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 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.

Challenges for Older Drivers in Urban, Suburban, and Rural Settings.

Along with age-related factors, geographical settings-urban, suburban, and rural areas-also contribute to the differences in fatal crashes among older drivers. These differences in crash outcomes might be attributed to the various driving challenges faced by older drivers residing in different locations. To understand these challenges from the perspective of the older driver, a focus group study was conducted with drivers 65 and older from urban, suburban, and rural settings. Guided-group interviews were used to assess driving challenges, mobility options, opportunities for driver support systems (DSS), and alternate transportation needs. Content analysis of the interview responses resulted in four categories representing common challenges faced by older drivers across the settings: behavior of other drivers on the road, placement of road signs, reduced visibility of road signs due to age-related decline, and difficulties using in-vehicle technologies. Six categories involved location-specific challenges such as heavy traffic situations for urban and suburban drivers, and multi-destination trips for rural drivers. Countermeasures implemented by older drivers to address these challenges primarily involved route selection and avoidance. Technological advances of DSS systems provide a unique opportunity to support the information needs for route selection and avoidance preferences of drivers. Using the content analysis results, a framework was built to determine additional and modified DSS features to meet the specific challenges of older drivers in urban, suburban, and rural settings. These findings suggest that there is heterogeneity in the driving challenges and preferences of older drivers based on their location. Consequently, DSS technologies and vehicle automation need to be tailored to not only meet the driving safety and mobility needs of older drivers as a population, but also to their driving environment.

Using trip diaries to mitigate route risk and risky driving behavior among older drivers.

To reduce exposure to risky and challenging driving situations and prolong mobility and independence, older drivers self-regulate their driving behavior. But self-regulation can be challenging because it depends on drivers' ability to assess their limitations. Studies using self-reports, survey data, and hazard and risk perception tests have shown that driving behavior feedback can help older drivers assess their limitations and adjust their driving behavior. But only limited work has been conducted in developing feedback technology interventions tailored to meet the information needs of older drivers, and the impact these interventions have in helping older drivers self-monitor their driving behavior and risk outcomes. The vehicles of 33 drivers 65 years and older were instrumented with OBD2 devices. Older drivers were provided access to customized web-based Trip Diaries that delivered post-trip feedback of the routes driven, low-risk route alternatives, and frequency of their risky driving behaviors. Data were recorded over four months, with baseline driving behavior collected for one month. Generalized linear mixed effects regression models assessed the effects of post-trip feedback on the route risk and driving behaviors of older drivers. Results showed that post-trip feedback reduced the estimated route risk of older drivers by 2.9% per week, and reduced their speeding frequency on average by 0.9% per week. Overall, the Trip Diary feedback reduced the expected crash rate from 1 in 6172 trips to 1 in 7173 trips, and the expected speeding frequency from 46% to 39%. Thus providing older drivers with tailored feedback of their driving behavior and crash risk could help them appropriately self-regulate their driving behavior, and improve their crash risk outcomes.