How do road infrastructure investments affect Powered Two-Wheelers crash risk?
Metadata
Show full item recordEditorial
Elsevier
Materia
Road infrastructure investment Road infrastructure maintenance Road safety Vulnerable road user Powered two-wheeler Motorcycle Random parameters model Seguridad vial Inversión en carreteras Gasto en mantenimiento
Date
2023-05-10Referencia bibliográfica
Navarro-Moreno, J., de Oña, J., Calvo-Poyo, F., 2023. How do road infrastructure investments affect Powered Two-Wheelers crash risk? Transp. Policy 138, 60–73.
Sponsorship
This study was carried out in the framework of the project RTI 2018-101770-B-I00 “Investment in roads and road safety: An international analysis (INCASE)”, financed by: MCIN/AEI/10.13039/501100011033/ERDF, within Spain's National Program of R + D + i Oriented to Societal Challenges. Funding for open access charge: Universidad de Granada.Abstract
The drivers of Powered Two-Wheelers (PTWs) pertain to the collective of so-called vulnerable road users. Crashes have scarcely decreased for these roadway users in recent years, whereas among other users, e.g. cars users, they have declined considerably. Meanwhile, the use of PTWs has risen sharply worldwide. This situation adds a further concern to transportation policies and makes evident the need to explore factors involved in PTW crashes. Yet there is a lack of studies specifically about road safety for PTWs. The present study therefore aspires to advance in the knowledge of the factors affecting PTW crashes on interurban roadways, by means of analyzing the effects of some variables not considered previously in this type of studies —mainly economic resources invested in roads—while also accounting specifically for the exposure to risk of PTWs (veh-km), along with relevant variables related to road traffic, the roadway infrastructure, and socioeconomic, meteorological and legislative factors. To this end, and bearing in mind the latest advancements of incorporating unobserved heterogeneity in count data models, different configurations of random parameters negative binomial models for data panels are presented. The realm of study is the network of national roads in Spain, distributed over 43 provinces, and the time period between 2007 and 2015. The results show significant associations for 11 of the variables considered: annual and accumulated investment in construction, expense on maintenance, proportion of motorways, light and heavy vehicle traffic, per capita GDP, age, unemployment rate, price of gasoline, and modification of the demerit point system (DPS). With respect to transport policy implications, the findings provided in this study may serve to monitor the effects of economic resources allocated to road construction and maintenance —along with other measures, such as gasoline prices and DPS—on PTWs safety.