Intelligent collision risk detection in medium-sized cities of developing countries, using naturalistic driving: A review
Traffic accidents are one of the most serious problems worldwide, being one of the leading causes of death and economic loss in the world. Low- and middle-income countries, mainly their medium-sized cities, are among the most affected by this problem. 93% of traffic accidents occur in low and middle...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2022-12-01
|
| Series: | Journal of Traffic and Transportation Engineering (English ed. Online) |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2095756422000848 |
| _version_ | 1797960962730360832 |
|---|---|
| author | Juan Jose Paredes Santiago Felipe Yepes Ricardo Salazar-Cabrera Álvaro Pachón de la Cruz Juan Manuel Madrid Molina |
| author_facet | Juan Jose Paredes Santiago Felipe Yepes Ricardo Salazar-Cabrera Álvaro Pachón de la Cruz Juan Manuel Madrid Molina |
| author_sort | Juan Jose Paredes |
| collection | DOAJ |
| description | Traffic accidents are one of the most serious problems worldwide, being one of the leading causes of death and economic loss in the world. Low- and middle-income countries, mainly their medium-sized cities, are among the most affected by this problem. 93% of traffic accidents occur in low and middle-income countries, even though these countries have approximately 60% of the world's vehicles. This occurs mainly because in these types of countries, especially in medium-sized cities (target context), there are no ideal conditions for driving, such as adequate road infrastructure, good condition of vehicles, and rigorous safety policies. Advanced data analysis techniques including machine learning (ML) have increasingly been used to solve this problem. Naturalistic driving (ND) can be applied as a data collection method that provides information on traffic accidents. ND commonly uses a vehicle's kinematic data to detect high-risk driving behaviors that could cause an accident. The objectives of this document are to present a review of different alternatives that help in data collection and creation of intelligent solutions related to detection of possible traffic accidents, principally using ND; and to propose an intelligent collision risk detection system (ICRDS) for identification of areas with a high probability of TA in the target context. Through the review, it was possible to analyze and evaluate the devices, variables and algorithms that help characterize a risk event in driving, considering the target context. The development of a prototype of an ICRDS for a medium-sized city in a developing country is considered viable, considering the identified components, with the aim of identifying risk events in driving, and areas of high probability of accidents in the city. |
| first_indexed | 2024-04-11T00:53:08Z |
| format | Article |
| id | doaj.art-498f6bb7de764b3ab09a0c59a2d7b6f0 |
| institution | Directory Open Access Journal |
| issn | 2095-7564 |
| language | English |
| last_indexed | 2024-04-11T00:53:08Z |
| publishDate | 2022-12-01 |
| publisher | KeAi Communications Co., Ltd. |
| record_format | Article |
| series | Journal of Traffic and Transportation Engineering (English ed. Online) |
| spelling | doaj.art-498f6bb7de764b3ab09a0c59a2d7b6f02023-01-05T08:36:36ZengKeAi Communications Co., Ltd.Journal of Traffic and Transportation Engineering (English ed. Online)2095-75642022-12-0196912929Intelligent collision risk detection in medium-sized cities of developing countries, using naturalistic driving: A reviewJuan Jose Paredes0Santiago Felipe Yepes1Ricardo Salazar-Cabrera2Álvaro Pachón de la Cruz3Juan Manuel Madrid Molina4Telematics Engineering Research Group (GIT), Telematics Department, Universidad Del Cauca, Popayán, ColombiaTelematics Engineering Research Group (GIT), Telematics Department, Universidad Del Cauca, Popayán, ColombiaTelematics Engineering Research Group (GIT), Telematics Department, Universidad Del Cauca, Popayán, Colombia; Corresponding author.Information Technology and Telecommunications Research Group (I2T), Universidad Icesi, Cali, ColombiaInformation Technology and Telecommunications Research Group (I2T), Universidad Icesi, Cali, ColombiaTraffic accidents are one of the most serious problems worldwide, being one of the leading causes of death and economic loss in the world. Low- and middle-income countries, mainly their medium-sized cities, are among the most affected by this problem. 93% of traffic accidents occur in low and middle-income countries, even though these countries have approximately 60% of the world's vehicles. This occurs mainly because in these types of countries, especially in medium-sized cities (target context), there are no ideal conditions for driving, such as adequate road infrastructure, good condition of vehicles, and rigorous safety policies. Advanced data analysis techniques including machine learning (ML) have increasingly been used to solve this problem. Naturalistic driving (ND) can be applied as a data collection method that provides information on traffic accidents. ND commonly uses a vehicle's kinematic data to detect high-risk driving behaviors that could cause an accident. The objectives of this document are to present a review of different alternatives that help in data collection and creation of intelligent solutions related to detection of possible traffic accidents, principally using ND; and to propose an intelligent collision risk detection system (ICRDS) for identification of areas with a high probability of TA in the target context. Through the review, it was possible to analyze and evaluate the devices, variables and algorithms that help characterize a risk event in driving, considering the target context. The development of a prototype of an ICRDS for a medium-sized city in a developing country is considered viable, considering the identified components, with the aim of identifying risk events in driving, and areas of high probability of accidents in the city.http://www.sciencedirect.com/science/article/pii/S2095756422000848Naturalistic drivingNear-crashTraffic accidentVehicle data collection |
| spellingShingle | Juan Jose Paredes Santiago Felipe Yepes Ricardo Salazar-Cabrera Álvaro Pachón de la Cruz Juan Manuel Madrid Molina Intelligent collision risk detection in medium-sized cities of developing countries, using naturalistic driving: A review Journal of Traffic and Transportation Engineering (English ed. Online) Naturalistic driving Near-crash Traffic accident Vehicle data collection |
| title | Intelligent collision risk detection in medium-sized cities of developing countries, using naturalistic driving: A review |
| title_full | Intelligent collision risk detection in medium-sized cities of developing countries, using naturalistic driving: A review |
| title_fullStr | Intelligent collision risk detection in medium-sized cities of developing countries, using naturalistic driving: A review |
| title_full_unstemmed | Intelligent collision risk detection in medium-sized cities of developing countries, using naturalistic driving: A review |
| title_short | Intelligent collision risk detection in medium-sized cities of developing countries, using naturalistic driving: A review |
| title_sort | intelligent collision risk detection in medium sized cities of developing countries using naturalistic driving a review |
| topic | Naturalistic driving Near-crash Traffic accident Vehicle data collection |
| url | http://www.sciencedirect.com/science/article/pii/S2095756422000848 |
| work_keys_str_mv | AT juanjoseparedes intelligentcollisionriskdetectioninmediumsizedcitiesofdevelopingcountriesusingnaturalisticdrivingareview AT santiagofelipeyepes intelligentcollisionriskdetectioninmediumsizedcitiesofdevelopingcountriesusingnaturalisticdrivingareview AT ricardosalazarcabrera intelligentcollisionriskdetectioninmediumsizedcitiesofdevelopingcountriesusingnaturalisticdrivingareview AT alvaropachondelacruz intelligentcollisionriskdetectioninmediumsizedcitiesofdevelopingcountriesusingnaturalisticdrivingareview AT juanmanuelmadridmolina intelligentcollisionriskdetectioninmediumsizedcitiesofdevelopingcountriesusingnaturalisticdrivingareview |