Abstract
In this paper, we present a Colored Petri Net (CPN) model for conducting formative analysis of driver affordances based on a highway-driving task. This model extends the initial conceptual CPN model proposed by Thiruvengada and Rothrock [1-3] and allows experimenters to study behavioral preferences for drivers (risky vs. conservative driver). There are two types of driver models: Confederate Driver Model (CDM) and Subject Driver Model (SDM). While, the CDM model follows a pre-scripted path similar to that of a confederate driver in actual empirical scenarios, the SDM model uses computational algorithm (CPN) to plan a path, while considering SDM and CDM attributes (such as relative position and relative velocity). This model allows experimenters to input various driver profiles as preferential turn probabilities to elicit model predicted driver performance pertaining to each test scenario. Finally, the model predicted path is compared with the path obtained from these test scenarios, to verify the precision of the affordance-based CPN model. We present that this model can be used to elicit the formative set of affordances (also known as niche) that become available to various types of drivers (risky vs. conservative driver) within such dynamic environment.
Original language | English (US) |
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Pages | 986-991 |
Number of pages | 6 |
State | Published - 2007 |
Event | IIE Annual Conference and Expo 2007 - Industrial Engineering's Critical Role in a Flat World - Nashville, TN, United States Duration: May 19 2007 → May 23 2007 |
Other
Other | IIE Annual Conference and Expo 2007 - Industrial Engineering's Critical Role in a Flat World |
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Country/Territory | United States |
City | Nashville, TN |
Period | 5/19/07 → 5/23/07 |
All Science Journal Classification (ASJC) codes
- Industrial and Manufacturing Engineering