Development and evaluation of a web-based software for crash data collection, processing and analysis

Montella, Alfonso; Chiaradonna, Salvatore; Criscuolo, Giorgio; Martino, Salvatore De

doi:10.1016/j.aap.2017.01.013

Cited by 22 publications

(15 citation statements)

References 11 publications

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“…Montella et al [9] and Campisi et al [3] have proposed the same kind of architecture when designing a web application to collect crash data. The ACID properties of relational databases protect them from operations that can corrupt data.…”

Section: Crash Data Loadmentioning

confidence: 99%

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Design and implementation of an offline-first road crash data collection system

Tiam¹,

Gueye²,

WADE³

et al. 2022

World J. Adv. Res. Rev.

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Road traffic accidents (RTAs) are a global burden that particularly affects people in developing countries. According to the World Health Organization, having reliable and precise data is necessary to raise the alert on the scale of road accidents and convince decision-makers of the need to take action. Each year, nearly 700 people lose their lives due to accidents on Senegalese roads. In Senegal, dis-aggregated data related to accidents are rare due to very significant under-recording. Most of these data are in a non-computerized form and their collection methods differ from one side to the other among road safety actors. The task of collecting data is simply considered of secondary importance for certain road safety actors. The disparity between the collection methods as well as collected data and the non computerized collection processes limit the possibility of having a real knowledge of the phenomenon of road accidents. In this work, we present a global solution of a road crash data collection and management system. In particular, we will focus here on the collection component with an application that aims to federate data collection processes of all road safety actors in Senegal. It uses a collection guide designed after a review of road accident data guides in Senegal and in other regions of the world. It also implements a parallel collection methodology, i.e the possibility of several agents working on collecting data for the same accident.

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Section: Crash Data Loadmentioning

confidence: 99%

“…The studied papers [3] [4] [10] [6] [9] use relational databases to store crash related data. There used to be four or more entities in the database intended to store crash data.…”

Section: Crashes Data Storesmentioning

confidence: 99%

Design and implementation of an offline-first road crash data collection system

Tiam¹,

Gueye²,

WADE³

et al. 2022

World J. Adv. Res. Rev.

View full text Add to dashboard Cite

show abstract

“…Public authorities by reporting crashes with the aid of GPS-based applications would enable automatic identification and linkage of the crash locations with the road environment conditions. Advanced GPS-applications are already being used in several new crash reporting systems such as Traffic and Criminal Software (TRACS) in the US, Collision Recording and Sharing (CRASH) in the UK, PRC and ReGIS in Italy (Department for Transport, 2011c; Montella et al, 2017;Ogle, 2007). Improved accuracy of crash locations combined with detailed real-time traffic, weather and geometric information would enable the identification of the actual conditions responsible for the crash occurrence.…”

Section: Intelligent Crash Reporting Systemsmentioning

confidence: 99%

“…Moreover, purchasing and developing new crash reporting systems as well as training of data collecting teams is costly. The time required to fill in crash report forms is also likely to be increased, at least when a new system is newly introduced (Montella et al, 2017). The vision for prefect crash databases may be utopic, however now it is more 14 timely and necessary than ever to work on improving crash data in anticipation of new and advanced 15 road safety analyses that will lead to the development of more successful preventive measures and technologies.…”

Section: Intelligent Crash Reporting Systemsmentioning

confidence: 99%

Crash data quality for road safety research: Current state and future directions

Imprialou

Quddus

2019

Accident Analysis & Prevention

138

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Crash databases are one of the primary data sources for road safety research. Therefore, their quality is fundamental for the accuracy of crash analyses and, consequently the design of effective countermeasures. Although crash data often suffer from correctness and completeness issues, these are rarely discussed or addressed in crash analyses. Crash reports aim to answer the five "W" questions (i.e. When?, Where?, What?, Who? and Why?) of each crash by including a range of attributes. This paper reviews current literature on the state of crash data quality for each of these questions separately. The most serious data quality issues appear to be: inaccuracies in crash location and time, difficulties in data linkage (e.g. with traffic data) due to inconsistencies in databases, severity misclassification, inaccuracies and incompleteness of involved users' demographics and inaccurate identification of crash contributory factors. It is shown that the extent and the severity of data quality issues are not equal between attributes and the level of impact in road safety analyses is not yet entirely known. This paper highlights areas that require further research and provides some suggestions for the development of intelligent crash reporting systems.

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“…The second issue concerns missing information recorded by the different police forces. Montella et al [49][50][51][52] found that in 36% of the crashes the location was completely missing. Due to these problems, the information reported in the database is often incomplete, making the location of accidents in some cases difficult to determine, in others impossible.…”

Section: Crash Datamentioning

confidence: 99%

Development of Macro-Level Safety Performance Functions in the City of Naples

et al. 2019

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This paper presents macro-level safety performance functions and aims to provide empirical tools for planners and engineers to conduct proactive analyses, promote more sustainable development patterns, and reduce road crashes. In the past decade, several studies have been conducted for crash modeling at a macro-level, yet in Italy, macro-level safety performance functions have neither been calibrated nor used, until now. Therefore, for Italy to be able to fully benefit from applying these models, it is necessary to calibrate the models to local conditions. Generalized linear modelling techniques were used to fit the models, and a negative binomial distribution error structure was assumed. The study used a sample of 15,254 crashes which occurred in the period of 2009–2011 in Naples, Italy. Four traffic analysis zones (TAZ) levels were used, as one of the aims of this paper is to check the extent to which these zoning levels help in addressing the issue. The models were developed by the stepwise forward procedure using explanatory Socio-Demographic (S-D), Transportation Demand Management (TDM), and Exposure variables. The most significant variables were: children and young people placed in re-education projects, population, population aged 65 and above, population aged 25 to 44, male population, total vehicle kilometers traveled, average congestion level, average speed, number of trips originating in the TAZ, number of trips ending in the TAZ, number of total trips and, number of bus stops served per hour. An important result of the study is that children and young people placed in re-education projects negatively affects the frequency of crashes, i.e., it has a positive safety effect. This demonstrates the effectiveness of education projects, especially on children from disadvantaged neighbourhoods.

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Development and evaluation of a web-based software for crash data collection, processing and analysis

Cited by 22 publications

References 11 publications

Design and implementation of an offline-first road crash data collection system

Design and implementation of an offline-first road crash data collection system

Crash data quality for road safety research: Current state and future directions

Development of Macro-Level Safety Performance Functions in the City of Naples

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