Abstract
On-ramp merging is a critical bottleneck in freeway traffic flow, contributing to congestion, accidents, and excessive fuel consumption. Although traditional ramp metering provides macroscopic control, it lacks the granularity for optimizing an individual vehicle’s trajectory. Cooperative merging, enabled by connected and automated vehicles, can potentially enhance traffic efficiency, safety, and fuel economy. However, existing research often neglects the influence of heterogeneous vehicle dynamics, unreliable vehicle-to-vehicle (V2V) communication, and real-time implementation challenges. This paper introduces novel model-free online speed planners for cooperative on-ramp merging. The planners address these limitations by being agnostic to vehicle dynamics, effectively compensating for V2V communication packet drops and incurring only a light computational burden. Comprehensive evaluation, conducted on a real-time traffic-vehicle-communication co-simulation platform integrating high-fidelity vehicle dynamics, a traffic simulator, and recorded V2V communication footprints, demonstrates the effectiveness of the proposed speed planners. Simulation results reveal that the proposed method yields accurate tracking of desired speed and inter-vehicle distance, maintaining low fuel consumption even under high packet drop ratios, and demonstrating real-time implementation efficiency.
| Original language | English |
|---|---|
| Pages (from-to) | 18894-18905 |
| Number of pages | 12 |
| Journal | IEEE Transactions on Intelligent Transportation Systems |
| Volume | 26 |
| Issue number | 11 |
| DOIs | |
| State | Published - 2025 |
Funding
This manuscript has been authored in part by UTBattelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). This work is supported by the US Department of Energy, Vehicle Technologies Office, Energy Efficient and Mobility Systems program under the project “A Cooperative Driving Automation (CDA) Framework for Developing Communication Requirements of Energy Centric CDA Applications” (EEMS120).
Keywords
- Cooperative merging
- model predictive control
- model-free control
- packet drop compensation
- real-time co-simulation