From Vehicle Performance to Transportation System Performance - System Impacts of Automated Vehicles

Award Information
Agency: Department of Transportation
Branch: N/A
Contract: DTRT5715C10048
Agency Tracking Number: DTRT57-15-C-10048
Amount: $149,975.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: 151FH4
Solicitation Number: DTRT5715RSBIR1
Timeline
Solicitation Year: 2015
Award Year: 2015
Award Start Date (Proposal Award Date): 2015-07-29
Award End Date (Contract End Date): 2016-03-09
Small Business Information
8885 Research Drive, suite 150, Irvine, CA, 92618
DUNS: 795785745
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: Y
Principal Investigator
 Lianyu Chu
 President
 (949) 705-8566
 lchu@clr-analytics.com
Business Contact
 Lianyu Chu
Title: President
Phone: (949) 705-8566
Email: lchu@clr-analytics.com
Research Institution
N/A
Abstract
The rapid development of automated vehicles has attracted a lot of attentions from the public in recent years. Current studies on automated vehicles mainly focus on microscopic simulations with simple network topologies and driver behaviors, and few has considered to incorporate automated vehicles into macroscopic travel demand models for the analysis in a regional network. In this project, we propose a multiple-resolution approach that allows us to model the impacts of automated vehicles for both transportation and traffic operation analysis. The approach hinges on the development of a capacity adjustment factor (CAF) for automated vehicles, similar to the heavy vehicles adjustment factor used in highway capacity analysis. CAF will be linked to input variables such as roadway facility types, traffic demand levels, and market penetration rates of automated vehicles. CAF will be derived from a microsimulation study, which involves the development of an integrated car-following model for both human drivers and automated vehicles, calibration of the model using NGSIM data, implementation of the model as a plugin in microsimulation. The proposed modeling approach can then be used to analyze the impact of automated vehicles in a regional network through additional traffic assignment runs using the adjusted capacity based on CAF.

* Information listed above is at the time of submission. *

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