Control of Automated Trucks Considering Stochastic Behaviors of Human-Driven Vehicles in Mixed Traffic

Xiao, Xiao; Zhang, Yulong; Wang, Bruce

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Control of Automated Trucks Considering Stochastic Behaviors of Human-Driven Vehicles in Mixed Traffic

2022-05-01
By Xiao, Xiao ; Zhang, Yulong ; Wang, Bruce

File Language:

English

Details

Creators:

Xiao, Xiao ; Zhang, Yulong ; Wang, Bruce
Corporate Creators:

Florida Atlantic University. Freight Mobility Research Institute ; Texas A&M University
Corporate Contributors:

United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
Subject/TRT Terms:

CAV Driving Behavior Freeways Freight Traffic Intelligent Vehicles Mixed Traffic Mobility Stochastic Processes Traffic Platooning Trajectory Trucks Vehicle Mix
Publication/ Report Number:

FMRI-YR5- 22
Resource Type:

Tech Report
Geographical Coverage:

Texas ; United States
Edition:

Final Report
Corporate Publisher:

Freight Mobility Research Institute. Florida Atlantic University
Abstract:

Freight traffic affects the performance of the road network significantly due to their different driving characteristics compared to passenger cars. For example, trucks have extra braking distance and time for deceleration and are slower when starting up. In Texas, freight traffic can be significant on the freeway, and the operation of trucks is significant in keeping traffic safe and efficient. Recently, connected and automated vehicle technology has added possibilities to control trucks wisely to improve safety and mobility. Strategies have been developed in the FMRI first and second-year projects to formulate multiple trucks’ trajectories considering mixed traffic conditions. The stability problem of vehicle streams has been studied in the third-year project. However, in previous research, deterministic behaviors of human-driven vehicles in mixed traffic were assumed. In reality, truck drivers may act differently (accelerating, decelerating, reacting) according to their varying driving habits, which will lead to uncertainties in the vehicle dynamic system. To make the research more complete and more general, this year, behaviors of human-driven vehicles are considered. This project investigates the method for CAV truck controlling in a truck-only lane. By controlling CAV trucks, the mixed traffic is stabilized and optimized in its mobility given different levels and distribution types of the uncertainty of human-driven vehicles. The outcomes show a control method for CAVs enables the traffic with safe and stable performances considering human drivers. Due to the limitation of time (one year), the research only focuses on theoretical modeling at the present stage. In the implementation stage in the future, local agencies or industry partners may be involved.
Format:

PDF
Funding:

69A3551747120
Collection(s):

University Transportation Centers
Main Document Checksum:

urn:sha-512:f127a7c59cc0fb3dd11dd171fd962650deaf0d074c951ad6bab095511cc96c450468294f7dfe3f8878066e990199288214915e4c9cbf1ed57b2b3688931cc63b
Download URL:

https://rosap.ntl.bts.gov/view/dot/79806/dot_79806_DS1.pdf
File Type:

[PDF - 1.18 MB ]

File Language:

English

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