An affective intelligent driving agent: driver's trajectory and activities prediction.
Name
2009_DiLorenzo_Pinelli_et all_VTC09.pdf
Size
2.01 MB
Format
Adobe PDF
Checksum (MD5)
bd013c1f6ef4069ad6aa3622c90daa4e
Author(s) • • • • • •
Ratti, Carlo
Di Lorenzo, Giusy
Pereira, Francisco
Biderman, Assaf
Pinelli, Fabio
Lee, Charles
Lee, Chuhee
Date Issued
January 2010
Journal
2009 IEEE 70th Vehicular Technology Conference (VTC 2009 Fall)
Publisher
Institute of Electrical and Electronics Engineers
Citation
Di Lorenzo, G. et al. “An Affective Intelligent Driving Agent: Driver's Trajectory and Activities Prediction.” Vehicular Technology Conference Fall (VTC 2009-Fall), 2009 IEEE 70th. 2009. 1-4. ©2009 Institute of Electrical and Electronics Engineers.
Version
Original manuscript
Abstract
The traditional relationship between the car, driver, and city can be described as waypoint navigation with additional traffic and maintenance information. The car can receive and store waypoint information, find the shortest route to these waypoints, integrate traffic information, find points-of-interest, and alert the driver of a pre-programmed set of maintenance issues related to the car. Here, we propose a new route system that is multi-goal-centric rather than waypoint-centric. Instead of focusing on determining the route to a specified waypoint, as done in commercially available navigation systems, the system will analyze the driver's behavior in order to extract the potential set(s) of goals that the driver would like to achieve. The system must also understand the city on a number of levels: physical, social, and commercial. This provides the foundation for a social and intelligent driving assistant, that helps the driver achieve his goals and helps the city perform better through interaction between both entities.
MIT Department
Massachusetts Institute of Technology. Department of Urban Studies and Planning
Massachusetts Institute of Technology. SENSEable City Laboratory
Terms of Use
Attribution-Noncommercial-Share Alike 3.0 Unported
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1109/VETECF.2009.5378965