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Pedestrian fatality and natural light: Evidence from South Africa using a Bayesian approach

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dc.contributor.author Das, Sonali
dc.date.accessioned 2014-08-27T12:39:39Z
dc.date.available 2014-08-27T12:39:39Z
dc.date.issued 2014-02
dc.identifier.citation Das, S. 2014. Pedestrian fatality and natural light: Evidence from South Africa using a Bayesian approach. Economic Modelling, vol. 38, pp 311-315 en_US
dc.identifier.issn 0264-9993
dc.identifier.uri http://ac.els-cdn.com/S0264999313005403/1-s2.0-S0264999313005403-main.pdf?_tid=d958cc9c-2dd3-11e4-aa52-00000aab0f26&acdnat=1409135043_cf7e37c21c46d8984a97a315b833934f
dc.identifier.uri http://hdl.handle.net/10204/7645
dc.description Copyright: 2014 Elsevier. This is the pre/post print version. The definitive version is published in Economic Modelling, vol. 38, pp 311-315 en_US
dc.description.abstract In this paper we use a Bayesian approach to investigate the relationship between pedestrian fatality records from Tshwane and time of fatality. Time of fatality is used as a proxy to reflect the presence of effective lighting, not precluding the presence of any other lighting intervention. In South Africa, for a large proportion (60%) walking is a primary means of transport, with about 45% of all deaths on South African roads being pedestrian. Such reports call for attention to be devoted to analyzing pedestrian fatalities records to locate possible directions of intervention. Results fromthis analysis reveals that not only does time of day influence pedestrian fatality counts, but also within road types, municipal roads were the most prone to pedestrian fatalities followed by national roads, while the regional roads were the least prone to pedestrian fatalities. en_US
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.relation.ispartofseries Workflow;13242
dc.subject Pedestrian fatality records en_US
dc.subject Bayesian approach en_US
dc.subject Natural light en_US
dc.subject Infrastructure improvements en_US
dc.title Pedestrian fatality and natural light: Evidence from South Africa using a Bayesian approach en_US
dc.type Article en_US
dc.identifier.apacitation Das, S. (2014). Pedestrian fatality and natural light: Evidence from South Africa using a Bayesian approach. http://hdl.handle.net/10204/7645 en_ZA
dc.identifier.chicagocitation Das, Sonali "Pedestrian fatality and natural light: Evidence from South Africa using a Bayesian approach." (2014) http://hdl.handle.net/10204/7645 en_ZA
dc.identifier.vancouvercitation Das S. Pedestrian fatality and natural light: Evidence from South Africa using a Bayesian approach. 2014; http://hdl.handle.net/10204/7645. en_ZA
dc.identifier.ris TY - Article AU - Das, Sonali AB - In this paper we use a Bayesian approach to investigate the relationship between pedestrian fatality records from Tshwane and time of fatality. Time of fatality is used as a proxy to reflect the presence of effective lighting, not precluding the presence of any other lighting intervention. In South Africa, for a large proportion (60%) walking is a primary means of transport, with about 45% of all deaths on South African roads being pedestrian. Such reports call for attention to be devoted to analyzing pedestrian fatalities records to locate possible directions of intervention. Results fromthis analysis reveals that not only does time of day influence pedestrian fatality counts, but also within road types, municipal roads were the most prone to pedestrian fatalities followed by national roads, while the regional roads were the least prone to pedestrian fatalities. DA - 2014-02 DB - ResearchSpace DP - CSIR KW - Pedestrian fatality records KW - Bayesian approach KW - Natural light KW - Infrastructure improvements LK - https://researchspace.csir.co.za PY - 2014 SM - 0264-9993 T1 - Pedestrian fatality and natural light: Evidence from South Africa using a Bayesian approach TI - Pedestrian fatality and natural light: Evidence from South Africa using a Bayesian approach UR - http://hdl.handle.net/10204/7645 ER - en_ZA


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