Safety diagnosis and road accident analysis: complementary methods and application
Ronni Litz Julien, N Muhlrad
Abstract
Ronni Litz Julien, N Muhlrad
Abstract
Road accidents are a growing concern in developing countries. In order to build safe new roads and to improve safety conditions on existing networks, it is essential to understand thoroughly how and why accidents occur. A safety diagnosis should both provide a description of the accident situation sufficient to point out priorities for action, and give enough insight into accident causation processes to help design countermeasures suited to the local conditions of application. To achieve this, two complementary levels of analysis are required: a statistical data treatment based on comprehensive accident files, and an in-depth investigation of accident causation processes based on a representative sample of accident cases. Both methods involve operational difficulties related to data collection procedures, but two examples of applications, in Cote d'Ivoire and in the Philippines, show how practical solutions can be found and what kind of results can be obtained. (A)
OpenAlex reports 1 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
Road accidents are a growing concern in developing countries. In order to build safe new roads and to improve safety conditions on existing networks, it is essential to understand thoroughly how and why accidents occur. A safety diagnosis should both provide a description of the accident situation sufficient to point out priorities for action, and give enough insight into accident causation processes to help design countermeasures suited to the local conditions of application. To achieve this, two complementary levels of analysis are required: a statistical data treatment based on comprehensive accident files, and an in-depth investigation of accident causation processes based on a representative sample of accident cases. Both methods involve operational difficulties related to data collection procedures, but two examples of applications, in Cote d'Ivoire and in the Philippines, show how practical solutions can be found and what kind of results can be obtained. (A)
Key concepts: Causation, Accident (philosophy), Risk analysis (engineering), Sample (material), Accident analysis, Computer science, Action (physics), Road accident