Differences in road-traffic crash rates during construction and non-contruction times on arterial streets: A comparative statistical analysis

Trabajo presentado en: R-Evolucionando el transporte, XIV Congreso de Ingeniería del Transporte (CIT 2021), realizado en modalidad online los días 6, 7 y 8 de julio de 2021, organizado por la Universidad de BurgosDifferent studies over the past 30 years have shown an increase in the rates of crash frequencies during road construction time, but this trend is not reported as valid for all cities. A question is raised whether higher rates are observed in arterial roads in Bogotá, Colombia. It is possible to apply descriptive statistics and hypothesis tests to prove them and identify the variables that affect the accident rate during road construction. Our research aims to verify the incidence of high impact construction zones, in the crash rate at the arterial road network of Bogotá. We use descriptive statistics and inferential statistical tests to analyze whether crash rates are statistically higher during construction time than during nonconstruction time at the same highway sections considering different crash severities (damages-only, injuries, and fatalities). Our database considered 871 road links that make up 68 artery corridors for the city of Bogota, and 5.450 road construction zones, from 2015 to 2019. An analysis by corridor was performed, in which we identified seven patterns in the behavior of accident rates influenced by the presence of a road intervention in the corridor. Within the patterns, it was evident that some corridors reported an increase in the accident rate during the time of construction, while others showed a decrease in the same comparison. We used the Wilcoxon test to establish the statistical significance of our conclusions, with a significance level of 10%. We also found that those construction interventions that do not require excavation of more than half a meter there was a decrease in the accident severity, as damages-only crashes, diminished during the construction time, while for those interventions that include excavation greater than half a meter there was an increase in overall accident rates during construction time.The research group wishes to thank the engineering faculty of the Universidad Nacional de Colombia, more specifically to the Vice-Dean of Research and Extension, which through the call for Support to Research Seedbeds of the Faculty of Engineering 2019, financed the total development of this research. To the seedbed of research in Infrastructure and Mobility (SIMUN) to which belong the members of this research, to generate the space and time for the development of the activities needed for this research

Comparison of Top-Down and Bottom-Up Road Transport Emissions through High-Resolution Air Quality Modeling in a City of Complex Orography

Vehicular emissions are a predominant source of pollution in urban environments. However, inherent complexities of vehicular behavior are sources of uncertainties in emission inventories (EIs). We compare bottom-up and top-down approaches for estimating road transport EIs in Manizales, Colombia. The EIs were estimated using a COPERT model, and results from both approaches were also compared with the official top-down EI (estimated from IVE methodology). The transportation model PTV-VISUM was used for obtaining specific activity information (traffic volumes, vehicular speed) in bottom-up estimation. Results from COPERT showed lower emissions from the top-down approach than from the bottom-up approach, mainly for NMVOC (−28%), PM10 (−26%), and CO (−23%). Comparisons showed that COPERT estimated lower emissions than IVE, with higher differences than 40% for species such as PM10, NOX, and CH4. Furthermore, the WRF–Chem model was used to test the sensitivity of CO, O3, PM10, and PM2.5 predictions to the different EIs evaluated. All studied pollutants exhibited a strong sensitivity to the emission factors implemented in EIs. The COPERT/top-down was the EI that produced more significant errors. This work shows the importance of performing bottom-up EI to reduce the uncertainty regarding top-down activity data