1
|
Guillen M, Pérez-Marín AM, Nielsen JP. Pricing weekly motor insurance drivers' with behavioral and contextual telematics data. Heliyon 2024; 10:e36501. [PMID: 39258213 PMCID: PMC11386000 DOI: 10.1016/j.heliyon.2024.e36501] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Revised: 07/09/2024] [Accepted: 08/16/2024] [Indexed: 09/12/2024] Open
Abstract
Telematics boxes integrated into vehicles are instrumental in capturing driving data encompassing behavioral and contextual information, including speed, distance travelled by road type, and time of day. These data can be amalgamated with drivers' individual attributes and reported accident occurrences to their respective insurance providers. Our study analyzes a substantial sample size of 19,214 individual drivers over a span of 55 weeks, covering a cumulative distance of 181.4 million kilometers driven. Utilizing this dataset, we develop predictive models for weekly accident frequency. As anticipated based on prior research with yearly data, our findings affirm that behavioral traits, such as instances of excessive speed, and contextual data pertaining to road type and time of day significantly aid in ratemaking design. The predictive models enable the creation of driving scores and personalized warnings, presenting a potential to enhance traffic safety by alerting drivers to perilous conditions. Our discussion delves into the construction of multiplicative scores derived from Poisson regression, contrasting them with additive scores resulting from a linear probability model approach, which offer greater communicability. Furthermore, we demonstrate that the inclusion of lagged behavioral and contextual factors not only enhances prediction accuracy but also lays the foundation for a diverse range of usage-based insurance schemes for weekly payments.
Collapse
Affiliation(s)
- Montserrat Guillen
- Departament d'Econometria, Estadística i Economia Aplicada, Universitat de Barcelona (UB), Av. Diagonal, 690, 08034, Barcelona, Spain
- RISKcenter-Institut de Recerca en Economia Aplicada (IREA), Universitat de Barcelona (UB), Av. Diagonal, 690, 08034, Barcelona, Spain
| | - Ana M Pérez-Marín
- Departament d'Econometria, Estadística i Economia Aplicada, Universitat de Barcelona (UB), Av. Diagonal, 690, 08034, Barcelona, Spain
- RISKcenter-Institut de Recerca en Economia Aplicada (IREA), Universitat de Barcelona (UB), Av. Diagonal, 690, 08034, Barcelona, Spain
| | - Jens P Nielsen
- Bayes Business School. City, University of London, 106 Bunhill Row, London, EC1Y 8TZ, United Kingdom
| |
Collapse
|
2
|
Safavi-Naini SAA, Sobhani S, Malekpour MR, Bhalla K, Shahraz S, Haghshenas R, Ghamari SH, Abbasi-Kangevari M, Rezaei N, Heydari ST, Rezaei N, Lankarani KB, Farzadfar F. Drivers' behavior confronting fixed and point-to-point speed enforcement camera: agent-based simulation and translation to crash relative risk change. Sci Rep 2024; 14:1863. [PMID: 38253631 PMCID: PMC10803355 DOI: 10.1038/s41598-024-52265-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2023] [Accepted: 01/16/2024] [Indexed: 01/24/2024] Open
Abstract
Utilizing a novel microsimulation approach, this study evaluates the impact of fixed and average point-to-point Speed Enforcement Cameras (SEC) on driving safety. Using the SUMO software, agent-based models for a 6-km highway without exits or obstacles were created. Telematics data from 93,160 trips were used to determine the desired free-flow speed. A total of 13,860 scenarios were simulated with 30 random seeds. The ratio of unsafe driving (RUD) is the spatial division of the total distance travelled at an unsafe speed by the total travel distance. The study compared different SEC implementations under different road traffic and community behaviours using the Power Model and calculated crash risk changes. Results showed that adding one or two fixed SECs reduced RUD by 0.20% (0.18-0.23) and 0.57% (0.54-0.59), respectively. However, average SECs significantly lowered RUD by 10.97% (10.95-10.99). Furthermore, a 1% increase in telematics enforcement decreased RUD by 0.22% (0.21-0.22). Point-to-point cameras effectively reduced crash risk in all implementation scenarios, with reductions ranging from - 3.44 to - 11.27%, pointing to their superiority as speed enforcement across various scenarios. Our cost-conscious and replicable approach can provide interim assessments of SEC effectiveness, even in low-income countries.
Collapse
Affiliation(s)
- Seyed Amir Ahmad Safavi-Naini
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
- Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | | | - Mohammad-Reza Malekpour
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Kavi Bhalla
- Public Health Sciences, University of Chicago, Chicago, IL, USA
| | - Saeid Shahraz
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA
| | - Rosa Haghshenas
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyyed-Hadi Ghamari
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohsen Abbasi-Kangevari
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Nazila Rezaei
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyed Taghi Heydari
- Health Policy Research Center, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Negar Rezaei
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
| | - Kamran B Lankarani
- Health Policy Research Center, Institute of Health, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Farshad Farzadfar
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| |
Collapse
|