1. THE ENHANCMENTS OF ATMIS USING ARTIFICIAL INTELLIGENCE
Task Order 4100
Henry Liu, PATH Headquarters
hliu@translab.its.uci.edu
Traffic management decisions frequently depend on qualitative assessments of network conditions.These high-level state variables can be used to determine what general strategies are most appropiate for improving the current system status. Accurate traffic condition assessment is vital to our understanding of how to provide information and control that leads to real-time, system-wide, traffic management. Because the system is so complex, ANN may be one feasible way that we can get a handle on it.
2. IDENTIFYING DENSITY-FLOW RELATIONS ON ARTERIAL STREETS
Task Order 4109
Mike Cassidy, University of California, Berkeley
cassidy@euler.berkeley.edu,
The research will extract and analyze empirical data to determine the precise shapes of density-flow relations for describing traffic along signalized arterial surface streets; possible forms for these range from piece-wise linear to non-linear, parabolic-like curves. Determining the correct forms is vital for modeling traffic signal control strategies.
3. CONSIDERING RISK-TAKING BEHAVIOR IN TRAVEL TIME RELIABILITY
Task Order 4110
Will Recker, University of California, Irvine
wwrecker@uci.edu, www.its.uci.edu/its/personnel/recker.html
This research proposes to incorporate a risk-taking, route choice behavior when estimating travel time reliability of a road network. The proposed research approach will allow the evaluation of network performance under uncertainty. It is particularly useful for the traffic information systems in which travel time is provided to the users for decision-making.
4. VALIDATION OF DAGANZO'S BEHAVIORAL THEORY OF MULTI-LANE TRAFFICE FLOW
Task Order 4113
James Banks, San Diego State University
banks@mail.sdsu.edu
The proposed research is empirical validation of Daganzo's behavioral theory of multi-lane traffic flow. The research will validate this theory by testing a set of predictions based on it. The major contribution will be a better understanding of freeway traffic flow and providing the basis for a very simple macroscopic model of freeway flow to design metering and other control measures.
5. IMPLEMENTATIONS TO THE DEMAND ESTIMATION AND SUBSECTION ANALYSIS OF THE MICROSCOPIC TRAFFIC SIMULATOR - PARAMICS
Task Order 4121
Reinaldo Garcia, PATH
rgarcia@translab.its.uci.edu
Paramics is an excellent "shell" or "framework" for a comprehensive and extensive transportation simulation laboratory. Paramics offers important and unprecedented features, such as high performance and scalability, to handle realistic real world traffic networks under ITS. Nevertheless, Paramics has its own limitations, particularly relating to the model's ability to interface with dynamic routing protocols, dynamic O-D estimation. This Work addresses the continuing effort to expand the Paramics capabilities, making it a more complete tool to evaluate the expected net benefits of ATMS applications.
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