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Journal Article

Citation

Colonna P, Intini P, Berloco N, Ranieri V. Eur. Transp. Res. Rev. 2018; 10(1): e5.

Copyright

(Copyright © 2018, European Conference of Transport Research Institutes, Publisher Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s12544-017-0274-4

PMID

unavailable

Abstract

PURPOSEThe main purpose was to integrate two strategies for road safety analyses (qualitative: audits, inspections; and quantitative: accident predictions) and develop a possible protocol for the safety interventions on existing two-lane rural road segments. Those road sections do not typically belong to the TEN-network, to which the 2008/96/EC Directive is mainly oriented. Hence, they could lack of methods for designing safety-based interventions. The main research questions were: Which possible problems can arise from the application of this protocol to real cases? Which data are practically needed? Which possible solutions can be provided for the highlighted problems? MethodsThe integrated protocol, including: 1) the HSM predictive method, 2) the EU Regulations, 3) the local road design standards, 4) some research developments; is applied to real two-lane rural road segments requiring safety-based interventions. Its application is divided in the typical road safety analysis stages.

RESULTSA wide list of possible problems was highlighted and addressed: 1) lack of data, 2) difficult comparison with current road standards in order to identify safety problems, 3) lack of methods for evaluating the skidding risk along the layout, 4) setting speed limits, 5) need for optimizing the selection of countermeasures based on their aims and their timely application, in different recurrent situations, 6) availability and comparison of predictive methods.

CONCLUSIONSBased on the problems and solutions discussed, main advantages (1) the systematic approach, 2) the quantitative assessment of benefits, 3) the possible transferability) and disadvantages (difficulties in overcoming the lack of data and calibrated accident prediction models) of the method were remarked.


Language: en

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