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Title:

Integrating Car Following and Lane Changing in a Mixed Traffic Model of Connected Automated Vehicles and Conventional Vehicles

Accession Number:

01764000

Record Type:

Component

Abstract:

This study developed mixed-traffic simulation models of Connected Automated Vehicles (CAVs) and Manually-Driven Vehicles (MDVs) at the full-spectrum of penetration rates on a freeway segment by incorporating the car-following and lane-changing models via a linkage to investigate capacity and travel time. The car-following models for CAVs and MDVs were modified from the Full Velocity Difference (FVD) model, while a lane-changing logic was adopted. Stochastic parameters were applied for MDVs to replicate the characteristics of the human drivers, whereas static parameters were adopted to establish the safe decision-making thresholds for CAVs. The CAV algorithm was designed to maintain a sizeable headway between vehicles and milder acceleration for safety and passenger comfort, also equipped with a gap-creation function for enhancing lane-changing maneuvers. The algorithms were coded in JAVA to create a simulation platform, prior to calibrating the model with field data. Eleven mixed-traffic scenarios were simulated, along with parallel simulations in VISSIM, to generate and validate the speed-flow diagrams. The results showed conservative increase in capacities in the range of 25.9% – 26.9%, while travel times decreased by 55.4%, as the CAV penetration rate shifted from 0 to 100 percent. The trajectory analysis indicated that CAVs have an influence on guiding smoother speeds and acceleration rates of MDVs while an MDV is following a CAV. The results suggest that although headways increased with increasing CAV penetration rate, capacity also increased; however, there should be an optimal headway that maximizes the capacity.

Supplemental Notes:

This paper was sponsored by TRB committee ACP80 Standing Committee on Traffic Simulation Committee.

Report/Paper Numbers:

TRBAM-21-01567

Language:

English

Corporate Authors:

Transportation Research Board

Authors:

Srisurin, Punyaanek
Kondyli, Alexandra

Pagination:

20p

Publication Date:

2021

Conference:

Transportation Research Board 100th Annual Meeting

Location: Washington DC, United States
Date: 2021-1-5 to 2021-1-29
Sponsors: Transportation Research Board; Transportation Research Board

Media Type:

Digital/other

Features:

Figures; References; Tables

Subject Areas:

Highways; Operations and Traffic Management; Planning and Forecasting; Vehicles and Equipment

Source Data:

Transportation Research Board Annual Meeting 2021 Paper #TRBAM-21-01567

Files:

TRIS, TRB, ATRI

Created Date:

Dec 23 2020 11:17AM