scholarly journals Safety Analysis of Signal-Coordinated Arterials with Multiple Heterogeneities

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yingfei Fan ◽  
Guopeng Zhang ◽  
Zhixuan Jia ◽  
Minjie Jin
Keyword(s):  
Temporal Change ◽  
Evaluation Model ◽  
Safety Evaluation ◽  
Safety Analysis ◽  
Traffic Data ◽  
Modeling Framework ◽  
Crash Frequency ◽  
Signal Coordination ◽  
Ann Arbor ◽  
Structural Heterogeneities

In the corresponding research available, the safety impact remains controversial in implementing signal coordination on arterials, which calls for an in-depth exploration with the appropriate statistical methods. Based on the traffic data from Ann Arbor City (Michigan, USA), the paper proposes a safety evaluation model considering the multiple heterogeneities. In terms of arterials with the coordinated signalization, modeling results imply that (1) the multivariate heterogeneity shows the strongest interaction on crash frequency, followed by the spatiotemporal and structural heterogeneities, and (2) the spatial variation is unrelated to the temporal change among crashes in the denoted traffic analysis zones (TAZs). In an attempt to alleviate the coupled crash risks along the coordinated arterials, the study emphasizes the necessity of dividing the subcontrol traffic areas in real time according to the correlative degree of crash distribution. Meanwhile, the modeling framework with multiple heterogeneities can be applied for the safety analysis of other urban roads.

Town Traffic Safety Evaluation Model Based on PSR – SPA

ICCTP 2011 ◽  
2011 ◽  
Author(s):  
Jianxiao Ma ◽  
Taowei Yan ◽  
Li Lin ◽  
Jingwen Jiang
Keyword(s):  
Traffic Safety ◽  
Evaluation Model ◽  
Safety Evaluation ◽  
Model Based

Using claims prediction model for road safety evaluation

2001 ◽  
Vol 28 (5) ◽  
pp. 804-812 ◽  
Author(s):  
Paul de Leur ◽  
Tarek Sayed
Keyword(s):  
Prediction Model ◽  
Road Safety ◽  
Claims Data ◽  
Safety Evaluation ◽  
Safety Analysis ◽  
Insurance Claims ◽  
Insurance Claim ◽  
Auto Insurance ◽  
Improvement Programs ◽  
Traffic Collision

Road safety analysis is typically undertaken using traffic collision data. However, the collision data often suffer from quality and reliability problems. These problems can inhibit the ability of road safety engineers to evaluate and analyze road safety performance. An alternate source of data that characterize the events of a traffic collision is the records that become available from an auto insurance claim. In settling an auto insurance claim, a claim adjuster must make an assessment and determination of the circumstances of the event, recording important contributing factors that led to the crash occurrence. As such, there is an opportunity to access and use the claims data in road safety engineering analysis. This paper presents the results of an initial attempt to use auto insurance claims records in road safety evaluation by developing and applying a claim prediction model. The prediction model will provide an estimate of the number of auto insurance claims that can be expected at signalized intersections in the Vancouver area of British Columbia, Canada. A discussion of the usefulness and application of the claim prediction model will be provided together with a recommendation on how the claims data could be utilized in the future.Key words: road safety improvement programs, auto insurance claims, road safety analysis, prediction models.

Safety Evaluation of Destination Lighting Treatment at Stop Controlled Cross-Intersections

2018 ◽  
Vol 2672 (16) ◽  
pp. 113-121 ◽  
Author(s):  
Amrita Goswamy ◽  
Shauna Hallmark ◽  
Theresa Litteral ◽  
Michael Pawlovich
Keyword(s):  
Rural Areas ◽  
Negative Binomial ◽  
Safety Evaluation ◽  
Negative Binomial Regression ◽  
State Agencies ◽  
Crash Frequency ◽  
Binomial Regression ◽  
Manual Selection ◽  
Roadway Lighting ◽  
Selection Of

Intersection crashes during nighttime hours may occur because of poor driver visual cognition of conflicting traffic or intersection presence. In rural areas, the only source of lighting is typically provided by vehicle headlights. Roadway lighting enhances driver recognition of intersection presence and visibility of signs and markings. Destination lighting provides some illumination for the intersection but is not intended to fully illuminate all approaches. Destination lighting has been widely used in Iowa but the effectiveness has not been well documented. This study, therefore, sought to evaluate the effect on safety of destination lighting at rural intersections. As part of an extensive data collection effort, locations with destination/street lighting were gathered with the assistance of several state agencies. After manual selection of a similar number of control intersections, propensity score matching using the caliper width technique was used to match 245 treatments with 245 control sites. Negative binomial regression was used to evaluate crash frequency data. The presence of destination lighting at stop-controlled cross-intersections generally reduced the night-to-day crash ratio by 19%. The presence of treatment or destination lighting was associated with a 33%–39% increase in daytime crashes across all models but was associated with an 18%–33% reduction in nighttime crashes. Injuries in nighttime crashes decreased by 24% and total nighttime crashes reduced by 33%. Property damage crashes were reduced by 18%.

scholarly journals Probabilistic Safety Analysis of High Speed and Conventional Lines Using Bayesian Networks

2016 ◽  
Author(s):  
Zacarias Grande Andrade ◽  
Enrique Castillo Ron ◽  
Alan O'Connor ◽  
Maria Nogal
Keyword(s):  
Bayesian Network ◽  
High Speed ◽  
Human Error ◽  
Driver Behavior ◽  
Safety Evaluation ◽  
Safety Analysis ◽  
Human Errors ◽  
Maintenance Costs ◽  
Railway Line ◽  
Probabilistic Safety

A Bayesian network approach is presented for probabilistic safety analysis (PSA) of railway lines. The idea consists of identifying and reproducing all the elements that the train encounters when circulating along a railway line, such as light and speed limit signals, tunnel or viaduct entries or exits, cuttings and embankments, acoustic sounds received in the cabin, curves, switches, etc. In addition, since the human error is very relevant for safety evaluation, the automatic train protection (ATP) systems and the driver behavior and its time evolution are modelled and taken into account to determine the probabilities of human errors. The nodes of the Bayesian network, their links and the associated probability tables are automatically constructed based on the line data that need to be carefully given. The conditional probability tables are reproduced by closed formulas, which facilitate the modelling and the sensitivity analysis. A sorted list of the most dangerous elements in the line is obtained, which permits making decisions about the line safety and programming maintenance operations in order to optimize them and reduce the maintenance costs substantially. The proposed methodology is illustrated by its application to several cases that include real lines such as the Palencia-Santander and the Dublin-Belfast lines.DOI: http://dx.doi.org/10.4995/CIT2016.2016.3428

scholarly journals Social Force Model-Based Safety Evaluation of Intersections in Arterials Considering the Pedestrian Yield Rule

2021 ◽  
Vol 18 (23) ◽  
pp. 12461
Author(s):  
Jiao Yao ◽  
Yuhang Li ◽  
Jiaping He
Keyword(s):  
Evaluation Model ◽  
Safety Evaluation ◽  
Force Model ◽  
Social Force ◽  
Trajectory Data ◽  
Entropy Weight ◽  
Social Force Model ◽  
Entropy Weight Method ◽  
Safety Models ◽  
Pedestrian Crossing

To enhance the safety of pedestrians crossing the street, a series of new regulations regarding pedestrian yield has been proposed and widely implemented across cities. In this study, we first made some improvements to the social force model, in which pedestrian crossing at the intersection, drivers’ psychology of giving way, vehicle yield to pedestrians, vehicle yield in different directions, the influence of pedestrians crossing boundaries, and signal lamp groups on pedestrian behavior were considered. Furthermore, pedestrian crossing and vehicle yield safety models were established, based on which the comprehensive safety evaluation model of intersections in arterials was established, in which two indices—(1) the safety degree of pedestrian crossings and (2) vehicle acceleration interference—were combined with the entropy weight method. Finally, four types of intersections in arterials were studied using a simulation: the intersections between different levels of arterials, and intersections with one-time and two-times pedestrian crossings. Moreover, safety evaluation and analysis of those intersections, considering the rule of pedestrian yield, were conducted combined with the trajectory data from the VISSIM simulation. The relevant results showed that for pedestrians crossing the street, the pedestrian safety of two-time crossing is significantly higher than that of one-time crossing, and compared with the arterial, the pedestrian crossing distance of the sub-arterial is shorter, and the pedestrian perception is safer. Moreover, due to the herd psychology effect, the increase in pedestrian flow volume improves the safety perception of pedestrians at the intersection.

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