Abstract
Brazil's road traffic mortality rates have been increasing since the 1960s and in 2003 road traffic crashes in Brazil were responsible for over 26 percent of fatal injuries. Some actions need to be taken to make it safer, hence, we have proposed, implemented, and deployed a support system that predicts and generates, based on the prediction, a program-card for a Federal agency responsible for patrolling highways which cross most of the big Brazilian cities. We used the data from the Federal Highway Police (PRF) about road accidents to test the performance of the generated models and demonstrate the designed dashboard. We obtained a better performance than the baseline of comparison on the three groups used on the study: Alcohol_drugs, lack_attention and aggressive driving, reaching a R2 score of 0.440, 0.688 and 0.453 respectively.
Original language | English |
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Title of host publication | 2020 IEEE International Smart Cities Conference, ISC2 2020 |
Publisher | IEEE |
ISBN (Electronic) | 9781728182940 |
DOIs | |
Publication status | Published - 28 Sept 2020 |
Externally published | Yes |
Event | IEEE International Smart Cities Conference, ISC2 2020: Smart Cities Solutions for New Challenges, Including a Pandemic - Virtual Conference, United States Duration: 28 Sept 2020 → 1 Oct 2020 https://attend.ieee.org/isc2-2020/ |
Conference
Conference | IEEE International Smart Cities Conference, ISC2 2020 |
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Abbreviated title | ISC2 2020 |
Country/Territory | United States |
City | Virtual Conference |
Period | 28/09/20 → 1/10/20 |
Internet address |
Keywords
- Forecasting
- Hotspot Prediction
- Machine Learning
- Public Security
- Road Accident Prediction
- n/a OA procedure