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Research Projects

STATUS: Complete YEAR: 2021 TOPIC AREA: Connected and autonomous systems Integrating freight and passenger systems CENTER: PSR

Connectivity-Based Cooperative Ramp Merging in Multimodal and Mixed Traffic Environment

Project Summary

Project number: PSR-21-20
Funding source: US DOT
Contract number: 69A3551747109
Funding amount: $99,999
Performance period: 9/16/2021 to 9/15/2022

Project description

On freeways, ramp merging has been considered as a representative scenario that may cause traffic bottlenecks or hotspots of traffic accidents. Conventionally, ramp metering is adopted as a key strategy to mitigate adverse impacts in the merging areas. In principle, it utilizes traffic signal operation (usually consisting of two-phase signal timing, i.e., green and red) at the on-ramp to regulate inflow rate of the traffic entering the mainline in response to prevailing mainline traffic conditions in order to avoid downstream traffic demands exceeding roadway capacities. Existing ramp metering strategies mainly rely on traffic detection from sensors (e.g., inductive loop detectors) at fixed locations to provide inputs for signal control at on-ramps. However, these strategies introduce additional stop-and-go maneuvers for the on-ramp traffic, leading to additional delays and energy consumption. In addition, under some scenarios (e.g., short or lack of acceleration lane), on-ramp vehicles (especially heavy-duty trucks) may experience difficulties accelerating to a desired speed for safe and comfortable merging maneuvers. Thanks to advances in connected and automated vehicle (CAV) technology, more efficient ramp merging strategies have been developed. Nevertheless, most existing CAV-based ramp merging strategies assume that all the vehicles are CAVs or do not differentiate vehicle type (i.e., passenger cars vs. heavy-duty trucks). In this study, it is proposed to develop and evaluate a vehicle-to-everything (V2X) based cooperative ramp merging system that takes into account the heterogeneity of traffic flows, i.e., multimodal (cars and trucks) and mixed (connected and non-connected vehicles), in the real world. In response to the type and connectivity of involved vehicles during merging, the proposed system will provide the optimal strategy to encourage cooperative driving for mitigating any adverse impacts from the merging maneuvers. Furthermore, a Unity-SUMO co-simulation platform will be set up and a multi-player-in-the-loop simulation approach will be adopted to validate the proposed system and evaluate its effectiveness from both the driver's and traffic operator's perspectives.


Guoyuan Wu
Associate Researcher
Department of Electrical and Computer Engineering
Riverside, CA 92521
United States
[email protected]


Kanok Boriboonsomsin
Associate Research Engineer, Bourns College of Engineering - Center for Environmental Research & Technology
1084 Columbia Avenue
Riverside, CA 92507
United States
[email protected]