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Multiple-Vehicle Trajectory Planning Framework Considering Vulnerable Road Users

Project Description

This study aims to address the challenge of real-time trajectory planning for connected and automated vehicles (CAVs) while considering vulnerable road users (VRUs) in the environment. The problem lies in efficiently planning trajectories for CAVs in the presence of unpredictable VRUs, ensuring safety and avoiding crashes. The solution involves modeling the decision-making processes of CAVs and VRUs through game theory, incorporating the uncertainty of VRUs' motion using confidence intervals, and designing efficient heuristic algorithms for real-time problem solving.

 

The project's expected outcomes include a technical paper describing the developed trajectory planning framework, along with simulation videos showcasing its effectiveness. This proposal seeks to fill a research gap by exploring novel solutions for this complex problem and contribute to the field of CAV operations. The proposed framework's concepts and validation methods are intended for educational purposes and potential practical implementation in future CAV operations.

Outputs

The project outputs, including:

1. One technical paper/report will be delivered describing the developed multiple-CAV trajectory planning framework. This document will detail the innovative methods and strategies devised to efficiently plan CAV trajectories while accounting for the presence of unpredictable VRUs in the environment. It will offer insights into the novel application of game theory for modeling decision-making among CAVs and VRUs and the incorporation of motion uncertainty using confidence intervals.

 

2. Simulation video clips will be recorded to visualize the effectiveness of the proposed framework. These videos will showcase real-world scenarios where the trajectory planning approach is implemented, highlighting its ability to ensure safety and avoid crashes in dynamic traffic situations.

Outcomes/Impacts

The research output aims to address the challenge of efficiently planning trajectories for CAVs while considering VRUs in the environment. By incorporating VRUs into the trajectory planning framework, this research will have significant implications for transportation safety and efficiency. The output will likely lead to changes in the regulatory and policy framework surrounding CAV operations. The proposed solution, which combines game theory, confidence interval modeling, and heuristic algorithms, will result in a practical and real-time trajectory planning framework. This framework can be applied to actual CAV operations, leading to reduced traffic accidents involving VRUs, improved traffic flow, and enhanced overall transportation system reliability. The developed technical paper and simulation video clips will provide valuable insights for both academia and industry, driving advancements in the field of CAVs and influencing educational curricula.

The research output will positively impact the transportation system by enhancing safety, reliability, and cost-effectiveness. By considering VRUs' uncertain behaviors, the trajectory planning will lead to safer interactions between CAVs and pedestrians, cyclists, and other vulnerable road users. The incorporation of real-time planning will prevent crashes and traffic disruptions, improving overall system reliability. The proposed solution framework's efficiency will lead to optimal traffic flow, minimizing congestion and reducing travel times. These benefits contribute to a safer and more efficient transportation network, reduced environmental impacts due to smoother traffic flow, and potentially lowered costs associated with accidents and congestion-related delays. Furthermore, as the research addresses a critical gap in the literature, it will guide future policy decisions and regulations for CAV operations, fostering a safer and more integrated transportation system for all road users.

Dates

06/01/2023 to 05/31/2024

Universities

University of Wisconsin-Milwaukee

Principal Investigator

Tom Shi

University of Wisconsin-Milwaukee

xiaowshi@uwm.edu

ORCID: 0000-0002-7288-3186

Research Project Funding

Federal: $73,867

Non-Federal: $38,029

Contract Number

69A3552348336

Project Number

23UWM07

Research Priority

Promoting Safety

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