1. DEPLOYMENT AND EVALUATION OF REAL-TIME VEHICLE REIDENTIFICATION FROM AN OPERATIONS PERSPECTIVE
Task Order 4107
Pravin Varaiya, University of California, Berkeley
varaiya@eecs.berkeley.edu, www.path.berkeley.edu/~varaiya
The goals of this proposal include: 1)maintain the high resolution loop detector surveillance and communication of the Berkeley Highway Lab, 2)make the vehicle reidentification systerm compatible with the Caltrans open architecture ATMS software and bring the data into the Caltrans D4 system, 3)evaluate the costs and benefits of vehicle reidentification from an operational prespective, and 4)develop a path to large scale deployment.
2. DEVELOPMENT AND TESTING OF FIELD DEPLOYABLE REAL-TIME LASER-BASED NON-INTRUSIVE DETECTION SYSTEM FOR MEASURING OF TRAVEL TIME ON THE HIGHWAY
Task Order 4116
Harry Cheng, University of California, Davis
hhcheng@ucdavis.edu, iel.ucdavis.edu/people/cheng.html
This project will develop and test a complete field deployable laser-based detection system which is capable on non-intrusively detecting high-resolution, site-independent delineation's of vehicles for measurement of true travel time on the highway in real time. The detection system will be reliable, easy to maintain and low-cost.
3. GPS/GIS TECHNOLOGIES FOR TRAFFIC SURVEILLANCE AND MANAGEMENT: A TESTBED IMPLEMENTATION STUDY
Task Order 4120
Michael McNally, University of California, Irvine
mmcnally@uci.edu, www.eng.uci.edu/civil/Faculty/McNally/index.html
The research seeks to gain better understanding of route choice behavior as part of individual travel pattern. The project is a frull study of full study of travel time patterns, which will be collected using a travel survey, augmented with GPS data.
4.
FIELD INVESTIGATION OF ADVANCED VEHICLE
REIDENTIFICATION TECHNIQUES AND DECTECTOR TECHNOLOGIES - PHASE 2
MOU
3008, Task Order 4122
Stephen
Ritchie, University of California, Irvine
ritchie@uci.edu, www.eng.uci.edu/civil/faculty/ritchie/index.html
C. Arthur MacCarley
cam@tesla.elee.calpoly.edu,
This research will
use the latest technologies available for traffic detection for collecting more
accurate traffic characteristics and traffic data necessary for ITS
applications. This project consists of three components. The first component is
a field investigation of several emerging and advanced freeway detector
technologies developed by PATH including a laser, video, and a new loop
detector. The second component involves the utilization of the reidentification
system at a major signalized intersection for real-time level of service
estimation. The third component involves an investigation of the fusion of the
various advanced detection systems that have been developed by PATH for the
purpose of vehicle reidentification.
5.
MULTI-SENSOR TRAFFIC DATA FUSION
MOU 3021
Jitendra Malik, University of California,
Berkeley
malik@cs.berkeley.edu, www.cs.berkeley.edu/~malik/
Alexander Skarbardonis, University of
California, Berkeley
dromeas@uclink.berkeley.edu, http://www.ce.berkeley.edu/~skabardonis/
This research will develop the infrastructure and algorithms necessary to generate a large, accurate database of vehicle trajectories and identifying features through the integration of loop and video data. This database will be used to validate the algorithms developed in previous research on data analysis/visualization, and travel time estimation and develop improved algorithms for field deployment.
updated 3/1/2001
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