01660940

Component

https://doi.org/10.1177/0361198118793257

https://doi.org/10.1177/0361198118793257

Cooperative adaptive cruise control (CACC) systems have the potential to improve traffic flow and fuel efficiency, but these effects are challenging to estimate. This paper reports the development of a micro-simulation model to represent these impacts for heavy trucks using CACC when they share a freeway with manually driven passenger cars. The simulation incorporates automated truck-following models that have been derived from experimental data recorded on heavy trucks driven under CACC, adaptive cruise control (ACC), and conventional cruise control (CC). The simulation includes other behavioral models for lane changing, lane change cooperation and lane use restrictions for trucks to better capture real-world traffic dynamics. The paper explains the calibration of the simulation method for a 15-mile urban freeway corridor with heavy truck traffic and significant congestion. Simulation results for different market penetration rates show that truck CACC improved traffic operations for trucks in terms of vehicle miles traveled, average speed, and flow rate. In addition, truck CACC did not adversely affect passenger car operations and in some locations it even produced considerable improvements in the general traffic conditions.

18-05698

English

pp 55-65

2018

Transportation Research Record: Journal of the Transportation Research Board

Print

Figures (6) ; References (27) ; Tables (2)

Automobiles; Autonomous intelligent cruise control; Car following; Case studies; Connected vehicles; Cruise control; Freeways; Heavy duty trucks; Lane changing; Managed lanes; Microsimulation; Traffic congestion; Traffic flow; Traffic platooning; Urban areas; Vehicle mix

Interstate 710

Southern California

Data and Information Technology; Highways; Operations and Traffic Management; Vehicles and Equipment

TRIS, TRB, ATRI

Jan 8 2018 11:27AM

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