Statistical Tests on Poisson Variables for Road Safety Evaluation

1981 ◽  
pp. 47-66
Author(s):  
S. Lassarre
Keyword(s):  
Road Safety ◽  
Statistical Tests ◽  
Safety Evaluation

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.

Study on Road Safety Evaluation of Subjectivity and Objectivity Based on Cloud Theory

CICTP 2012 ◽  
2012 ◽  
Author(s):  
Xiao-huan Zhou ◽  
Zhi-zhong Li ◽  
Zhong-yin Guo ◽  
Xiao-an Wang
Keyword(s):  
Road Safety ◽  
Safety Evaluation ◽  
Cloud Theory

Evaluating the Effectiveness of Norway’s “Speak Out!” Road Safety Campaign: The Logic of Causal Inference in Road Safety Evaluation Studies

2000 ◽  
Vol 1717 (1) ◽  
pp. 66-75 ◽  
Author(s):  
Rune Elvik
Keyword(s):  
Causal Inference ◽  
Road Safety ◽  
Evaluation Studies ◽  
Evaluation Research ◽  
Percent Level ◽  
Safety Evaluation ◽  
Age Group ◽  
Back Seat ◽  
Before And After ◽  
The Relationship

The effects on road safety of the “Speak out!” road safety campaign are evaluated. The campaign, which began in Sogn og Fjordane County in Norway in 1993, is targeted toward teenagers and calls on car passengers to act as back-seat drivers and “Speak out!” to drivers about unsafe driving. The campaign’s effects were evaluated by means of two before-and-after studies and and a multivariate Poisson regression analysis. The results of these evaluation studies were very similar. The number of teenagers 16 to 19 years old who were killed or injured was reduced by about 10 percent; the number of occupants in this age group who were killed or injured was reduced by about 15 percent; and the number of car passengers who were killed or injured was reduced by about 30 percent. The number of killed or injured car drivers 16 to 19 years old did not change. Only the reduction among car passengers was statistically significant at the 10 percent level. It is nevertheless concluded that the “Speak out!” campaign has probably been effective in reducing the number of teenagers killed or injured in Sogn og Fjordane. This conclusion is based on a careful discussion of the logic of causal inference in nonexperimental evaluation research. Seven criteria are proposed for attributing causality to the relationship between a measure and changes in the dependent variable that the measure is intended to influence. The majority of these criteria were met in evaluations of the “Speak out!” campaign.

scholarly journals Road safety evaluation through automatic extraction of road horizontal alignments from Mobile LiDAR System and inductive reasoning based on a decision tree

2018 ◽  
Vol 146 ◽  
pp. 334-346 ◽  
Author(s):  
José Antonio Martín-Jiménez ◽  
Santiago Zazo ◽  
José Juan Arranz Justel ◽  
Pablo Rodríguez-Gonzálvez ◽  
Diego González-Aguilera
Keyword(s):  
Decision Tree ◽  
Road Safety ◽  
Inductive Reasoning ◽  
Safety Evaluation ◽  
Automatic Extraction ◽  
Lidar System

scholarly journals The Correlation between Vehicle Vertical Dynamics and Deep Learning-Based Visual Target State Estimation: A Sensitivity Study

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 4870 ◽  
Author(s):  
Yannik Weber ◽  
Stratis Kanarachos
Keyword(s):  
Traffic Congestion ◽  
Vehicle Dynamics ◽  
Road Safety ◽  
Safety Evaluation ◽  
Sensitivity Study ◽  
Vehicle Suspension ◽  
Automated Vehicles ◽  
Detection And Tracking ◽  
First Time

Automated vehicles will provide greater transport convenience and interconnectivity, increase mobility options to young and elderly people, and reduce traffic congestion and emissions. However, the largest obstacle towards the deployment of automated vehicles on public roads is their safety evaluation and validation. Undeniably, the role of cameras and Artificial Intelligence-based (AI) vision is vital in the perception of the driving environment and road safety. Although a significant number of studies on the detection and tracking of vehicles have been conducted, none of them focused on the role of vertical vehicle dynamics. For the first time, this paper analyzes and discusses the influence of road anomalies and vehicle suspension on the performance of detecting and tracking driving objects. To this end, we conducted an extensive road field study and validated a computational tool for performing the assessment using simulations. A parametric study revealed the cases where AI-based vision underperforms and may significantly degrade the safety performance of AVs.

AHP to Appraise the Traffic Safety of the Express Way

2011 ◽  
Vol 48-49 ◽  
pp. 157-163
Author(s):  
Dan Yu ◽  
Yi Hu Wu ◽  
Zhi Xiang Hou ◽  
Wen Jun Liu ◽  
Ji Guang Zhang
Keyword(s):  
Traffic Safety ◽  
Road Safety ◽  
Comprehensive Evaluation ◽  
Evaluation Model ◽  
Safety Evaluation ◽  
Evaluation Index System ◽  
The Road ◽  
Comprehensive Evaluation Model ◽  
The Impact ◽  
Fuzzy Interval

The internal structure of the road safety system is extremely complex and it is affected by a lot of factors, each factor weights can not be fully established. In this article, we expressed the attribute value with a fuzzy interval number, the comprehensive appraise to the impact of traffic safety with emphasis on "people", "car" "road" in the "road". First of all, establishing evaluation index system, and form the judging matrix by AHP; then, it can be acquired a method of traffic safety evaluation by using the comprehensive evaluation model of the fuzzy interval.

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