Effect of novel divergence markings on conflict prevention regarding motorcycle-involved right turn accidents of mixed traffic flow

Introduction: In Taiwan, segregated traffic flow countermeasures have long been in place. Although these facilities have decreased the numbers of motorcycle left-turn collisions, right-angle collisions, and sideswipe collisions, they have also induced serious right-turn accidents. The purpose of this research was to evaluate an intervention intended to decrease conflicts and motorcycle-involved crashes. In this study, the reasons why the motorcycle accident rate is higher at intersections with slow lanes than at those without slow lanes are presented, and the theory of the self-explaining road was applied to create divergence markings for a mixed traffic flow environment. An intervention that guides motorcycles and cars into appropriate locations at intersections was applied to three intersection approaches. Method: The intervention effectiveness was evaluated by comparing the number of accidents at the intersections before and after the implementation of improvement measures. Moreover, video recordings were used to analyze the traffic distributions at the cross-sections of intersections. T-test was adopted to examine whether the traffic flows at the cross-sections of the intersections before and after the intervention were statistically different. In addition, this research applied the post-encroachment time (PET), the time between the first road user leaving the encroachment zone and the second road user arriving in it, to evaluate traffic conflicts. Finally, the PET and severity index between a straight-through motorcycle and a right-turn vehicle were analyzed. Results: PET increased by 3.2%–20.4%, and the rates of right-turn collisions, sideswipe collisions, and rear-end collisions decreased by 64.3%, 77.3%, and 61.5% respectively. Conclusions: Eliminating the slow traffic lane and setting divergence markings may not effectively cause vehicles in different driving directions to drive in the proper locations in the lanes. However, divergence markings both reduce the rate of right-turn collisions and decrease the incidence of sideswipe and rear-end collisions. Practical applications: The proposed design method may be a good design reference for countries having a high motorcycle density.     

Accident risk of foreign drivers in various road environments

INTRODUCTION: This paper reports on the accident risk of foreign and native drivers in various road environments in Greece. In particular, the analysis aims to determine the combined effect of driver nationality, area type (inside/outside urban area), junction (yes/no), and lighting conditions (day/night) on accident fault risk. METHODS: Data from the national accident database of Greece are used in a hierarchical log-linear analysis. The induced exposure technique is applied due to the lack of exposure data. Estimated and observed odds ratios are then examined for the quantification of the various effects in terms of relative risk. RESULTS: The initial examination of a saturated model leads to the rejection of all three- and higher-order effects within variables, without providing an adequate fit to the data. On the contrary, a non-saturated second-order model presents a very satisfactory overall fit. The examination of single and combined effects indicates that the most significant effect on accident risk rises from the presence of foreign drivers at junctions. CONCLUSIONS: Results confirm that foreign drivers in Greece are at increased risk. However, immigrant permanent residents appear to have a lower risk compared to tourists, regardless of the road environment.     

Motorcyclist injury severity in angle crashes at T-junctions: Identifying significant factors and analysing what made motorists fail to yield to motorcycles

Evidence in literature suggested that motorists’ failure to give way to motorcycles at junctions is the main contributory factor to motorcycle–car accidents that involve gap acceptance (i.e., approach-turn and angle crashes). This paper attempts to examine how motorist’s failure to give way affects motorcyclist injury severity in angle crashes at T-junctions, while controlling for other factors (demographic, vehicle, crash, and environmental factors). Binary logistic models of motorcyclist injury severity were estimated using the data extracted from the Stats19 accident injury database (1991–2004). Angle collisions were classified into several sub-crashes based on the manoeuvres motorcycles and cars were making prior to the accidents. The modelling results showed that injuries were greatest when a travelling-straight motorcycle on the main road crashed into a right-turn car from the minor road, particularly at stop-/yield-controlled junctions. Such crash pattern was assumed to be an accident involving right-of-way violation. Using binary logistic models, factors determining the likelihood of motorist’s failure to yield to motorcycles were also examined. The implications of the research findings of this present study were provided.     

Incorporating real-time traffic and weather data to explore road accident likelihood and severity in urban arterials

IntroductionThe effective treatment of road accidents and thus the enhancement of road safety is a major concern to societies due to the losses in human lives and the economic and social costs. The investigation of road accident likelihood and severity by utilizing real-time traffic and weather data has recently received significant attention by researchers. However, collected data mainly stem from freeways and expressways. Consequently, the aim of the present paper is to add to the current knowledge by investigating accident likelihood and severity by exploiting real-time traffic and weather data collected from urban arterials in Athens, Greece.MethodRandom Forests (RF) are firstly applied for preliminary analysis purposes. More specifically, it is aimed to rank candidate variables according to their relevant importance and provide a first insight on the potential significant variables. Then, Bayesian logistic regression as well finite mixture and mixed effects logit models are applied to further explore factors associated with accident likelihood and severity respectively.ResultsRegarding accident likelihood, the Bayesian logistic regression showed that variations in traffic significantly influence accident occurrence. On the other hand, accident severity analysis revealed a generally mixed influence of traffic variations on accident severity, although international literature states that traffic variations increase severity. Lastly, weather parameters did not find to have a direct influence on accident likelihood or severity.ConclusionsThe study added to the current knowledge by incorporating real-time traffic and weather data from urban arterials to investigate accident occurrence and accident severity mechanisms.Practical applicationThe identification of risk factors can lead to the development of effective traffic management strategies to reduce accident occurrence and severity of injuries in urban arterials.     

Analysis of recent trends in bus and coach safety in Britain

We examine in detail trends from 1966 to 1990 and the fitting of statistical models to assess whether significant changes have taken place in casualty rates since local bus deregulation in 1986.The major source of data is the ‘Stats 19’ collated from police reports by the Department of Transport.The evidence indicates that no significant change in casualty rates for bus and coach occupants (defined as those killed or seriously injured) has occurred since local bus deregulation, although the previous trend of reduction in fatality rates has not been maintained.International comparisons have been made between Britain and a sample of other West European countries. Britain appears to have a higher occupant fatality rate. However, other countries′ data do not always include casualties to bus and coach occupants other than those in which vehicular collisions occur. Better comparative data is available for accidents involving buses and coaches with other road users, notably for Britain and Germany. These suggest that such accidents tend to reflect the national pattern of road casualty rates — for example, Germany has a higher level of collisions between buses and coaches, and other road vehicles, while Britain has a relatively high incidence of casualties involving pedestrians.Differences in accident rates between Britain and other European countries and the extent to which they reflect real differences, as distinct from those due to differences in recording of data, are evaluated, along with policy implications.     

Severity of passenger injuries on public buses: A comparative analysis of collision injuries and non-collision injuries

Introduction: Although public buses have been demonstrated as a relatively safe mode of transport, the number of injuries to public bus passengers is far from negligible. Existing studies of public bus safety have focused primarily on injuries caused by collisions. Surprisingly, limited effort has been devoted to identifying factors that increase the severity of passenger injuries in non-collision incidents. Method: Our study therefore investigated the injury risk of public bus passengers involved in collision incidents and non-collision incidents comparatively, based on a police-reported dataset of 17,383 passengers injured on franchised public buses over a 10-year period in Hong Kong. A random parameters logistic model was established to estimate the likelihood of fatal and severe injuries to passengers as a function of various factors. Results: Our results indicated substantial inconsistences in the effects of risk factors between models of non-collision injuries and collision injuries. The severity of passenger injuries tended to increase significantly when non-collision incidents occurred due to excessive speed of bus drivers, on double-decker buses, in less urbanized areas, in winter, in heavy rains, during daytime, and at night without street lighting. Elderly female passengers were also found more likely to be fatally or severely injured in non-collision incidents if they lost their balance while boarding, alighting from, or standing on a bus. In comparison, the following factors were associated with a greater likelihood of fatal or severe injuries in collision incidents: elderly female passengers, standing passengers who lost balance, buses out of driver control, double-decker buses, collisions with vehicles or objects, and less urbanized areas. Practical Applications: Based on our comparative analysis, more targeted countermeasures, namely “4E” (engineering, enforcement, emergency, and education) and “3A” (awareness, appreciation, and assistance), were recommended to mitigate collision injuries and non-collision injuries to public bus passengers, respectively.     

Exploring motorcyclist injury severity resulting from various crash configurations at T-junctions in the United Kingdom--an application of the ordered probit models

OBJECTIVES: The fact that motorcycle users tend to be more vulnerable to injuries than those using other motorized vehicles may act synergistically with the complexity of conflicting movements between vehicles and motorcycles to increase injury severity in a junction-type accident. A junction-type collision tends to be more severe than a non-junction case due to the fact that some of the injurious crashes such as angle-collision commonly occur. Existing studies have applied several statistical modeling techniques to examine influential factors on the occurrences of different crashes among motorized vehicles but surprisingly very little has empirically explored whether a particular crash type, resulting from a junction-type accident, is more injurious to motorcyclists. This article attempts to investigate whether a particular collision is more deadly to motorcyclists conditioned on crash occurrence at T-junctions in the U.K., while controlling for environment, vehicle, and demographic factors. METHODS: The statistical modeling technique employed is the ordered probit models using the data extracted from the STATS19 accident injury database (1999-2004). RESULTS: The modeling found determinants of injury severity among motorcyclists at T-junctions in the U.K. For example, an approach-turn/head-on collision is much more injurious to motorcyclists; and, those riding in early morning (i.e., 0000-0659) are more likely to be severely injured. CONCLUSIONS: This study offers a guideline for future research, as well as insight into potential prevention strategies that might help moderate motorcyclist injuries.     

摩托车头盔与摩托车交通事故的相关研究

我国近年来的摩托车死亡事故占交通事故死亡总数的25％-28％。在我国摩托车使用比较普及的地区，摩托车交通事故数占到该地区交通事故总数的70％-80％，伤亡比例占到总数的50％以上，甚至更高。通过对摩托车交通事故伤亡人员的具体受伤部位分析，发现头部受伤致死的比例非常高，占到该类事故死亡总数75％以上，远远高于其他部位受伤致死率。摩托车驾乘人员头部受伤致死的主要原因是摩托车驾驶乘人员头盔佩戴率低和佩戴的头盔质量差，对头部未能起到应有的保护作用。造成这一局面既有摩托车乘员头盔标准等技术层面存在的问题，又有行业监管等政策层面存在的问题，最后，文章从摩托车头盔标准方面提出了几点修订建议，为规范头盔行业进行基础性的准备。     

Risk factors in urban road traffic accidents

INTRODUCTION: The urban road traffic accident (RTA) risks for the city of Zagreb, Croatia, from 1999 through 2000 were analyzed with the aim of reducing the increasing injury incidence. METHOD: Simple and bivariate analysis using chi(2), odds ratio, and confidence interval of 95% was used to determine risks in three outcome groups: killed, severely, and mildly injured. RESULTS: There were 528 RTA victims consisting of 260 severely, 213 mildly injured, and 55 killed at the scene of an accident and during transportation. More fatal accidents occurred during night hours (OR=3.78; 95% CI, 2.08-6.85), on urban road links (OR=2.33; 95% CI, 1.30-4.19), and at exceeding speed limit (OR=2.56; 95% CI, 1.43-4.61). More people were injured than killed on urban junctions (OR=5.27; 95% CI, 2.21-12.57). The highest combined risk of dying or being severely injured was found in males, driving at excessive speed, on urban links, and during bad visibility (OR=16.15; 95% CI, 3.901-66.881). CONCLUSION: These results will influence the urban traffic police enforcement measures, which will change inappropriate behavior of drivers and protect the least experienced road users.     

A simultaneous equations model of crash frequency by collision type for rural intersections

Safety at roadway intersections is of significant interest to transportation professionals due to the large number of intersections in transportation networks, the complexity of traffic movements at these locations that leads to large numbers of conflicts, and the wide variety of geometric and operational features that define them. A variety of collision types including head-on, sideswipe, rear-end, and angle crashes occur at intersections. While intersection crash totals may not reveal a site deficiency, over exposure of a specific crash type may reveal otherwise undetected deficiencies. Thus, there is a need to be able to model the expected frequency of crashes by collision type at intersections to enable the detection of problems and the implementation of effective design strategies and countermeasures. Statistically, it is important to consider modeling collision type frequencies simultaneously to account for the possibility of common unobserved factors affecting crash frequencies across crash types. In this paper, a simultaneous equations model of crash frequencies by collision type is developed and presented using crash data for rural intersections in Georgia. The model estimation results support the notion of the presence of significant common unobserved factors across crash types, although the impact of these factors on parameter estimates is found to be rather modest.     

The effect of speed limit reductions in urban areas on cyclists’ injuries in collisions with cars

Abstract

Objective: Impact speed is one of the most important factors explaining the severity of injuries to cyclists when they collide with passenger cars. To reduce injury severity (especially for vulnerable road users), since 2008, Swedish municipalities have the authority to lower the speed limit to 30 or 40?km/h in urban areas as appropriate. The aim of this study was to evaluate how this speed limit reduction has influenced the injury severity for cyclists in this type of collision.

Method: Data from 1,953 collisions between bicycles and passenger cars were collected using information from third-party-liability insurance claims from 2005 to 2017. The change of speed limit distribution, influenced by the reduction of speed limits in urban areas, where car-to-cyclist collisions occurred was studied. Following that, injury severity for cyclists was evaluated regarding collisions occurring in areas with different speed limits.

Results: The results show that, in collisions with cars, cyclists have a significantly lower risk of a moderate-to-fatal (MAIS 2+) injury when the speed limit is 30–40?km/h compared to 50–60?km/h. During the last decade, while the speed-limit has been lowered on many road-sections in urban areas from 50–60?km/h to 30–40?km/h the risk of a cyclist getting a MAIS 2+ injury decreased by 25%. In 2005 to 2011, 16% of the crashes happened on a road with a speed limit of 30–40?km/h; in 2016–2017, this percentage had increased to approximately 50%. Thus, in recent years more crashes occurred on roads with lower speed limits, and in these crashes, there was a lower risk of severe injuries to cyclists. Unfortunately, it was not possible to evaluate the risk of a crash for specific speed limits; since one limitation of this study was the lack of exposure data, nor do we know the impact speed or the actual speed of the vehicles.

Conclusions: This study is an important follow-up on the implementation of measures that can influence bicycle safety. The insurance data used, made it possible to quantify a positive effect on injury severity for cyclists in passenger car-to-cyclist collisions when the speed limit was reduced in urban areas. Insurance claims cover collisions of all crash severity, so they include data covering all types of injuries—not just the most severe/fatal ones. This aspect is especially important in the speed intervals evaluated here, since moderate (MAIS 2) injuries are very frequent in lower-speed crashes and even these injuries can result in long-term consequences.     

Older drivers’ involvement in fatal RTCs. Do crashes fatal to them differ from crashes involving them but fatal to others?

In several countries, older drivers are disproportionately involved in fatal road traffic crashes (RTCs) for various reasons. This study maps the circumstances of occurrence of crashes involving older drivers that are fatal to either them or other road users and highlights differences between them. Sweden’s national in-depth studies of fatal RTCs archive was used and focus was placed on crashes in which a driver aged 65 years or older was involved between 2002 and 2004 (n = 197). Thirteen driver and crash characteristics were analyzed simultaneously and typical crash patterns (classes) were highlighted. For each pattern, the proportions of crashes fatal to the older driver vs. to someone else were compared. Four patterns were identified: (1) crashes on low-speed stretches, involving left turn and intersections; (2) crashes involving very old drivers and older vehicles, (3) rear-end collisions on high-speed stretches; and (4) head-on and single-vehicle crashes in rural areas. Older drivers dying in the crash were over-represented in classes 2 and 4. The study shows that when older drivers are involved in fatal RTCs, they are often the ones who die (60%). Typical circumstances surrounding their involvement include manoeuvring difficulties, fast-moving traffic, and colliding in an old vehicle. Preventing fatal RTCs involving older drivers requires not only age-specific but also general measures.     

Investigating safety of vulnerable road users in selected EU countries

Problem: Vulnerable road users comprise over half of all road accident victims in the EU and their safety situation is not improving as fast as for motorists. The paper examines factors affecting fatality risk of pedestrians, cyclists, motorcyclists, and moped riders in seven EU countries using data from CARE database. Method: Comparing accident severity indicators between countries is problematic because of data quality issues, different degree of underreporting, and different exposure levels. To avoid bias arising from these issues, fatality risk is modeled with binary logistic regression. Risk factors considered include accident location by area type, junction type, and traffic control, as well as lighting condition. Results are presented as odds ratios of fatal accident outcome in different countries under specific circumstances compared to reference conditions. It is shown that the error in OR values due to underreporting is small. Results and discussion: Wide confidence intervals of the odds ratios in some countries confirm problems with accident data quality. Fatality risk is always higher for non-urban versus urban area and for darkness versus daylight conditions, but the odds ratios are different for different countries. Inconsistent results are obtained for accident location with respect to junction and its control type. Possible reasons for these differences are suggested and discussed. Practical applications: The proposed method avoids the data quality bias of accident severity indicators, thus, it can be used in international comparisons of vulnerable road user accidents. The article findings also support the concept of changes in legislation, such as reducing the speed limit in urban areas in Poland at night. Generally, the experience of countries with low VRU fatality risk identified in the article can be transferred to those with a higher risk.     

Characteristics and clinical outcomes of head-injured cyclists with and without helmets in urban and rural areas of Taiwan: A 15-year study

Objective: Bicycle riding is increasingly popular in Taiwan, but the number of cyclists injured and cyclists' death rates are both increasing. The aim of this study was to investigate the different characteristics and clinical outcomes of traffic accident–related head injuries among cyclists in urban and rural areas.

Methods: Records of 812 patients (533 urban and 279 rural) admitted to 27 hospitals in Taipei City and Hualien County as the result of a traumatic head injury while bicycling between 1998 and 2013 were retrieved for study. Demographics, details about the accident, protective helmet use, and clinical outcomes were then subjected to analysis.

Results: Urban victims were more likely to be injured during morning and early evening rush hours and rural victims during the day; most urban victims were between 19 and 34 years of age and injured in the slow lane; rural victims tended to be younger or older and were injured in the fast lane (all P ≤.001). Riders who wore a helmet were less likely to suffer loss of consciousness (odds ratio [OR] = 0.31), amnesia (OR = 0.069), neurological disorders (OR = 0.205), or facial fractures (OR = 0.369). Older age, more severe head injuries, and bicycle–motor vehicle collisions influenced the severity of symptoms on admission and the residual effects at discharge.

Conclusions: Differences in the characteristics of injuries in urban and rural areas and the utilization of protective helmets may help government authorities adopt appropriate policies to promote safer and more enjoyable cycling.     

Analysis of the injury severity of crashes by considering different lighting conditions on two-lane rural roads

IntroductionMany studies have examined different factors contributing to the injury severity of crashes; however, relatively few studies have focused on the crashes by considering the specific effects of lighting conditions. This research investigates lighting condition differences in the injury severity of crashes using 3-year (2009–2011) crash data of two-lane rural roads of the state of Washington.MethodSeparate ordered-probit models were developed to predict the effects of a set of factors expected to influence injury severity in three lighting conditions; daylight, dark, and dark with street lights. A series of likelihood ratio tests were conducted to determine if these lighting condition models were justified.ResultsThe modeling results suggest that injury severity in specific lighting conditions are associated with contributing factors in different ways, and that such differences cannot be uncovered by focusing merely on one aggregate model. Key differences include crash location, speed limit, shoulder width, driver action, and three collision types (head-on, rear-end, and right-side impact collisions).Practical ApplicationsThis paper highlights the importance of deploying street lights at and near intersections (or access points) on two-lane rural roads because injury severity highly increases when crashes occur at these points in dark conditions.     

Analyses of rear-end crashes based on classification tree models

OBJECTIVE: Signalized intersections are accident-prone areas especially for rear-end crashes due to the fact that the diversity of the braking behaviors of drivers increases during the signal change. The objective of this article is to improve knowledge of the relationship between rear-end crashes occurring at signalized intersections and a series of potential traffic risk factors classified by driver characteristics, environments, and vehicle types. METHODS: Based on the 2001 Florida crash database, the classification tree method and Quasi-induced exposure concept were used to perform the statistical analysis. Two binary classification tree models were developed in this study. One was used for the crash comparison between rear-end and non-rear-end to identify those specific trends of the rear-end crashes. The other was constructed for the comparison between striking vehicles/drivers (at-fault) and struck vehicles/drivers (not-at-fault) to find more complex crash pattern associated with the traffic attributes of driver, vehicle, and environment. RESULTS: The modeling results showed that the rear-end crashes are over-presented in the higher speed limits (45-55 mph); the rear-end crash propensity for daytime is apparently larger than nighttime; and the reduction of braking capacity due to wet and slippery road surface conditions would definitely contribute to rear-end crashes, especially at intersections with higher speed limits. The tree model segmented drivers into four homogeneous age groups: < 21 years, 21-31 years, 32-75 years, and > 75 years. The youngest driver group shows the largest crash propensity; in the 21-31 age group, the male drivers are over-involved in rear-end crashes under adverse weather conditions and the 32-75 years drivers driving large size vehicles have a larger crash propensity compared to those driving passenger vehicles. CONCLUSIONS: Combined with the quasi-induced exposure concept, the classification tree method is a proper statistical tool for traffic-safety analysis to investigate crash propensity. Compared to the logistic regression models, tree models have advantages for handling continuous independent variables and easily explaining the complex interaction effect with more than two independent variables. This research recommended that at signalized intersections with higher speed limits, reducing the speed limit to 40 mph efficiently contribute to a lower accident rate. Drivers involved in alcohol use may increase not only rear-end crash risk but also the driver injury severity. Education and enforcement countermeasures should focus on the driver group younger than 21 years. Further studies are suggested to compare crash risk distributions of the driver age for other main crash types to seek corresponding traffic countermeasures.     

Pedestrian Casualties and Fatalities in Road Traffic Crashes in a South African Municipality

A study of the pedestrian casualties and fatalities in road traffic crashes in Durban, a South African municipality, for 1999 was undertaken using official road traffic accident data. The pedestrians age 25 to 44, although only 23.9% of the population, were 39.3% of the casualties and 48.2% of the fatalities. The most vulnerable pedestrians were those 30 to 34 years old who were 6.1% of the population, 11.7% of the casualties, and 14.6% of the fatalities; 35- to 39-year-olds who were 6% of the population, 8.8% of the casualties, and 13.5% of the fatalities; and the 40- to 44-year-olds who were 4.9% of the population, 7.5% of the casualties, and 10.2% of the fatalities. Cars were involved in 52% of the vehicle-pedestrian crashes but had fewer crashes than minibuses and buses, and fewer casualties and fatalities than minibuses, buses, and motorcycles. Minibuses recorded the most crashes at 1,037 per 100 million km, the highest casualty rate of 268 per 100 million km, and highest fatality rate of 17 per 100 million km. Buses, which were involved in 3% of the vehicle-pedestrian crashes, had 951 crashes per 100 million km, 182 casualties per 100 million km, and 11 fatalities per 100 million km. Motorcycles were involved in 1% of the vehicle-pedestrian crashes and had per 100 million km 508 crashes, 192 casualties, and 7 fatalities. There was no statistically significant difference in the monthly distribution of the road traffic crashes.     

Pedestrian casualties and fatalities in road traffic crashes in a South African municipality

A study of the pedestrian casualties and fatalities in road traffic crashes in Durban, a South African municipality, for 1999 was undertaken using official road traffic accident data. The pedestrians age 25 to 44, although only 23.9% of the population, were 39.3% of the casualties and 48.2% of the fatalities. The most vulnerable pedestrians were those 30 to 34 years old who were 6.1% of the population, 11.7% of the casualties, and 14.6% of the fatalities; 35- to 39-year-olds who were 6% of the population, 8.8% of the casualties, and 13.5% of the fatalities; and the 40- to 44-year-olds who were 4.9% of the population, 7.5% of the casualties, and 10.2% of the fatalities. Cars were involved in 52% of the vehicle-pedestrian crashes but had fewer crashes than minibuses and buses, and fewer casualties and fatalities than minibuses, buses, and motorcycles. Minibuses recorded the most crashes at 1,037 per 100 million km, the highest casualty rate of 268 per 100 million km, and highest fatality rate of 17 per 100 million km. Buses, which were involved in 3% of the vehicle-pedestrian crashes, had 951 crashes per 100 million km, 182 casualties per 100 million km, and 11 fatalities per 100 million km. Motorcycles were involved in 1% of the vehicle-pedestrian crashes and had per 100 million km 508 crashes, 192 casualties, and 7 fatalities. There was no statistically significant difference in the monthly distribution of the road traffic crashes.     

基于Logistic的不同车型碰撞行人事故严重程度致因分析

为定量分析不同车型碰撞行人事故严重程度影响因素,以美国北卡罗来纳州2007-2016年人车碰撞事故数据为样本,将其分为小轿车、SUV、货车碰撞行人事故3类,以事故严重程度为因变量,交通参与者属性、道路、环境条件和事故特征为候选自变量,分别建立累计logistic模型进行对比分析,探究人、车、路和环境因素对人车碰撞事故严...