biking in New York, Boston, and Chicago.

Coronavirus has had a large-scale impact on transportation. This study attempts to assess the effects of COVID-19 on biking. Bikeshare data was used to understand the impacts of COVID-19 during the initial wave of the disease on biking in New York City, Boston, and Chicago. As the cases increased, these cities experienced a reduction in bikeshare trips, and the reductions were different in the three cities. Correlations were developed between COVID-19 cases and various bikeshare related variables. The study period was split into three phases-no COVID-19 phase, cases increasing phase, and cases decreasing phase-to examine how the residents of the three cities reacted during the different phases of the coronavirus spread. While bike trips decreased, the average duration of the trips increased during the pandemic. NYC's average trip duration was consistently less than that of Boston and Chicago, which could be due to its sprawl (NYC is considered as more compact and connected compared to the other two cities).

Do NHTSA vehicle safety ratings affect side impact crash outcomes?

INTRODUCTION: Side impact crash injuries tend to be severe, mainly due to the effects of the mechanism of such crashes. This study addresses the relationship between side impact crash injury severities and side impact safety ratings of the passenger cars involved in such crashes. It is motivated by the lack of research on side impact safety ratings in relation to the real-world crash outcomes. METHOD: Analysis of Crashworthiness Data System's (CDS) data show the head and thorax are the most common regions of impact of severe injuries, while the neck is the least. Irrespective of body regions, higher-rated vehicles were found to provide better occupant protection to both younger and older driver age groups. Assessment based on injury severity score (ISS) indicates that higher-rated vehicles have an overall lower average ISS compared to lower-rated vehicles. RESULTS: Ultimately, this study shows that vehicles rated with National Highway Traffic Safety Administration's (NHTSA) new criteria had lower average ISS compared to vehicles rated under the old criteria. The 2011 NHTSA side impact rating criteria being relatively new, it has very few crashes to draw meaningful statistically significant conclusions. However, this paper establishes the fact that vehicles with higher star ratings (under experimental conditions) indeed offer increased occupant protection in the field conditions. Practical applications: Previous studies have found that safety was given priority while buying new vehicles. However, people associated vehicle safety with technologies and specific safety features rather than the vehicle's crash test results or ratings (Koppel, Charlton, Fildes, & Fitzharris, 2008). The results from this study provide a point of reference for safety advocates to educate the drivers about the importance of considering vehicle safety ratings during a vehicle purchase.

Modeling and comparing injury severity of at-fault and not at-fault drivers in crashes.

This paper examines and compares the effect of selected variables on driver injury severity of, both, at-fault and not at-fault drivers. Data from the Highway Safety Information System (HSIS) for the state of North Carolina was used for analysis and modeling. A partial proportional odds model was developed to examine the effect of each variable on injury severity of at-fault driver and not at-fault driver, and, to examine how each variable affects these two drivers' injury severity differently. Road characteristics, weather condition, and geometric characteristics were observed to have a similar effect on injury severity in a crash to at-fault and not at-fault drivers. Age of the driver, physical condition, gender, vehicle type, and, the number and type of traffic rule violations were observed to play a significant role in the injury severity of not at-fault drivers when compared to at-fault drivers in the crash. Moreover, motorcyclists and drivers 70 years or older are observed to be the most vulnerable road users.

Modeling crash injury severity by road feature to improve safety.

OBJECTIVE: The objective of this research is 2-fold: to (a) model and identify critical road features (or locations) based on crash injury severity and compare it with crash frequency and (b) model and identify drivers who are more likely to contribute to crashes by road feature. METHOD: Crash data from 2011 to 2013 were obtained from the Highway Safety Information System (HSIS) for the state of North Carolina. Twenty-three different road features were considered, analyzed, and compared with each other as well as no road feature. A multinomial logit (MNL) model was developed and odds ratios were estimated to investigate the effect of road features on crash injury severity. RESULTS: Among the many road features, underpass, end or beginning of a divided highway, and on-ramp terminal on crossroad are the top 3 critical road features. Intersection crashes are frequent but are not highly likely to result in severe injuries compared to critical road features. Roundabouts are least likely to result in both severe and moderate injuries. Female drivers are more likely to be involved in crashes at intersections (4-way and T) compared to male drivers. Adult drivers are more likely to be involved in crashes at underpasses. Older drivers are 1.6 times more likely to be involved in a crash at the end or beginning of a divided highway. CONCLUSIONS: The findings from this research help to identify critical road features that need to be given priority. As an example, additional advanced warning signs and providing enlarged or highly retroreflective signs that grab the attention of older drivers may help in making locations such as end or beginning of a divided highway much safer. Educating drivers about the necessary skill sets required at critical road features in addition to engineering solutions may further help them adopt safe driving behaviors on the road.

Methods to rank traffic rule violations resulting in crashes for allocation of funds.

Education, enforcement and engineering countermeasures are implemented to make road users comply with the traffic rules. Not all the traffic rule violations can be addressed nor countermeasures be implemented at all unsafe locations, at once, due to limited funds. Therefore, this study aims at ranking the traffic rule violations resulting in crashes based on individual ranks, such as 1) frequency (expressed as a function of the number of drivers violating a traffic rule and involved in crashes), 2) crash severity, 3) total crash cost, and, 4) cost severity index, to assist transportation system managers in prioritizing the allocation of funds and improving safety on roads. Crash data gathered for the state of North Carolina was processed and used in this study. Variations in the ranks of traffic rule violations were observed when individual ranking methods are used. As an example, exceeding authorized speed limit and driving under the influence of alcohol are ranked 1st and 2nd based on crash severity while failure to reduce speed and failure to yield the right-of-way are ranked 1st and 2nd based on frequency. To minimize the variations and capture the merits of individual ranking methods, four different composite ranks were computed by combining selected individual ranks. The computed averages and standard deviations of absolute rank differences between composite ranks is lower than those obtained from individual ranks. The weights to combine the selected individual ranks have a marginal effect on the computed averages and standard deviations of absolute rank differences. Combining frequency and crash severity or cost severity index, using equal weights, is recommended for prioritization and allocation of funds.

Risk drivers pose to themselves and other drivers by violating traffic rules.

OBJECTIVE: Violation of traffic rules is a major contributing factor in both crashes and fatalities in the United States. This study aims at quantifying risk that drivers pose to themselves and other drivers by violating traffic rules. METHOD: Crash data from 2010 to 2013 were gathered for the state of North Carolina. Descriptive analysis was carried out to identify frequent traffic violations and who were committing the traffic violations that resulted in crashes. A multinomial logit model was then developed to examine the relation between different traffic violations and driver injury severity. Additionally, odds ratios were estimated to identify the likelihood (probability) of severe or moderate injury to the driver and other drivers due to a driver violating a traffic rule that led to a crash. RESULTS: Exceeding the speed limit is more likely to result in severe injury compared to disregarding traffic signals. However, going the wrong way is more likely to result in severe injury to other drivers when compared to any other traffic violation. Driving under the influence of alcohol is 2 times more likely to result in severe injury than driving under the influence of drugs. These 2 traffic violations by a driver are almost equally likely to result in severe injury to other drivers. CONCLUSIONS: Drivers often perceive that violating traffic rules will not result in a crash or severe injury. However, the results from this study show that a majority of the traffic violations lead to severe injury to the violator as well as to other drivers. The findings from this study serve as documented evidence to educate drivers about the risk they pose to themselves and to other drivers by violating traffic rules and encourage the adaptation of safe driving behavior in order to contribute toward reaching the "zero traffic deaths" vision. They also help make policy changes pertaining to penalty points and fines for violating a traffic rule.