Severity of motorcycle crashes in Dar es Salaam,Tanzania

Objective: Motorcycles are a common mode of transportation in low- and middle-income countries. Tanzania, in particular, has experienced an increased use of motorcycles in the last decade. In Dar es Salaam, motorcycles provide door-to-door travel and often operate where more conventional services are uneconomical or physically impossible to maneuver. Although motorcycles play a crucial role in improving mobility in the city, they have several safety issues. This study focuses on identifying factors influencing the severity of motorcycle crashes.

Method: A multinomial logit analysis was conducted to identify factors influencing the severity of motorcycle crashes in Dar es Salaam, Tanzania. The severity categories were fatal, severe injury, minor injury, and property damage only (PDO). The analysis was based on a total of 784 motorcycle crashes that occurred from 2013 to 2016.

Results: The following factors were found to increase the probability of a fatality: Speeding, driving under the influence, head-on impact, presence of horizontal curves, reckless riding, off-peak hours, violations, and riding without a helmet. The results indicate that crashes occurring on weekdays, during peak hours, at intersections, involving a rear-end impact, in daylight, on street roads, and under clear weather conditions decrease the probability of a fatality. However, minor injury and PDO crashes were found to be associated with crashes occurring during peak hours, at intersections, and on street roads, as well as failure to yield right-of-way.

Conclusions: Several countermeasures are recommended based on the study findings. The recommended countermeasures focus on the holistic safety improvement strategies constituting the three Es of highway safety, namely, engineering, education, and enforcement.     

Severity models of cross-median and rollover crashes on rural divided highways in Pennsylvania

Introduction

Crossover and rollover crashes in earth-divided, traversable medians on rural divided highways can lead to severe injury outcomes. This study estimated severity models of these two crash types. Vehicle, driver, roadway, and median cross-section design data were factors considered in the models. A unique aspect of the data used to estimate the models were the availability of median cross-slope data, which are not commonly included in roadway inventory data files.

Methods

A binary logit model of cross-median crash severity and a multinomial logit model of rollover crash severity were estimated using five years of data from rural divided highways in Pennsylvania.

Results

The highest probability of a fatal or major injury in cross-median and rollover crashes was found to occur in cases when a driver was not wearing a seatbelt. While flatter cross-slopes and narrower medians were associated with more severe cross-median crash outcomes, steeper cross-slopes and narrower medians significantly increased rollover crash severity outcomes. The presence of horizontal curves was associated with increased probabilities of high-severity outcomes in a median rollover crash.

Impact on Industry

Modeling results in this study confirmed that cross-median and median rollover crash severity outcomes are associated with median cross-section design characteristics. Based on the estimated models, it appears that flatter and narrower medians lead to more severe injury outcomes in cross-median crashes. Steeper median cross-slopes and narrower medians were associated with higher probabilities of more severe outcomes in median rollover crashes. The results presented in this study suggest that there is a trade-off between median cross-section design and cross-median and rollover crashes in earth-divided, traversable medians on rural divided highways. While the severity models can be included in a framework to develop design guidance in relation to this trade-off, models of crash frequency should also be considered.     

Does time of day matter at highway work zone crashes?

Introduction: It is widely agreed that highway work zones pose significant threats to road users because driving conditions in work zones are quite different from the normal ones, particularly when traffic volumes approach a highway capacity. Therefore, work zone safety is a critical aspect for state agencies and traffic engineers. Method: In the current study, a total of 10,218 crashes that occurred in highway work zones in the state of Washington for the period between 2007 and 2013 were used. Time of day is disaggregated into four subgroups: (1) Morning from 6:00 to 11:00 a.m. (2) Midday from 12:00 to 5:00 p.m. (3) Night from 6:00 to 11:00 p.m., and (4) Late night from 12:00 to 5:00 a.m. Then, four mixed logit models were estimated to account and correct for heterogeneity in the crash data by considering three injury severity levels: severe injury, minor injury, and no injury. Results: The estimation results reveal that most contributing factors are uniquely significant in a specific time of day period, whereas three factors affect injury severity regardless of time of day such as the indicators of not deployed airbag, one passenger vehicle involved in the crash, and rear-end collision. Further, some factors were found to affect injury severity into two or three time periods, such as female drivers that found to decrease the probability of no injury in morning and night time periods, while increasing severe injury outcome in midday time. Conclusions: The effect of time of day on injury severity of work-zone related crashes should be modeled separately rather than using a holistic model. Practical applications: As a starting point, findings of the current study can be used by transportation officials to reduce fatalities and injuries of work zone crashes by identifying factors that uniquely contribute to each time of day period.     

The effect of motorcyclists’ age on injury severities in single-motorcycle crashes with unobserved heterogeneity

Introduction: Due to the myriad of unique characteristics associated with motorcycle operation, motorcycle safety is a public health concern as complex as it is serious. National crash data suggest motorcyclists are 28 times more likely to be killed when compared to passenger car occupants. In the state of Florida, motorcycle crashes are 1.5 times more likely to result in the death of the rider, placing Florida among the top deadliest states for motorcyclists in the nation. Using police-reported data from 2016, this study addresses the complex and interconnected nature of the many characteristics associated with motorcycle operation by investigating the effect of age on motorcyclists’ riding behavior as it relates to injury severity for single-motorcycle crashes in the state of Florida. Method: To account for unobserved heterogeneity in the crash data, mixed logit models with heterogeneity in means and variances were estimated to model three injury severity outcomes (non-visible, severe, and fatal) for three age groups (under 30, 30–49, and 50 and above). Results: Model results indicate that age affects motorcyclists’ safety perception and ability to assess risks, thereby influencing their involvement in risky behaviors. Characteristics unique to motorcycle operation—spatial characteristics, speed, motorcycle type, time of day, helmet usage, alcohol consumption, ejection from motorcycle, passenger presence, endorsement status, and lighting—are further complicated by their dependency on the characteristics of the individual motorcyclist. Age of motorcyclist indicates a relationship between motorcyclists’ behavior and perceived safety. Conclusion: The model results indicated that statistically significant parameters constituted different models and they were not equal across the age groups of motorcyclists: aged under 30, aged 30–49, and aged 50 and above. Through advanced econometric modeling, this study fills a gap in the existing literature and assists the safety professionals, motorcycle trainers, policymakers, law enforcement agencies, and roadway designers in developing countermeasures.     

A multinomial logit analysis of factors associated with severity of motorcycle crashes in Ghana

Objective: The objective of this study was to explore the factors affecting motorcycle crash severity in Ghana.

Methods: A retrospective analysis of motorcycle crash data between 2011 and 2015 was conducted using a motorcycle crash data set extracted from the National Road Traffic Crash Database at the Building and Road Research Institute (BRRI) in Ghana. Injury severity was classified into 4 categories: Fatal, hospitalized, injured, and damage only. A multinomial logit modeling framework was used to identify the possible determinants of motorcycle crash severity.

Results: During the study period, a total of 8,516 motorcycle crashes were recorded, of which 22.9% were classified as fatal, 42.1% were classified as hospitalized injuries, 29.4% were classified as slight injuries, and 5.6% were classified as damage-only crashes. The estimation results indicate that the following factors increase the probability of fatal injuries: At a junction; weekend; signage; poor road shoulder; village settlement; tarred and good road surface; and collision between motorcycle and heavy goods vehicle (HGV). Motorcycle crashes occurring during the daytime and on the weekend increases the probability of hospitalized injury. The results also suggest that motorcycle crashes occurring during the daytime, in curves or inclined portions of roads, or in unclear weather conditions decrease the probability of fatal injury.

Conclusions: This study provides further empirical evidence to support motorcycle crash modeling research, which is lacking in developing countries. The ability to understand the various factors that influence motorcycle crash severity is a step forward in providing an appropriate basis upon which informed motorcycle crash policies can be developed. Particular attention should be given to the provision of road signage at junctions and speed humps and controlling traffic during the weekend. In addition, road maintenance should be carried out periodically to address motorcycle safety in Ghana.     

Using latent class clustering and binary logistic regression to model Australian cyclist injury severity in motor vehicle–bicycle crashes

Introduction: In recent years, Australia is seeing an increase in the total number of cyclists. However, the rise of serious injuries and fatalities to cyclists has been a major concern. Understanding the factors affecting the fatalities and injuries of bicyclists in crashes with motor vehicles is important to develop effective policy measures aimed at improving the safety of bicyclists. This study aims to identify the factors affecting motor vehicle-bicycle (MVB) crashes in Victoria, Australia and introducing effective countermeasures for the identified risk factors. Method: A data set of 14,759 MVB crash records from Victoria, Australia between 2006 and 2019 was analyzed using the binary logit model and latent class clustering. Results: It was observed that the factors that increase the risk of fatalities and serious injuries of bicyclists (FSI) in all clusters are: elderly bicyclist, not using a helmet, and darkness condition. Likewise, in areas with no traffic control, clear weather, and dry surface condition (cluster 1), high speed limits increase the risk of FSI, but the occurrence of MVB crashes in cross intersection and T-intersection has been significantly associated with a reduction in the risk of FSI. In areas with traffic control and unfavorable weather conditions (cluster 2), wet road surface increases the risk of FSI, but the areas with give way sign and pedestrian crossing signs reduce the risk of FSI. Practical Applications: Recommendations to reduce the risk of fatalities or serious injury to bicyclists are: improvement of road lighting and more exposure of bicyclists using reflective clothing and reflectors, separation of the bicycle and vehicle path in mid blocks especially in high-speed areas, using a more stable bicycle for the older people, monitoring helmet use, improving autonomous emergency braking, and using bicyclist detection technology for vehicles.     

Views of US drivers about driving safety

Problem: To assess how drivers view dangers on the highway, what motivates them to drive safely, how they say they reduce their crash and injury risk, and how they rate their own driving skills. Results: Most drivers rated their skills as better than average. The biggest motivating factor for safe driving was concern for safety of others in their vehicle, followed by negative outcomes such as being in a crash, increased insurance costs, and fines. The greatest threats to their safety were thought to be other drivers' actions that increase crash risk such as alcohol impairment or running red lights. In terms of reducing crashes and injuries, drivers tended to focus on actions they could take such as driving defensively or using seat belts. There was less recognition of the role of vehicles and vehicle features in crash or injury prevention. Impact on research, practice, and policy: Knowing how drivers view themselves and others, their concerns, and their motivations and techniques for staying out of trouble on the roads provides insight into the difficulty of changing driving practices.     

Some determinants of possible injuries in crashes at signalized intersections

INTRODUCTION: This paper identifies some determinants of possible injuries from crashes that occur at signalized intersections using a conditional probability model. METHOD: It uses longitudinal data for one city and calculates the marginal effects of these determinants. RESULTS: Among its findings, an airbag deploying in a crash reduces the conditional probability of sustaining possible injury. The size of this decrease is similar for the front airbag or both side airbags deploying. When crashes occur because a driver suddenly falls ill, or because a driver has an existing medical condition that flares up, the results show that the conditional probability of sustaining possible injury increases by 0.1414 and 0.1217, respectively. In comparison the conditional probability of sustaining possible injury increases by 0.0706 when the crash is because of impairment from drugs or alcohol. Additionally, the probability of sustaining possible injury in the event of a crash is 0.0435 and 0.0459 higher in passenger cars and vans respectively than in other vehicles. CONCLUSIONS: Comparing these results to those in the traffic safety literature, the marginal effects from national data are similar to those from local level data.     

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.     

Risk factors affecting the severity of traffic accidents at Shanghai river-crossing tunnel

Objective: With increasing traffic volume and urban development, increasing numbers of underground tunnels have been constructed to relieve conflict between strained land and heavy traffic. However, as more long tunnels are constructed, tunnel traffic safety is becoming increasingly serious. Thus, it is necessary to acquire their implications and impacts. This study examined 4,539 traffic accidents that have occurred in 14 Shanghai river-crossing tunnels for the period 2011–2012 and analyze the correlation between potential factors and accident injury severity.

Methods: An ordered logit model was developed to examine the correlation between potential factors and accident injury severity.

Results: Results show that increased injury severity is associated with male drivers, drivers aged 65 years or older, accident time from midnight to dawn, weekends, wet road surface, goods vehicles, 3 or more vehicles, 4 or more lanes, middle speed limits (50–79 km/h), zone 3, extra-long tunnels (over 3,000 m), and maximum longitudinal gradient.

Conclusions: This article aims to provide useful information for engineers to develop interventions and countermeasures to improve tunnel safety in China.     

Modeling faults among e-bike-related fatal crashes in China

Objectives: This article aims to model fault in e-bike fatal crashes in a county-level city in China.

Method: Three-year crash data are retrieved from the crash reports (2012–2014) from the Taixing Police Department. A mixed logit model is introduced to explore significant factors associated with fault assignment, as well as accounting for similarity among fault assignment and heterogeneity within unobserved variables.

Results: The modeling results indicate some interesting new findings. First, precrash behaviors of both drivers and e-bike riders are found to be significant to fault assignment. Second, bike lane and median type are significantly associated with e-bike rider fault commitment. Third, specific groups of e-bike riders (low-educated and older) and drivers (heavy good vehicles) are more likely to be at fault in e-bike crashes. Last, crash location and the built environment have significant correlations with faulty behaviors of e-bike riders.

Conclusions: Safety countermeasures are proposed including (1) the deployment of traffic design and control elements including physically separated bike lanes, medians, video surveillance systems for e-bike riders, and left-turning treatments for nonmotorists (e.g., a 2-step e-bike left turning); (2) the amendment of the current traffic regulations on drunk e-bike riders and child e-bike passengers; (3) the development of a license system for specific e-bike rider groups (older and low-educated) and a safety campaign for drivers (to increase safety awareness when parking on-street or driving heavy good vehicles). Some interesting future research topics are also suggested: e-bike riders' behaviors at unsignalized intersections and mid-block openings, e-bike safety in suburban areas, and an in-depth study of the effect of the built environment on e-bike safety.