Representing Route Familiarity Using the Abstraction Hierarchy Framework
Familiarity with a route is influenced by levels of dynamic and static knowledge about the route and the route network such as type of roads, infrastructure, traffic conditions, purpose of travel, weather, departure time, etc. To better understand and develop route choice models that can incorporate...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-08-01
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| Series: | Geriatrics |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2308-3417/6/3/81 |
| _version_ | 1797519116994609152 |
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| author | Rashmi P. Payyanadan John D. Lee |
| author_facet | Rashmi P. Payyanadan John D. Lee |
| author_sort | Rashmi P. Payyanadan |
| collection | DOAJ |
| description | Familiarity with a route is influenced by levels of dynamic and static knowledge about the route and the route network such as type of roads, infrastructure, traffic conditions, purpose of travel, weather, departure time, etc. To better understand and develop route choice models that can incorporate more meaningful representations of route familiarity, OBDII devices were installed in the vehicles of 32 drivers, 65 years and older, for a period of three months. Personalized web-based trip diaries were used to provide older drivers with post-trip feedback reports about their risky driving behaviors, and collect feedback about their route familiarity, preferences, and reasons for choosing the route driven vs. an alternate low-risk route. Feedback responses were analyzed and mapped onto an abstraction hierarchy framework, which showed that among older drivers, route familiarity depends not only on higher abstraction levels such as trip goals, purpose, and driving strategies, but also on the lower levels of demand on driving skills, and characteristics of road type. Additionally, gender differences were identified at the lower levels of the familiarity abstraction model, especially for driving challenges and the driving environment. Results from the analyses helped highlight the multi-faceted nature of route familiarity, which can be used to build the necessary levels of granularity for modelling and interpretation of spatial and contextual route choice recommendation systems for specific population groups such as older drivers. |
| first_indexed | 2024-03-10T07:37:38Z |
| format | Article |
| id | doaj.art-4ec91ddf1ee042c1a03d52a914f3ed7c |
| institution | Directory Open Access Journal |
| issn | 2308-3417 |
| language | English |
| last_indexed | 2024-03-10T07:37:38Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Geriatrics |
| spelling | doaj.art-4ec91ddf1ee042c1a03d52a914f3ed7c2023-11-22T13:16:33ZengMDPI AGGeriatrics2308-34172021-08-01638110.3390/geriatrics6030081Representing Route Familiarity Using the Abstraction Hierarchy FrameworkRashmi P. Payyanadan0John D. Lee1Touchstone Evaluations, Detroit, MI 48202, USADepartment of Industrial and Systems Engineering, University of Wisconsin-Madison, Madison, WI 53706, USAFamiliarity with a route is influenced by levels of dynamic and static knowledge about the route and the route network such as type of roads, infrastructure, traffic conditions, purpose of travel, weather, departure time, etc. To better understand and develop route choice models that can incorporate more meaningful representations of route familiarity, OBDII devices were installed in the vehicles of 32 drivers, 65 years and older, for a period of three months. Personalized web-based trip diaries were used to provide older drivers with post-trip feedback reports about their risky driving behaviors, and collect feedback about their route familiarity, preferences, and reasons for choosing the route driven vs. an alternate low-risk route. Feedback responses were analyzed and mapped onto an abstraction hierarchy framework, which showed that among older drivers, route familiarity depends not only on higher abstraction levels such as trip goals, purpose, and driving strategies, but also on the lower levels of demand on driving skills, and characteristics of road type. Additionally, gender differences were identified at the lower levels of the familiarity abstraction model, especially for driving challenges and the driving environment. Results from the analyses helped highlight the multi-faceted nature of route familiarity, which can be used to build the necessary levels of granularity for modelling and interpretation of spatial and contextual route choice recommendation systems for specific population groups such as older drivers.https://www.mdpi.com/2308-3417/6/3/81route familiarityolder driversabstraction hierarchyroute choice |
| spellingShingle | Rashmi P. Payyanadan John D. Lee Representing Route Familiarity Using the Abstraction Hierarchy Framework Geriatrics route familiarity older drivers abstraction hierarchy route choice |
| title | Representing Route Familiarity Using the Abstraction Hierarchy Framework |
| title_full | Representing Route Familiarity Using the Abstraction Hierarchy Framework |
| title_fullStr | Representing Route Familiarity Using the Abstraction Hierarchy Framework |
| title_full_unstemmed | Representing Route Familiarity Using the Abstraction Hierarchy Framework |
| title_short | Representing Route Familiarity Using the Abstraction Hierarchy Framework |
| title_sort | representing route familiarity using the abstraction hierarchy framework |
| topic | route familiarity older drivers abstraction hierarchy route choice |
| url | https://www.mdpi.com/2308-3417/6/3/81 |
| work_keys_str_mv | AT rashmippayyanadan representingroutefamiliarityusingtheabstractionhierarchyframework AT johndlee representingroutefamiliarityusingtheabstractionhierarchyframework |