scholarly journals Exploring European Heavy Goods Vehicle Crashes Using a Three-Level Analysis of Crash Data

2021 ◽  
Author(s):  
Ron Schindler ◽  
Michael Jänsch ◽  
András Bálint ◽  
Heiko Johannsen
Keyword(s):  
System Development ◽  
Information Access ◽  
Safety System ◽  
Crash Data ◽  
The Road ◽  
Access Problems ◽  
Heavy Goods Vehicles ◽  
Causation Analysis ◽  
Level Analysis ◽  
Blind Spots

This paper addresses crashes involving heavy goods vehicles (HGV) in Europe focusing on long-haul trucks weighing 16 tons or more (16t+). The identification of the most critical scenarios and their characteristics is based on a three-level analysis: general crash statistics from CARE addressing all HGVs, results about 16t+ trucks from national crash databases and a detailed study of in-depth crash data from GIDAS, including a crash causation analysis. Most European HGV crashes occur in clear weather, during daylight, on dry roads, outside city limits, and on non-highway roads. Three main scenarios for 16t+ trucks are characterized in-depth: (1) rear-end crashes in which the truck is the striking partner, (2) conflicts during right turn maneuvers of the truck and a cyclist riding alongside and (3) pedestrians crossing the road in front of the truck. Among truck-related crash causes, information admission failures (e.g. distraction) were the main causing factors in 72% of cases in scenario (1) while information access problems (e.g. blind spots) were present for 72% of cases in scenario (2) and 75% of cases in scenario (3). The results provide both a global overview and sufficient depth of analysis in the most relevant cases and thereby aid safety system development.

scholarly journals Exploring European Heavy Goods Vehicle Crashes Using a Three-Level Analysis of Crash Data

2022 ◽  
Vol 19 (2) ◽  
pp. 663
Author(s):  
Ron Schindler ◽  
Michael Jänsch ◽  
András Bálint ◽  
Heiko Johannsen
Keyword(s):  
System Development ◽  
Information Access ◽  
The European Union ◽  
Crash Data ◽  
Road Crashes ◽  
The Road ◽  
Passive Safety Systems ◽  
Road Crash ◽  
Causation Analysis ◽  
Level Analysis

Heavy goods vehicles (HGVs) are involved in 4.5% of police-reported road crashes in Europe and 14.2% of fatal road crashes. Active and passive safety systems can help to prevent crashes or mitigate the consequences but need detailed scenarios based on analysis of region-specific data to be designed effectively; however, a sufficiently detailed overview focusing on long-haul trucks is not available for Europe. The aim of this paper is to give a comprehensive and up-to-date analysis of crashes in the European Union that involve HGVs weighing 16 tons or more (16 t+). The identification of the most critical scenarios and their characteristics is based on a three-level analysis, as follows. Crash statistics based on data from the Community Database on Accidents on the Roads in Europe (CARE) provide a general overview of crashes involving HGVs. These results are complemented by a more detailed characterization of crashes involving 16 t+ trucks based on national road crash data from Italy, Spain, and Sweden. This analysis is further refined by a detailed study of crashes involving 16 t+ trucks in the German In-Depth Accident Study (GIDAS), including a crash causation analysis. The results show that most European HGV crashes occur in clear weather, during daylight, on dry roads, outside city limits, and on nonhighway roads. Three main scenarios for 16 t+ trucks are characterized in-depth: rear-end crashes in which the truck is the striking partner, conflicts during right turn maneuvers of the truck with a cyclist riding alongside, and pedestrians crossing the road in front of the truck. Among truck-related crash causes, information admission failures (e.g., distraction) were the main crash causation factor in 72% of cases in the rear-end striking scenario while information access problems (e.g., blind spots) were present for 72% of cases in the cyclist scenario and 75% of cases in the pedestrian scenario. The three levels of data analysis used in this paper give a deeper understanding of European HGV crashes, in terms of the most common crash characteristics on EU level and very detailed descriptions of both kinematic parameters and crash causation factors for the above scenarios. The results thereby provide both a global overview and sufficient depth of analysis of the most relevant cases and aid safety system development.

Academic Librarians and the Road to Success: Facilitating Undergraduate Achievement Through Information Access

2013 ◽  
Author(s):  
Lisa M. Given
Keyword(s):  
Academic Success ◽  
Information Access ◽  
Physical Space ◽  
Literacy Programs ◽  
Academic Librarians ◽  
The Road ◽  
Premier Cycle ◽  
Access Problems ◽  
Role Of Information

Presents qualitative interview data exploring academic librarians’ perceptions of undergraduates and the role of information resources, design of physical space, and information literacy programs in facilitating academic success. Findings point to information access problems given the university’s socio-political context, varied definitions of success, and frustrations with technology and space planning.Cette étude présente des données d’entrevues qualitatives explorant les perceptions des bibliothécaires universitaires au sujet des étudiants de premier cycle et le rôle des ressources informationnelles, de l’aménagement de l’espace physique et des programmes de littératie contribuant à la réussite universitaire. Les résultats orientent vers les problèmes de l’accès à l’information selon le contexte sociopolitique universitaire, les différentes définitions de la réussite et les frustrations ressenties envers la technologie et l’aménagement de l’espace. 

scholarly journals The Awareness of Blind Spot Area in Heavy Goods Vehicle (HGV)

2019 ◽  
Vol 8 (12) ◽  
pp. 5619-5623
Keyword(s):  
Blind Spot ◽  
Truck Drivers ◽  
Road User ◽  
The Road ◽  
Spot Area ◽  
Road Users ◽  
Heavy Goods Vehicles ◽  
The Government ◽  
Good Vehicle ◽  
Blind Spots

This paper is to demonstrate the awareness of blind spot area in heavy goods vehicles (HGV) towards the road user. A blind spot is an area or zone that cannot be directly observe by the driver. Usually, the weaknesses in the blind spot area resulted in accident between the vehicle as many drivers did not alert or have awareness on the blind spot area especially in heavy goods vehicle. The objective of this paper is to identify the awareness on the blind spot area in heavy goods vehicles to the road users. To achieve the objective, a questionnaire survey has been conducted to the road user. About 100 drivers randomly pick to answer the survey and they are consisting of non-truck drivers that drive a car, van and motorcycle. The results reveal that even the respondents know about the blind spot in heavy good vehicle, but the awareness in the of blind spot area still less where they mistake on the exact location of blind spot. Typically, the only zone that they know as the blind spot for heavy goods vehicle is at the back area. Therefore, it is suggested that the government to improve the awareness of blind spot areas within the drivers through restructure the system inside driving school by give more attention on the blind spot for heavy goods vehicle, make a campaign on the awareness of blind spot in heavy goods vehicle to remind again the road users about the area of blind spots, and establish a standard direct vision in heavy goods vehicle. Keywords: Blind spot, heavy good

Development and Application of Quality Control System for Highway Subgrade Construction

2019 ◽  
Vol 2 (5) ◽  
Author(s):  
Tong Wang
Keyword(s):  
Quality Control ◽  
Real Time ◽  
Detection Method ◽  
System Development ◽  
Effective Control ◽  
Construction Process ◽  
Development Mode ◽  
The Road ◽  
Whole Process

The compaction quality of the subgrade is directly related to the service life of the road. Effective control of the subgrade construction process is the key to ensuring the compaction quality of the subgrade. Therefore, real-time, comprehensive, rapid and accurate prediction of construction compaction quality through informatization detection method is an important guarantee for speeding up construction progress and ensuring subgrade compaction quality. Based on the function of the system, this paper puts forward the principle of system development and the development mode used in system development, and displays the development system in real-time to achieve the whole process control of subgrade construction quality.

scholarly journals Evaluating the Safety Risk of Rural Roadsides Using a Bayesian Network Method

2019 ◽  
Vol 16 (7) ◽  
pp. 1166 ◽  
Author(s):  
Tianpei Tang ◽  
Senlai Zhu ◽  
Yuntao Guo ◽  
Xizhao Zhou ◽  
Yang Cao
Keyword(s):  
Bayesian Network ◽  
Low Cost ◽  
Road Networks ◽  
Access Point ◽  
Safety Risk ◽  
Crash Data ◽  
Risk Levels ◽  
The Road ◽  
Run Off ◽  
Point Density

Evaluating the safety risk of rural roadsides is critical for achieving reasonable allocation of a limited budget and avoiding excessive installation of safety facilities. To assess the safety risk of rural roadsides when the crash data are unavailable or missing, this study proposed a Bayesian Network (BN) method that uses the experts’ judgments on the conditional probability of different safety risk factors to evaluate the safety risk of rural roadsides. Eight factors were considered, including seven factors identified in the literature and a new factor named access point density. To validate the effectiveness of the proposed method, a case study was conducted using 19.42 km long road networks in the rural area of Nantong, China. By comparing the results of the proposed method and run-off-road (ROR) crash data from 2015–2016 in the study area, the road segments with higher safety risk levels identified by the proposed method were found to be statistically significantly correlated with higher crash severity based on the crash data. In addition, by comparing the respective results evaluated by eight factors and seven factors (a new factor removed), we also found that access point density significantly contributed to the safety risk of rural roadsides. These results show that the proposed method can be considered as a low-cost solution to evaluating the safety risk of rural roadsides with relatively high accuracy, especially for areas with large rural road networks and incomplete ROR crash data due to budget limitation, human errors, negligence, or inconsistent crash recordings.

scholarly journals 3C.006 Enabling journalists to contribute to the road safety system: experience from Nepal

2021 ◽  
Author(s):  
Puspa Raj Pant ◽  
Sudhamshu Dahal ◽  
Kannan Krishnaswamy ◽  
Sunil Kumar Joshi ◽  
Julie Mytton
Keyword(s):  
Road Safety ◽  
Safety System ◽  
The Road

NSTX-U Personnel Safety System: Safety Instrumented System Development and Design

2021 ◽  
pp. 1-8
Author(s):  
Joseph R. Petrella ◽  
Timothy Stevenson ◽  
Mark Cropper ◽  
Paul Sichta ◽  
Michael D’Agostino ◽  
...  
Keyword(s):  
System Development ◽  
Safety System ◽  
System Safety ◽  
Personnel Safety

Legal and organizational basis for ensuring road safety in the Ukrainian SSR in 1948–1953

2021 ◽  
pp. 39-56
Author(s):  
Maksim P. Tishakov
Keyword(s):  
Road Safety ◽  
National Policy ◽  
Road Transport ◽  
Safety System ◽  
Legal Basis ◽  
Socialist Republic ◽  
Soviet Socialist Republic ◽  
Local Conditions ◽  
The Road ◽  
The Government

The work, based on previously little available for research, as well as materials and documents found in archival institutions, reflects the legal basis for ensuring road safety in 1948-1953, the state and organizational and legal measures taken in the field of combating accidents in road transport at the republican level by the example Ukrainian Soviet Socialist Republic. Attention is focused on the key problems that determine the development of the road safety system, the measures taken, their effectiveness, mistakes and achievements. Measures to counteract accidents in vehicles are investigated from a historical and legal standpoint, a critical and detailed analysis of decrees and orders of the government, departmental regulatory legal acts. It was found that the presence of a significant number of administrative decisions of the republican authorities of Soviet Ukraine, although it was a rather progressive step for its time, did not fully take into account the reality of achieving the set goals, local conditions and peculiarities. At the same time, the functioning of the emerging road safety system was significantly hampered by the lack of a unified national policy in the context of the rapid growth and development of the country’s automobile and road complex.

scholarly journals Lower Volumes, Higher Speeds: Changes to Crash Type, Timing, and Severity on Urban Roads from COVID-19 Stay-at-Home Policies

2021 ◽  
pp. 036119812110444
Author(s):  
Jonathan Stiles ◽  
Armita Kar ◽  
Jinhyung Lee ◽  
Harvey J. Miller
Keyword(s):  
Logistic Regression ◽  
Traffic Safety ◽  
Travel Demand ◽  
Multinomial Logistic Regression ◽  
High Volume ◽  
Time Of Day ◽  
Bayesian Hierarchical ◽  
Crash Data ◽  
The Road ◽  
At Home

Stay-at-home policies in response to COVID-19 transformed high-volume arterials and highways into lower-volume roads, and reduced congestion during peak travel times. To learn from the effects of this transformation on traffic safety, an analysis of crash data in Ohio’s Franklin County, U.S., from February to May 2020 is presented, augmented by speed and network data. Crash characteristics such as type and time of day are analyzed during a period of stay-at-home guidelines, and two models are estimated: (i) a multinomial logistic regression that relates daily volume to crash severity; and (ii) a Bayesian hierarchical logistic regression model that relates increases in average road speeds to increased severity and the likelihood of a crash being fatal. The findings confirm that lower volumes are associated with higher severity. The opportunity of the pandemic response is taken to explore the mechanisms of this effect. It is shown that higher speeds were associated with more severe crashes, a lower proportion of crashes were observed during morning peaks, and there was a reduction in types of crashes that occur in congestion. It is also noted that there was an increase in the proportion of crashes related to intoxication and speeding. The importance of the findings lay in the risk to essential workers who were required to use the road system while others could telework from home. Possibilities of similar shocks to travel demand in the future, and that traffic volumes may not recover to previous levels, are discussed, and policies are recommended that could reduce the risk of incapacitating and fatal crashes for continuing road users.

The HRA-Based Road Crash Data

2019 ◽  
pp. 528-543
Author(s):  
Khashayar Hojjati-Emami ◽  
Balbir S. Dhillon ◽  
Kouroush Jenab
Keyword(s):  
Risk Assessment ◽  
Data Collection ◽  
Reliability Assessment ◽  
Behavioral Characteristics ◽  
Road Accidents ◽  
Human Reliability ◽  
Human Errors ◽  
Crash Data ◽  
The Road ◽  
To Come

Human error has played a critical role in the events precipitating the road accidents. Such accidents can be predicted and prevented by risk assessment, in particular assessing the human contribution to risk. As part of the Human Reliability Assessment (HRA) process, it is usually necessary not only to define what human errors can occur, but how often they will occur. Lack of understanding of the failure distribution characteristics of drivers on roads at any given time is a factor impeding the development of human reliability assessment and prediction of road accidents in order to take best proactive measures. The authors developed the complete investigation methodology for crash data collection. Furthermore, they have experimentally tested the proposed predictive behavioral characteristics of drivers in light of their instantaneous error rate over the course of driving period to assist processing and analysis of data collection as part of risk assessment. The findings of this research can assist road safety authorities to collect the necessary data, to better understand the behavioral characteristics of drivers on roads, to make more accurate risk assessments and finally to come up with right preventive measures.

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