01628738

Component

Advances in connected and automated vehicle technologies have resulted in new vehicle applications, such as cooperative adaptive cruise control (CACC). Studies have shown significant increases in capacity and stability due to CACC, but most previous work has relied on microsimulation — ignoring route choice and demand impacts. To study the effects of CACC on larger networks and with user equilibrium route choice, the authors incorporate CACC into the link transmission model (LTM) for dynamic network loading. First, the authors derive the flow-density relationship from the MIXIC car-following model of CACC. The flow-density relationship has an unusual shape; part of the congested regime has an infinite congested wave speed. However, the authors verify that the flow predictions match observations from MIXIC modeled in VISSIM. Then, they use the flow- density relationship from MIXIC in LTM. Although the independence of separate links restricts the maximum congested wave speed, for common freeway link lengths the congested wave speed is sufficiently high to fit the observed flows from MIXIC. Results on a large freeway corridor indicate that CACC could significantly reduce travel times over current conditions.

This paper was sponsored by TRB committee ADB30 Standing Committee on Transportation Network Modeling.

01618707

17-05626

English

16p

2017

Transportation Research Board 96th Annual Meeting

Digital/other

Figures; References

Autonomous intelligent cruise control; Car following; Dynamic traffic assignment; Mobile communication systems; Traffic density; Traffic flow; Vehicle to vehicle communications

Cooperative adaptive cruise control; Flow-density relationships

Highways; Operations and Traffic Management; Planning and Forecasting

Transportation Research Board Annual Meeting 2017 Paper #17-05626

TRIS, TRB, ATRI

Dec 8 2016 12:14PM