Loading…
Investigating the effect of driver-vehicle-environment interaction with risk through naturalistic driving data
While mobility and safety of drivers are challenged by behavioural changes, the increasingly complex road environment has placed a higher demand on their adaptability. The ultimate goal of this paper was to identify the impact that the balance between task complexity and coping capacity had on crash...
Saved in:
| Main Authors: | , , , , , , , , , , , , , , |
|---|---|
| Format: | Default Conference proceeding |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://hdl.handle.net/2134/25567872.v1 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1818164873808314368 |
|---|---|
| author | Eva Michelaraki Thodoris Garefalakis Stella Roussou Christos Katrakazas Amir Pooyan Afghari Evita Papazikou Rachel Talbot Muhammad Adnan Muhammad Wisal Khattak Christelle Al Haddad Md Rakibul Alam Constantinos Antoniou Eleonora Papadimitriou Tom Brijs George Yannis |
| author_facet | Eva Michelaraki Thodoris Garefalakis Stella Roussou Christos Katrakazas Amir Pooyan Afghari Evita Papazikou Rachel Talbot Muhammad Adnan Muhammad Wisal Khattak Christelle Al Haddad Md Rakibul Alam Constantinos Antoniou Eleonora Papadimitriou Tom Brijs George Yannis |
| author_sort | Eva Michelaraki (9594794) |
| collection | Figshare |
| description | While mobility and safety of drivers are challenged by behavioural changes, the increasingly complex road environment has placed a higher demand on their adaptability. The ultimate goal of this paper was to identify the impact that the balance between task complexity and coping capacity had on crash risk. Towards that aim, an integrated model for understanding the effect of the inter-relationship of task complexity and coping capacity with risk was developed. A vast library of data from a naturalistic driving experiment was created in three countries (i.e. Belgium, UK and Germany) to investigate the most prominent driving behaviour indicators available, including speeding, headway, overtaking, duration, distance and harsh events. In order to fulfil the aforementioned objectives, exploratory analysis, such as Generalized Linear Models (GLMs) were developed and the most appropriate variables associated to the latent variable “task complexity” and “coping capacity” were estimated from the various indicators. Additionally, Structural Equation Models (SEMs) were used to explore how the model variables were interrelated, allowing for both direct and indirect relationships to be modelled. The analyses revealed that higher task complexity levels lead to higher coping capacity by drivers. Additionally, the effect of task complexity on risk was greater than the impact of coping capacity in Belgium and Germany, while mixed results were observed in the UK. |
| format | Default Conference proceeding |
| id | rr-article-25567872 |
| institution | Loughborough University |
| publishDate | 2024 |
| record_format | Figshare |
| spelling | rr-article-255678722024-04-17T15:24:50Z Investigating the effect of driver-vehicle-environment interaction with risk through naturalistic driving data Eva Michelaraki (9594794) Thodoris Garefalakis (17635479) Stella Roussou (17099863) Christos Katrakazas (7152404) Amir Pooyan Afghari (6208055) Evita Papazikou (2567296) Rachel Talbot (1252758) Muhammad Adnan (678952) Muhammad Wisal Khattak (12510293) Christelle Al Haddad (17635482) Md Rakibul Alam (17635485) Constantinos Antoniou (568693) Eleonora Papadimitriou (568694) Tom Brijs (570863) George Yannis (568695) Driving behaviour Road safety Naturalistic driving experiment Structural equation models Generalized linear models <p>While mobility and safety of drivers are challenged by behavioural changes, the increasingly complex road environment has placed a higher demand on their adaptability. The ultimate goal of this paper was to identify the impact that the balance between task complexity and coping capacity had on crash risk. Towards that aim, an integrated model for understanding the effect of the inter-relationship of task complexity and coping capacity with risk was developed. A vast library of data from a naturalistic driving experiment was created in three countries (i.e. Belgium, UK and Germany) to investigate the most prominent driving behaviour indicators available, including speeding, headway, overtaking, duration, distance and harsh events. In order to fulfil the aforementioned objectives, exploratory analysis, such as Generalized Linear Models (GLMs) were developed and the most appropriate variables associated to the latent variable “task complexity” and “coping capacity” were estimated from the various indicators. Additionally, Structural Equation Models (SEMs) were used to explore how the model variables were interrelated, allowing for both direct and indirect relationships to be modelled. The analyses revealed that higher task complexity levels lead to higher coping capacity by drivers. Additionally, the effect of task complexity on risk was greater than the impact of coping capacity in Belgium and Germany, while mixed results were observed in the UK.</p> 2024-04-17T15:24:50Z Text Conference contribution 2134/25567872.v1 https://figshare.com/articles/conference_contribution/Investigating_the_effect_of_driver-vehicle-environment_interaction_with_risk_through_naturalistic_driving_data/25567872 All Rights Reserved |
| spellingShingle | Driving behaviour Road safety Naturalistic driving experiment Structural equation models Generalized linear models Eva Michelaraki Thodoris Garefalakis Stella Roussou Christos Katrakazas Amir Pooyan Afghari Evita Papazikou Rachel Talbot Muhammad Adnan Muhammad Wisal Khattak Christelle Al Haddad Md Rakibul Alam Constantinos Antoniou Eleonora Papadimitriou Tom Brijs George Yannis Investigating the effect of driver-vehicle-environment interaction with risk through naturalistic driving data |
| title | Investigating the effect of driver-vehicle-environment interaction with risk through naturalistic driving data |
| title_full | Investigating the effect of driver-vehicle-environment interaction with risk through naturalistic driving data |
| title_fullStr | Investigating the effect of driver-vehicle-environment interaction with risk through naturalistic driving data |
| title_full_unstemmed | Investigating the effect of driver-vehicle-environment interaction with risk through naturalistic driving data |
| title_short | Investigating the effect of driver-vehicle-environment interaction with risk through naturalistic driving data |
| title_sort | investigating the effect of driver-vehicle-environment interaction with risk through naturalistic driving data |
| topic | Driving behaviour Road safety Naturalistic driving experiment Structural equation models Generalized linear models |
| url | https://hdl.handle.net/2134/25567872.v1 |