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1.
This paper proposes a multimodal approach to study safety at intersections by simultaneously analysing the safety and flow outcomes for both motorized and non-motorized traffic. This study uses an extensive inventory of signalized and non-signalized intersections on the island of Montreal, Quebec, Canada, containing disaggregate motor-vehicle, cyclist and pedestrian flows, injury data, geometric design, traffic control and built environment characteristics in the vicinity of each intersection. Bayesian multivariate Poisson models are used to analyze the injury and traffic flow outcomes and to develop safety performance functions for each mode at both facilities. After model calibration, contributing injury frequency factors are identified. Injury frequency and injury risk measures are then generated to carry out a comparative study to identify which mode is at greatest risk at intersections in Montreal. Among other results, this study identified the significant effect that motor-vehicle traffic imposes on cyclist and pedestrian injury occurrence. Motor-vehicle traffic is the main risk determinant for all injury and intersection types. This highlights the need for safety improvements for cyclists and pedestrians who are, on average, at 14 and12 times greater risk than motorists, respectively, at signalized intersections. Aside from exposure measures, this work also identifies some geometric design and built environment characteristics affecting injury occurrence for cyclists, pedestrians and motor-vehicle occupants. 相似文献
2.
Estimating the risk of collisions between bicycles and motor vehicles at signalized intersections 总被引:2,自引:0,他引:2
Collisions between bicycles and motor vehicles have caused severe life and property losses in many countries. The majority of bicycle-motor vehicle (BMV) accidents occur at intersections. In order to reduce the number of BMV accidents at intersections, a substantial understanding of the causal factors for the collisions is required. In this study, intersection BMV accidents were classified into three types based on the movements of the involved motor vehicles and bicycles. The three BMV accident classifications were through motor vehicle related collisions, left-turn motor vehicle related collisions, and right-turn motor vehicle related collisions. A methodology for estimating these BMV accident risks was developed based on probability theory. A significant difference between this proposed methodology and most current approaches is that the proposed approach explicitly relates the risk of each specific BMV accident type to its related flows. The methodology was demonstrated using a 4-year (1992-1995) data set collected from 115 signalized intersections in the Tokyo Metropolitan area. This data set contains BMV accident data, bicycle flow data, motor vehicle flow data, traffic control data, and geometric data for each intersection approach. For each BMV risk model, an independent explanatory variable set was chosen according to the characteristics of the accident type. Three negative binomial regression models (one corresponding to each BMV accident type) were estimated using the maximum likelihood method. The coefficient value and its significance level were estimated for each selected variable. The negative binomial dispersion parameters for all the three models were significant at 0.01 levels. This supported the choice of the negative binomial regression over the Poisson regression for the quantitative analyses in this study. 相似文献
3.
Md. Mazharul Haque Hoong Chor Chin Helai Huang 《Accident; analysis and prevention》2010,42(1):203-212
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. 相似文献
4.
The link between built environment, pedestrian activity and pedestrian-vehicle collision occurrence at signalized intersections 总被引:1,自引:0,他引:1
This paper studies the influence of built environment (BE) – including land use types, road network connectivity, transit supply and demographic characteristics – on pedestrian activity and pedestrian–vehicle collision occurrence. For this purpose, a two-equation modeling framework is proposed to investigate the effect of built environment on both pedestrian activity and vehicle–pedestrian collision frequency at signalized intersections. Using accident data of ambulance services in the City of Montreal, the applicability of our framework is illustrated. Different model settings were attempted as part of a model sensitivity analysis. Among other results, it was found that the BE in the proximity of an intersection has a powerful association with pedestrian activity but a small direct effect on pedestrian–vehicle collision frequency. This suggests that the impact of BE is mainly mediated through pedestrian activity. In other words, strategies that encourage densification, mix of land uses and increase in transit supply will increase pedestrian activity and may indirectly, with no supplementary safety strategies, increase the total number of injured pedestrians. In accordance with previous research, the number of motor vehicles entering a particular intersection is the main determinant of collision frequency. Our results show that a 30% reduction in the traffic volume would reduce the total number of injured pedestrians by 35% and the average risk of pedestrian collision by 50% at the intersections under analysis. Major arterials are found to have a double negative effect on pedestrian safety. They are positively linked to traffic but negatively associated with pedestrian activity. The proposed framework is useful for the identification of effective pedestrian safety actions, the prediction of pedestrian volumes and the appropriate safety design of new urban developments that encourage walking. 相似文献
5.
Obeng K 《Accident; analysis and prevention》2011,(4):1521-1531
This paper analyzes gender differences in crash risk severities using data for signalized intersections. It estimates gender models for injury severity risks and finds that driver condition, type of crash, type of vehicle driven and vehicle safety features have different effects on females’ and males’ injury severity risks. Also, it finds some variables which are significantly related to females’ injury severity risks but not males’ and others which affect males’ injury severity risks but not females’. It concludes that better and more in-depth information about gender differences in injury severity risks is gained by estimating separate models for females and males. 相似文献
6.
In this study, the generalized estimating equations with the negative binomial link function were used to model rear-end crash frequencies at signalized intersections to account for the temporal or spatial correlation among the data. The longitudinal data for 208 signalized intersections over 3 years and the spatially correlated data for 476 signalized intersections which are located along different corridors were collected in the state of Florida. The modeling results showed that there are high correlations between the longitudinal or spatially correlated rear-end crashes. Some intersection related variables are identified as significantly influencing rear-end crash occurrences at signalized intersections. Intersections with heavy traffic on the major and minor roadways, having more right and left-turn lanes on the major roadway, having a large number of phases per cycle (indicated by the left-turn protection on the minor roadway), with high speed limits on the major roadway, and in high population areas are correlated with high rear-end crash frequencies. On the other hand, intersections with three legs, having channelized or exclusive right-turn lanes on the minor roadway, with protected left-turning on the major roadway, with medians on the minor roadway, and having longer signal spacing have a lower frequency of rear-end crashes. 相似文献
7.
Many studies have shown that intersections are among the most dangerous locations of a roadway network. Therefore, there is a need to understand the factors that contribute to injuries at such locations. This paper addresses the different factors that affect crash injury severity at signalized intersections. It also looks into the quality and completeness of the crash data and the effect that incomplete data has on the final results. Data from multiple sources have been cross-checked to ensure the completeness of all crashes including minor crashes that are usually unreported or not coded into crash databases. The ordered probit modeling technique has been adopted in this study to account for the fact that injury levels are naturally ordered variables. The tree-based regression methodology has also been adopted in this study to explore the factors that affect each severity level. The probit model results showed that a combination of crash-specific information and intersection characteristics result in the highest prediction rate of injury level. More specifically, having a divided minor roadway or a higher speed limit on the minor roadway decreased the level of injury while crashes involving a pedestrian/bicyclist and left turn crashes had the highest probability of a more severe crash. Several regression tree models showed a difference in the significant factors that affect the different severity types. Completing the data with minor non injury crashes improved the modeling results and depicted differences when modeling the no injury crashes. 相似文献
8.
Most crash severity studies ignored severity correlations between driver-vehicle units involved in the same crashes. Models without accounting for these within-crash correlations will result in biased estimates in the factor effects. This study developed a Bayesian hierarchical binomial logistic model to identify the significant factors affecting the severity level of driver injury and vehicle damage in traffic crashes at signalized intersections. Crash data in Singapore were employed to calibrate the model. Model fitness assessment and comparison using intra-class correlation coefficient (ICC) and deviance information criterion (DIC) ensured the suitability of introducing the crash-level random effects. Crashes occurring in peak time and in good street-lighting condition as well as those involving pedestrian injuries tend to be less severe. But crashes that occur in night time, at T/Y type intersections, and on right-most lane, as well as those that occur in intersections where red light cameras are installed tend to be more severe. Moreover, heavy vehicles have a better resistance on severe crash and thus induce less severe injuries, while crashes involving two-wheel vehicles, young or aged drivers, and the involvement of offending party are more likely to result in severe injuries. 相似文献
9.
Chunjiao Dong David B. Clarke Stephen H. Richards Baoshan Huang 《Accident; analysis and prevention》2014
The influence of intersection features on safety has been examined extensively because intersections experience a relatively large proportion of motor vehicle conflicts and crashes. Although there are distinct differences between passenger cars and large trucks-size, operating characteristics, dimensions, and weight-modeling crash counts across vehicle types is rarely addressed. This paper develops and presents a multivariate regression model of crash frequencies by collision vehicle type using crash data for urban signalized intersections in Tennessee. In addition, the performance of univariate Poisson-lognormal (UVPLN), multivariate Poisson (MVP), and multivariate Poisson-lognormal (MVPLN) regression models in establishing the relationship between crashes, traffic factors, and geometric design of roadway intersections is investigated. Bayesian methods are used to estimate the unknown parameters of these models. The evaluation results suggest that the MVPLN model possesses most of the desirable statistical properties in developing the relationships. Compared to the UVPLN and MVP models, the MVPLN model better identifies significant factors and predicts crash frequencies. The findings suggest that traffic volume, truck percentage, lighting condition, and intersection angle significantly affect intersection safety. Important differences in car, car–truck, and truck crash frequencies with respect to various risk factors were found to exist between models. The paper provides some new or more comprehensive observations that have not been covered in previous studies. 相似文献
10.
A systematic procedure is presented for calibrating and validating a microscopic model of safety performance. The context in the model application is the potential for rear-end crashes at signalized intersections. VISSIM® v.4.3 provides the simulation platform for estimating the safety performance for individual vehicles and has been calibrated and validated using separate samples of observed vehicle tracking data extracted from the FHWA/NGSIM program. The calibration exercise involves four sequential steps: (1) heuristic selection of initial model inputs, (2) statistical screening using a Plackett–Burnman design, (3) fractional factorial analysis relating inputs to safety performance, and (4) genetic algorithm procedure for obtaining best estimate input values. Three measures of safety performance were considered: crash potential index, number of vehicles in conflict and total conflict duration per vehicle. Model consistency was assessed by comparing simulated and observed safety performance based on a separate validation sample of vehicle tracking data. The suggested procedure was found to effectively estimate model input parameters that closely matched safety performance measures in the observed validation data. This procedure yields an objective and efficient means for simulation model calibration applied for estimating safety performance at signalized intersections. 相似文献
11.
Chunjiao Dong David B. Clarke Xuedong Yan Asad Khattak Baoshan Huang 《Accident; analysis and prevention》2014
Crash data are collected through police reports and integrated with road inventory data for further analysis. Integrated police reports and inventory data yield correlated multivariate data for roadway entities (e.g., segments or intersections). Analysis of such data reveals important relationships that can help focus on high-risk situations and coming up with safety countermeasures. To understand relationships between crash frequencies and associated variables, while taking full advantage of the available data, multivariate random-parameters models are appropriate since they can simultaneously consider the correlation among the specific crash types and account for unobserved heterogeneity. However, a key issue that arises with correlated multivariate data is the number of crash-free samples increases, as crash counts have many categories. In this paper, we describe a multivariate random-parameters zero-inflated negative binomial (MRZINB) regression model for jointly modeling crash counts. The full Bayesian method is employed to estimate the model parameters. Crash frequencies at urban signalized intersections in Tennessee are analyzed. The paper investigates the performance of MZINB and MRZINB regression models in establishing the relationship between crash frequencies, pavement conditions, traffic factors, and geometric design features of roadway intersections. Compared to the MZINB model, the MRZINB model identifies additional statistically significant factors and provides better goodness of fit in developing the relationships. The empirical results show that MRZINB model possesses most of the desirable statistical properties in terms of its ability to accommodate unobserved heterogeneity and excess zero counts in correlated data. Notably, in the random-parameters MZINB model, the estimated parameters vary significantly across intersections for different crash types. 相似文献
12.
A Bayesian Belief Network modelling of organisational factors in risk analysis: A case study in maritime transportation 总被引:2,自引:0,他引:2
The paper presents an innovative approach to integrate Human and Organisational Factors (HOF) into risk analysis. The approach has been developed and applied to a case study in the maritime industry, but it can also be utilised in other sectors. A Bayesian Belief Network (BBN) has been developed to model the Maritime Transport System (MTS), by taking into account its different actors (i.e., ship-owner, shipyard, port and regulator) and their mutual influences. The latter have been modelled by means of a set of dependent variables whose combinations express the relevant functions performed by each actor. The BBN model of the MTS has been used in a case study for the quantification of HOF in the risk analysis carried out at the preliminary design stage of High Speed Craft (HSC). The study has focused on a collision in open sea hazard carried out by means of an original method of integration of a Fault Tree Analysis (FTA) of technical elements with a BBN model of the influences of organisational functions and regulations, as suggested by the International Maritime Organisation's (IMO) Guidelines for Formal Safety Assessment (FSA). The approach has allowed the identification of probabilistic correlations between the basic events of a collision accident and the BBN model of the operational and organisational conditions. The linkage can be exploited in different ways, especially to support identification and evaluation of risk control options also at the organisational level. Conditional probabilities for the BBN have been estimated by means of experts’ judgments, collected from an international panel of different European countries. Finally, a sensitivity analysis has been carried out over the model to identify configurations of the MTS leading to a significant reduction of accident probability during the operation of the HSC. 相似文献
13.
Urban expressway systems have been developed rapidly in recent years in China; it has become one key part of the city roadway networks as carrying large traffic volume and providing high traveling speed. Along with the increase of traffic volume, traffic safety has become a major issue for Chinese urban expressways due to the frequent crash occurrence and the non-recurrent congestions caused by them. For the purpose of unveiling crash occurrence mechanisms and further developing Active Traffic Management (ATM) control strategies to improve traffic safety, this study developed disaggregate crash risk analysis models with loop detector traffic data and historical crash data. Bayesian random effects logistic regression models were utilized as it can account for the unobserved heterogeneity among crashes. However, previous crash risk analysis studies formulated random effects distributions in a parametric approach, which assigned them to follow normal distributions. Due to the limited information known about random effects distributions, subjective parametric setting may be incorrect. In order to construct more flexible and robust random effects to capture the unobserved heterogeneity, Bayesian semi-parametric inference technique was introduced to crash risk analysis in this study. Models with both inference techniques were developed for total crashes; semi-parametric models were proved to provide substantial better model goodness-of-fit, while the two models shared consistent coefficient estimations. Later on, Bayesian semi-parametric random effects logistic regression models were developed for weekday peak hour crashes, weekday non-peak hour crashes, and weekend non-peak hour crashes to investigate different crash occurrence scenarios. Significant factors that affect crash risk have been revealed and crash mechanisms have been concluded. 相似文献
15.
W.J. Frith 《Accident; analysis and prevention》1984,16(2):75-76
Zador, Moshman and Marcus estimated an increase in right-turn accidents of 21% following the adoption of right turn on red. However, their study contained property damage only accidents, as well as injury accidents, and the change in injury accidents was not reported. An insignificant decrease (?0.7%) in accidents involving incapacitating injury was reported, however. It is suggested that Zador et al. report on the change in injury accidents in their sample. 相似文献
16.
The ripple effect can occur when a supplier base disruption cannot be localised and consequently propagates downstream the supply chain (SC), adversely affecting performance. While stress-testing of SC designs and assessment of their vulnerability to disruptions in a single-echelon-single-event setting is desirable and indeed critical for some firms, modelling the ripple effect impact in multi-echelon-correlated-events systems is becoming increasingly important. Notably, ripple effect assessment in multi-stage SCs is particularly challenged by the need to consider both vulnerability and recoverability capabilities at individual firms in the network. We construct a new model based on integration of Discrete-Time Markov Chain (DTMC) and a Dynamic Bayesian Network (DBN) to quantify the ripple effect. We use the DTMC to model the recovery and vulnerability of suppliers. The proposed DTMC model is then equalised with a DBN model in order to simulate the propagation behaviour of supplier disruption in the SC. Finally, we propose a metric that quantifies the ripple effect of supplier disruption on manufacturers in terms of total expected utility and service level. This ripple effect metric is applied to two case studies and analysed. The findings suggest that our model can be of value in uncovering latent high-risk paths in the SC, analysing the performance impact of both a disruption and its propagation, and prioritising contingency and recovery policies. 相似文献
17.
MacNab YC 《Accident; analysis and prevention》2004,36(6):1019-1028
In this article, recently developed Bayesian spatial and ecological regression models are applied to analyse small-area variation in accident and injury. This study serves to demonstrate how Bayesian modelling techniques can be implemented to assess potential risk factors measured at group (e.g. area) level. Presented here is a unified modelling framework that enables thorough investigations into associations between injury rates and regional characteristics, residual variation and spatial autocorrelation. Using hospital separation data for 83 local health areas in British Columbia (BC), Canada, in 1990–1999, we explore and examine ecological/contextual determinants of motor vehicle accident injury (MVAI) among male children and youth aged 0–24 and for those of six age groups (<1, 1–4, 5–9, 10–14, 15–19 and 20–24). Eighteen local health area characteristics are studied. They include a broad spectrum of socio-economic indicators, residential environment indicators (roads and parks), medical services availability and utilisation, population health, proportion of recent immigrants, crime rates, rates of speeding charge and rates of seatbelt violation. Our study indicates a large regional variation in MVAI in males aged 0–24 in British Columbia, Canada, in 1990–1999, and that adjusting for appropriate risk factors eliminates nearly all the variation observed. Socio-economic influence on MVAI was profoundly apparent in young males of all ages with the injury being more common in communities of lower socio-economic status. High adult male crime rates were significantly associated with high injury rates of boys aged 1–14. Seatbelt violations and excess speeding charges were found to be positively associated with the injury rates of young men aged 20–24. This and similar ecological studies shed light on reasons for regional variations in accident occurrence as well as in the resulting injuries and hospital utilisation. Thereby they are potentially useful in identifying priority areas for injury/accident prevention and in informing regional health planning and policy development. 相似文献
18.
MacNab YC 《Accident; analysis and prevention》2003,35(1):91-102
This article presents a recent study which applies Bayesian hierarchical methodology to model and analyse accident and injury surveillance data. A hierarchical Poisson random effects spatio-temporal model is introduced and an analysis of inter-regional variations and regional trends in hospitalisations due to motor vehicle accident injuries to boys aged 0-24 in the province of British Columbia, Canada, is presented. The objective of this article is to illustrate how the modelling technique can be implemented as part of an accident and injury surveillance and prevention system where transportation and/or health authorities may routinely examine accidents, injuries, and hospitalisations to target high-risk regions for prevention programs, to evaluate prevention strategies, and to assist in health planning and resource allocation. The innovation of the methodology is its ability to uncover and highlight important underlying structure of the data. Between 1987 and 1996, British Columbia hospital separation registry registered 10,599 motor vehicle traffic injury related hospitalisations among boys aged 0-24 who resided in British Columbia, of which majority (89%) of the injuries occurred to boys aged 15-24. The injuries were aggregated by three age groups (0-4, 5-14, and 15-24), 20 health regions (based of place-of-residence), and 10 calendar years (1987 to 1996) and the corresponding mid-year population estimates were used as 'at risk' population. An empirical Bayes inference technique using penalised quasi-likelihood estimation was implemented to model both rates and counts, with spline smoothing accommodating non-linear temporal effects. The results show that (a) crude rates and ratios at health region level are unstable, (b) the models with spline smoothing enable us to explore possible shapes of injury trends at both the provincial level and the regional level, and (c) the fitted models provide a wealth of information about the patterns (both over space and time) of the injury counts, rates and ratios. During the 10-year period, high injury risk ratios evolved from northwest to central-interior and the southeast [corrected]. 相似文献
19.
To enable packaging machinery manufacturers to compete at an international level, it is necessary to introduce them to more advanced design methods and technologies. For years, the evolution of packaging machinery has relied heavily on trial‐and‐error methods. The demands for continual increases in the performance capabilities of the machines, escalating legislation, environmental directives and changes in the characteristics of the product require rapid development of existing machine designs and the creation of new machines. This paper discusses the needs of SME packaging machinery manufacturers and identifies their requirements for methods in support of the design and redesign of packaging machinery. The need to identify, capture and manipulate design knowledge is critical for SMEs, where all too often design records are incomplete. Furthermore, a systems modelling approach that provides for support over the conceptual, embodiment and detailed design phases is essential for the rapid and effective development of designs. In order to meet these requirements, a methodology is proposed which incorporates ‘constraint modelling’ techniques. The methodology provides for experimental investigation and computer‐based modelling, which together aid the designer in gaining a fundamental understanding of the design problem. This enables the identification and representation of design knowledge, the determination of the limitations of an existing design, the evaluation of alternative designs and redesign strategies, as well as the embodiment, refinement and optimization of design solutions. The theory of ‘constraint modelling’ is discussed and the various phases of the methodology described. The applications of the methodology to a new machine design and a redesign program are also detailed. Copyright © 2001 John Wiley & Sons, Ltd. 相似文献
20.
STUDY OBJECTIVE: The study examines whether there are socioeconomic differences among young motorcycle drivers (aged 16-25) involved in road-traffic injuries with regard to age and injury severity. DESIGN: Nationwide retrospective register-based cohort study. SETTING AND PARTICIPANTS: Subjects born in 1970-1972 were extracted from the Swedish Population and Housing Census of 1985 (n = 334,070). Individual records from the 1985 census were linked to police-reported data and hospital-based data for the period 1988-1995 on the basis of a search for each subject's first registered road-traffic injury as a motorcycle driver (n = 2034). Information on household socioeconomic group was taken from the Swedish census of 1985. Two categories of crash severity were analysed (minor injury and severe/fatal injury), based on assessments of the police and according to length of hospitalization. MAIN RESULTS: Incidence of motorcycle injury varies considerably according to age of driver, reaching a peak at the age of 17. The greatest differences in injury risk between socioeconomic groups are present when their members are aged 17-19. At the age of 18, subjects belonging to low socioeconomic positions run a risk of injury occurrence 2.5 times higher than those belonging to the highest socioeconomic category. Young drivers in lower socioeconomic groups have higher odds for both minor and severe injuries than their counterparts in the highest socioeconomic group, but there is no further increase for the latter. CONCLUSIONS: The study demonstrates how crucial the first years of driving are in relation to injury, and how wide the gap is in terms of socioeconomic differences at these ages, suggesting that this is the most appropriate time for intervention. 相似文献