Corridor-level signalized intersection safety analysis in Shanghai,China using Bayesian hierarchical models

Most traffic crashes in Chinese cities occur at signalized intersections. Research on the intersection safety problem in China is still in its early stage. The recent development of an advanced traffic information system in Shanghai enables in-depth intersection safety analyses using road design, traffic operation, and crash data. In Shanghai, the road network density is relatively high and the distance between signalized intersections is small, averaging about 200 m. Adjacent signalized intersections located along the same corridor share similar traffic flows, and signals are usually coordinated. Therefore, when studying intersection safety in Shanghai, it is essential to account for intersection correlations within corridors. In this study, data for 195 signalized intersections along 22 corridors in the urban areas of Shanghai were collected. Mean speeds and speed variances of corridors were acquired from taxis equipped with Global Positioning Systems (GPS). Bayesian hierarchical models were applied to identify crash risk factors at both the intersection and the corridor levels. Results showed that intersections along corridors with lower mean speeds were associated with fewer crashes than those with higher speeds, and those intersections along two-way roads, under elevated roads, and in close proximity to each other, tended to have higher crash frequencies.     

Modeling left-turn crash occurrence at signalized intersections by conflicting patterns

In order to better understand the underlying crash mechanisms, left-turn crashes occurring at 197 four-legged signalized intersections over 6 years were classified into nine patterns based on vehicle maneuvers and then were assigned to intersection approaches. Crash frequency of each pattern was modeled at the approach level by mainly using Generalized Estimating Equations (GEE) with the Negative Binomial as the link function to account for the correlation among the crash data. GEE with a binomial logit link function was also applied for patterns with fewer crashes. The Cumulative Residuals test shows that, for correlated left-turn crashes, GEE models usually outperformed basic Negative Binomial models. The estimation results show that there are obvious differences in the factors that cause the occurrence of different left-turn collision patterns. For example, for each pattern, the traffic flows to which the colliding vehicles belong are identified to be significant. The width of the crossing distance (represented by the number of through lanes on the opposing approach of the left-turning traffic) is associated with more left-turn traffic colliding with opposing through traffic (Pattern 5), but with less left-turning traffic colliding with near-side crossing through traffic (Pattern 8). The safety effectiveness of the left-turning signal is not consistent for different crash patterns; "protected" phasing is correlated with fewer Pattern 5 crashes, but with more Pattern 8 crashes. The study indicates that in order to develop efficient countermeasures for left-turn crashes and improve safety at signalized intersections, left-turn crashes should be considered in different patterns.     

Turning-lane and signal optimization at intersections with multiple objectives

Traffic congestion at intersections is a serious problem in cities. In order to discharge turning vehicles efficiently at intersections to relieve traffic jams, multiple left-turn and right-turn lanes are often used. This article proposes a novel multi-objective optimization method for signal setting and multiple turning-lane assignment at intersections based on microscopic traffic simulations and a cell-mapping method. Vehicle conflicts and pedestrian interference are considered. The intersection multi-objective optimization problem (MOP) is formulated. The cell-mapping method is adopted to solve the MOP. Three measures of traffic performance are studied including transportation efficiency, energy consumption and road safety. The influence of turning-lane assignment on intersection performance is investigated in the optimization. Significant impacts of the number of turning lanes on the traffic are observed. An algorithm is proposed to assist traffic engineers to select and implement the optimal designs. In general, more turning lanes help increase turning traffic efficiency and lower fuel consumption in most cases. Remarkable improvement in traffic performance can be achieved with combined optimization of lane assignment and signal setting, which cannot be obtained with signal setting optimization alone. The studies reported in this article provide general guidance for intersection planning and operation. The proposed optimization methodology represents a promising emerging technology for traffic applications.     

The influence of road curvature on fatal crashes in New Zealand

Bends in roads can cause crashes but a recent study in the UK found that areas with mostly curved roads had lower crash rates than areas with straighter roads. This present study aimed to replicate the previous research in a different country. Variations in the number of fatal road crashes occurring between 1996 and 2005 in 73 territorial local authorities across New Zealand were modelled against possible predictors. The predictors were traffic flow, population counts and characteristics, car use, socio-economic deprivation, climate, altitude and road characteristics including four measures of average road curvature. The best predictors of the number of fatal crashes on urban roads, rural state highways and other rural roads were traffic flow, speed limitation and socio-economic deprivation. Holding significant factors constant, there was no evidence that TLAs with the most curved roads had more crashes than elsewhere. Fatal crashes on urban roads were significantly and negatively related to two measures of road curvature: the ratio of road length to straight distance and the cumulative angle turned per kilometre. Weaker negative associations on rural state highways could have occurred by chance. These results offer limited support to the suggestion that frequently occurring road bends might be protective.     

What can we learn about North Dakota's youngest drivers from their crashes?

For North Dakota teens, three of every four deaths are from motor vehicle crashes. Injury crash records for teen drivers were studied to gain insight regarding driver, vehicle, and road factors for public safety policy and program discussions. Results show 14-year-old drivers are three times more likely to die or be disabled in an injury crash than 17-year-old drivers, and that male drivers are 30% less likely to incur severe injury. As expected, seat belt use is a critical factor in severe injury avoidance. The likelihood for death or disablement is 165% greater for unbelted teen drivers than for those who are properly belted. In addition, rural and gravel roads pose a risk. Teens are six times more likely to be severely injured in crashes on rural roads than on urban roads. Findings suggest that an increased licensing age and seat belt emphasis may reduce teen traffic injuries in the state. In addition, more information on exposure should be attained to better understand rural and gravel road as risks.     

Use of speed profile as surrogate measure: Effect of traffic calming devices on crosstown road safety performance

Urban road safety management is usually characterized by the lack of sufficient, good quality crash data and low budgets to obtain it even though many traffic accidents occur there. For example, 54 percent of road crashes in Spain take place in urban areas, and 10 percent of urban fatal crashes occur on crosstown roads, which are rural roads that traverse small communities. Traffic calming measures (TCMs) are often implemented on these parts of rural roads that traverse small communities in order to reduce both the frequency and severity of crashes by lowering speeds, but evaluation of their effectiveness has been limited. The objective of this study was to develop a methodology using continuous speed profiles to evaluate the safety effectiveness of TCMs on crosstown roads as part of an integrated system in the absence of historical data. Given the strong relationship between speed and crash experience, safety performance can be related to speed. Consequently, speed can be used indirectly as a surrogate safety measure in the absence of crash and speed data.     

Factors associated with civilian drivers involved in crashes with emergency vehicles

Motor vehicle crashes involving civilian and emergency vehicles (EVs) have been a known problem that contributes to fatal and nonfatal injuries; however, characteristics associated with civilian drivers have not been examined adequately. This study used data from The National Highway Traffic Safety Administration's Fatality Analysis Reporting System and the National Automotive Sampling System General Estimates System to identify driver, roadway, environmental, and crash factors, and consequences for civilian drivers involved in fatal and nonfatal crashes with in-use and in-transport EVs. In general, drivers involved in emergency–civilian crashes (ECCs) were more often driving: straight through intersections (vs. same direction) of four-points or more (vs. not at intersection); where traffic signals were present (vs. no traffic control device); and at night (vs. midday). For nonfatal ECCs, drivers were more often driving: distracted (vs. not distracted); with vision obstructed by external objects (vs. no obstruction); on dark but lighted roads (vs. daylight); and in opposite directions (vs. same directions) of the EVs. Consequences included increased risk of injury (vs. no injury) and receiving traffic violations (vs. no violation). Fatal ECCs were associated with driving on urban roads (vs. rural), although these types of crashes were less likely to occur on dark roads (vs. daylight). The findings of this study suggest drivers may have difficulties in visually detecting EVs in different environments.     

The significance of endogeneity problems in crash models: an examination of left-turn lanes in intersection crash models

Crash prediction models are used for a variety of purposes including forecasting the expected future performance of various transportation system segments with similar traits. The influence of intersection features on safety have been examined extensively because intersections experience a relatively large proportion of motor vehicle conflicts and crashes compared to other segments in the transportation system.

The effects of left-turn lanes at intersections in particular have seen mixed results in the literature. Some researchers have found that left-turn lanes are beneficial to safety while others have reported detrimental effects on safety. This inconsistency is not surprising given that the installation of left-turn lanes is often endogenous, that is, influenced by crash counts and/or traffic volumes. Endogeneity creates problems in econometric and statistical models and is likely to account for the inconsistencies reported in the literature.

This paper reports on a limited-information maximum likelihood (LIML) estimation approach to compensate for endogeneity between left-turn lane presence and angle crashes. The effects of endogeneity are mitigated using the approach, revealing the unbiased effect of left-turn lanes on crash frequency for a dataset of Georgia intersections. The research shows that without accounting for endogeneity, left-turn lanes ‘appear’ to contribute to crashes; however, when endogeneity is accounted for in the model, left-turn lanes reduce angle crash frequencies as expected by engineering judgment. Other endogenous variables may lurk in crash models as well, suggesting that the method may be used to correct simultaneity problems with other variables and in other transportation modeling contexts.     

Survival hazards of road environment factors between motor-vehicles and motorcycles

Motorcycles are frequently used in middle- and low-income societies. They are often involved in crashes, and account for a noticeable percentage of fatalities secondary to crashes. Comparing motor-vehicle occupants and motorcycle riders, the present study examined the survival hazard of crash injuries with respect to road environmental factors (i.e., area, road type, and location). We investigated the effects of such factors on survival and survival time after crashes via a binary logistic regression analysis and a Cox proportional hazard regression analysis, respectively. Results indicated that, for both motor-vehicle occupants and motorcycle riders, the fatal prevalence, occurrence likelihood, and risk based on time were decreased in urban areas and elevated on highways. The three indexes were also higher for motor-vehicle occupants on non-straight or non-level roadway sections. The prevalence of death on local roads and at intersections was relatively higher for motorcycle riders compared to motor-vehicle occupants. Speed may contribute to the survival hazard with respect to road environment factors. Speed management initiatives account for hazardous roadway, curve alignment re-examination, and increased traffic enforcement density are suggested. Collaboration among the roadway authorities, vehicle industry, and medical systems for a timely rescue is also advised. In addition, the attention to crashes at intersections and on local roads is a promising intervention for motorcycle riders.     

Exploring the impacts of factors contributing to tram-involved serious injury crashes on Melbourne tram routes

Previous research is limited regarding factors influencing tram-involved serious injury crashes. The aim of this study is to identify key vehicle, road, environment and driver related factors associated with tram-involved serious injury crashes. Using a binary logistic regression modelling approach, the following factors were identified to be significant in influencing tram-involved fatal crashes in Melbourne: tram floor height, tram age, season, traffic volume, tram lane priority and tram travel speed. Low floor trams, older trams, tram priority lanes and higher tram travelling speeds are more likely to increase tram-involved fatal crashes. Higher traffic volume decreases the likelihood of serious crashes. Fatal crashes are more likely to occur during spring and summer. Findings from this study may offer ideas for future research in the area of tram safety and help to develop countermeasures to prevent specific fatality types from occurring.     

Applying Bayesian hierarchical models to examine motorcycle crashes at signalized intersections

Motorcycles are overrepresented in road traffic crashes and particularly vulnerable at signalized intersections. The objective of this study is to identify causal factors affecting the motorcycle crashes at both four-legged and T signalized intersections. Treating the data in time-series cross-section panels, this study explores different Hierarchical Poisson models and found that the model allowing autoregressive lag-1 dependence specification in the error term is the most suitable. Results show that the number of lanes at the four-legged signalized intersections significantly increases motorcycle crashes largely because of the higher exposure resulting from higher motorcycle accumulation at the stop line. Furthermore, the presence of a wide median and an uncontrolled left-turn lane at major roadways of four-legged intersections exacerbate this potential hazard. For T signalized intersections, the presence of exclusive right-turn lane at both major and minor roadways and an uncontrolled left-turn lane at major roadways increases motorcycle crashes. Motorcycle crashes increase on high-speed roadways because they are more vulnerable and less likely to react in time during conflicts. The presence of red light cameras reduces motorcycle crashes significantly for both four-legged and T intersections. With the red light camera, motorcycles are less exposed to conflicts because it is observed that they are more disciplined in queuing at the stop line and less likely to jump start at the start of green.     

Making minor rural road networks safer: The effects of 60 km/h-zones

For safety reasons a maximum speed limit of 60 km/h has been applied to minor rural roads in the Netherlands since 1998. To support this structurally, a part of these roads have also received additional physical measures in a so-called “low cost design” that is expected to reduce the number of traffic casualties by 10–20%. This measure has been implemented as much as possible in an area oriented way. To measure the design's effectivity, road safety in 20 specific rural areas was studied for 5 years before changes were implemented and, on average, 3.5 years thereafter. The study examined 851 km of roads, and a control study was done on 2105 km of comparable roads with a speed limit of 80 km/h. Both the study and the control roads are managed by water boards. Results show that the measures implemented on the roads in the 60 km/h-zones had statistically significant effects (p < 0.05) on casualty accidents (−24% overall), especially at intersections (−44%). This high reduction is probably caused by the concentration of technical interventions at intersections. Both outcomes are somewhat higher than previously expected and are comparable with the outcome of a meta-analysis of safety effects on area-wide urban traffic calming schemes. However, the cost-effectiveness ratio of the 60 km/h zones measures (€33,000 per prevented KSI-casualty) is much more favourable than the ratio in urban 30 km/h-zones (€86,000 per prevented KSI-casualty).     

Identification of differences between rural and urban safety cultures

The prevailing risk of traffic fatalities is much larger in rural areas compared to urban areas. A number of explanations have been offered to explain this including road design, emergency medical service proximity, and human factors. This research explored the potential contribution of rural driver attitudes that may underlie the increased fatal crash risk in rural environments. This analysis examined differences between rural and urban drivers in terms of self-reported risk taking for driving behaviors associated with fatal crashes and attitudes toward safety interventions using a large-scale survey. The results suggested that rural drivers engage in riskier behavior, such as not wearing seatbelts, because they have lower perceptions of the risks associated with such behaviors. Results also suggested that vehicle type (e.g., pickup trucks versus passenger vehicles) may be related to seatbelt compliance and frequency of driving under the influence of alcohol. Rural drivers perceived the utility of government-sponsored traffic safety interventions to be lower than their urban counterparts. This study provides insights into the role of the human factor in rural fatal crashes and provides policy suggestions for developing safety interventions that are designed with respect to the psychosocial factors that define the rural culture.     

An examination of the environmental,driver and vehicle factors associated with the serious and fatal crashes of older rural drivers

Motor vehicle crashes involving rural drivers aged 75 years and over are more than twice as likely to result in a serious or fatal injury as those involving their urban counterparts. The current study examined some of the reasons for this using a database of police-reported crashes (2004–2008) to identify the environmental (lighting, road and weather conditions, road layout, road surface, speed limit), driver (driver error, crash type), and vehicle (vehicle age) factors that are associated with the crashes of older rural drivers. It also determined whether these same factors are associated with an increased likelihood of serious or fatal injury in younger drivers for whom frailty does not contribute to the resulting injury severity. A number of environmental (i.e., undivided, unsealed, curved and inclined roads, and areas with a speed limit of 100 km/h or greater) and driver (i.e., collision with a fixed object and rolling over) factors were more frequent in the crashes of older rural drivers and additionally associated with increased injury severity in younger drivers. Moreover, when these environmental factors were entered into a logistic regression model to predict whether older drivers who were involved in crashes did or did not sustain a serious or fatal injury, it was found that each factor independently increased the likelihood of a serious or fatal injury. Changes, such as the provision of divided and sealed roads, greater protection from fixed roadside objects, and reduced speed limits, appear to be indicated in order to improve the safety of the rural driving environment for drivers of all ages. Additionally, older rural drivers should be encouraged to reduce their exposure to these risky circumstances.     

Traffic signal phasing at intersections to improve safety for alcohol-affected pedestrians

Alcohol-affected pedestrians are among the highest-risk groups involved in pedestrian casualty crashes. This paper investigates the opportunities to use a modified form of traffic signal operation during high-risk periods and at high-risk locations to reduce alcohol-affected pedestrian crashes and the severity of injuries that might otherwise occur. The 'Dwell-on-Red' treatment involves displaying a red traffic signal to all vehicle directions during periods when no vehicular traffic is detected, so that drivers approach high-risk intersections at a lower speed than if a green signal were displayed. Vehicle speed data were collected before and after treatment activation at both a control and treatment site. Speed data were collected both 30 m prior to and at the intersection stop line. The treatment was associated with a reduction in mean vehicle speeds of 3.9 kph (9%) and 11.0 kph (28%) at 30 m and stop line collection points, respectively, and substantial reductions in the proportion of vehicles travelling at threatening speeds with regard to the severity of pedestrian injury. Other important road safety concerns may also benefit from this form of traffic signal modification, and it is recommended that other areas of application be explored, including the other severe trauma categories typically concentrated around signalised intersections.     

Multilevel models for evaluating the risk of pedestrian–motor vehicle collisions at intersections and mid-blocks

Walking is a popular form of physical activity associated with clear health benefits. Promoting safe walking for pedestrians requires evaluating the risk of pedestrian–motor vehicle collisions at specific roadway locations in order to identify where road improvements and other interventions may be needed. The objective of this analysis was to estimate the risk of pedestrian collisions at intersections and mid-blocks in Seattle, WA. The study used 2007–2013 pedestrian–motor vehicle collision data from police reports and detailed characteristics of the microenvironment and macroenvironment at intersection and mid-block locations. The primary outcome was the number of pedestrian–motor vehicle collisions over time at each location (incident rate ratio [IRR] and 95% confidence interval [95% CI]). Multilevel mixed effects Poisson models accounted for correlation within and between locations and census blocks over time. Analysis accounted for pedestrian and vehicle activity (e.g., residential density and road classification). In the final multivariable model, intersections with 4 segments or 5 or more segments had higher pedestrian collision rates compared to mid-blocks. Non-residential roads had significantly higher rates than residential roads, with principal arterials having the highest collision rate. The pedestrian collision rate was higher by 9% per 10 feet of street width. Locations with traffic signals had twice the collision rate of locations without a signal and those with marked crosswalks also had a higher rate. Locations with a marked crosswalk also had higher risk of collision. Locations with a one-way road or those with signs encouraging motorists to cede the right-of-way to pedestrians had fewer pedestrian collisions. Collision rates were higher in locations that encourage greater pedestrian activity (more bus use, more fast food restaurants, higher employment, residential, and population densities). Locations with higher intersection density had a lower rate of collisions as did those in areas with higher residential property values. The novel spatiotemporal approach used that integrates road/crossing characteristics with surrounding neighborhood characteristics should help city agencies better identify high-risk locations for further study and analysis. Improving roads and making them safer for pedestrians achieves the public health goals of reducing pedestrian collisions and promoting physical activity.     

Residence location of drivers involved in fatal crashes

Traffic safety researchers have long known that the majority of fatal crashes occur on rural roads, but it is not clear whether these crashes involve people who live in rural areas or residents of urban areas traveling on rural roads. ‘Geodemographic' market-research tools allow determination of the urbanization of drivers' residence locations from their postal ‘zip code.' Using data from the 1988–1992 files of the Fatal Accident Reporting System (FARS) maintained by the National Highway Traffic Safety Administration (NHTSA), this study determined the residence location of several subgroups of drivers involved in fatal crashes. Not only did the majority of fatal crashes occur in rural areas, but the majority of fatal crashes involved rural and small-town residents, and the majority of the rural and small-town residents involved in fatal crashes were traveling on rural roads.     

Investigation of pedestrian crashes on two-way two-lane rural roads in Ethiopia

Understanding pedestrian crash causes and contributing factors in developing countries is critically important as they account for about 55% of all traffic crashes. Not surprisingly, considerable attention in the literature has been paid to road traffic crash prediction models and methodologies in developing countries of late. Despite this interest, there are significant challenges confronting safety managers in developing countries. For example, in spite of the prominence of pedestrian crashes occurring on two-way two-lane rural roads, it has proven difficult to develop pedestrian crash prediction models due to a lack of both traffic and pedestrian exposure data. This general lack of available data has further hampered identification of pedestrian crash causes and subsequent estimation of pedestrian safety performance functions. The challenges are similar across developing nations, where little is known about the relationship between pedestrian crashes, traffic flow, and road environment variables on rural two-way roads, and where unique predictor variables may be needed to capture the unique crash risk circumstances. This paper describes pedestrian crash safety performance functions for two-way two-lane rural roads in Ethiopia as a function of traffic flow, pedestrian flows, and road geometry characteristics. In particular, random parameter negative binomial model was used to investigate pedestrian crashes. The models and their interpretations make important contributions to road crash analysis and prevention in developing countries. They also assist in the identification of the contributing factors to pedestrian crashes, with the intent to identify potential design and operational improvements.