Vehicle-to-Everything (V2X) Communication: A Roadside Unit for Adaptive Intersection Control of Autonomous Electric Vehicles (2409.00866v1)

Abstract: Recent advances in autonomous vehicle technologies and cellular network speeds motivate developments in vehicle-to-everything (V2X) communications. Enhanced road safety features and improved fuel efficiency are some of the motivations behind V2X for future transportation systems. Adaptive intersection control systems have considerable potential to achieve these goals by minimizing idle times and predicting short-term future traffic conditions. Integrating V2X into traffic management systems introduces the infrastructure necessary to make roads safer for all users and initiates the shift towards more intelligent and connected cities. To demonstrate our solution, we implement both a simulated and real-world representation of a 4-way intersection and crosswalk scenario with 2 self-driving electric vehicles, a roadside unit (RSU), and traffic light. Our architecture minimizes fuel consumption through intersections by reducing acceleration and braking by up to 75.35%. We implement a cost-effective solution to intelligent and connected intersection control to serve as a proof-of-concept model suitable as the basis for continued research and development. Code for this project is available at https://github.com/MMachado05/REU-2024.

• The paper demonstrates that a V2X-enabled RSU can reduce vehicle acceleration changes by up to 75%, boosting fuel efficiency and safety at intersections.
• It employs a combined simulation and real-world testing approach using sensors, Raspberry Pi, and Wi-Fi connectivity for reliable traffic signal communication.
• The cost-effective design, with RSU units under $500, offers scalable potential for smart intersection control in urban transportation systems.

Overview of V2X Communication for Intersection Control

This paper addresses the implementation of Vehicle-to-Everything (V2X) communication for autonomous electric vehicles, emphasizing adaptive intersection control. The authors present a method to enhance road safety and fuel efficiency through a cost-effective roadside unit (RSU) deployed at intersections. The system's primary objective is to reduce idle times and optimize driving behaviors at intersections, aligning with the broader vision of intelligent and connected transportation systems.

Methodology

The V2X communication architecture proposed integrates a RSU with self-driving vehicles to create an adaptive intersection control mechanism. Utilizing technologies such as DSRC and cellular networks, the system informs vehicles about traffic light states through wireless communication. The research employs both a simulated environment using GazelleSim and real-world experiments to validate the system's efficacy.

Simulation and Real-World Implementation

The research involves a combination of a virtual model and physical testing at a controlled intersection. The authors employ two electric vehicles equipped with sensors and a Raspberry Pi-based RSU. The RSU facilitates intra-agent communication and publishes traffic light states via a Wi-Fi connection.

The lane-following algorithms, including K-means and DBSCAN, are tested to ensure reliable vehicle navigation. The adaptive speed control algorithm calculates the optimal speed for vehicles to approach intersections, minimizing unnecessary acceleration and deceleration.

Results and Performance

Quantitative assessments reveal that the adaptive system achieves up to a 75.35% reduction in acceleration changes through intersections compared to human drivers, suggesting significant improvements in fuel efficiency. Furthermore, the architecture's cost-effectiveness could promote more widespread deployment than traditional traffic systems.

Cost Implications

The implementation cost for each RSU is under $500, presenting a stark contrast to more traditional systems, potentially paving the way for more efficient urban traffic management solutions.

Implications and Future Directions

This research lays foundational work for the deployment of intelligent intersection control systems. The proposed method could lead to reduced emissions and enhanced safety for pedestrians and vehicles alike. Future improvements could explore dynamic traffic light adjustments based on real-time traffic conditions, elevating the level of autonomy and adaptability of the system.

Continuous development in this domain may necessitate further integration with broader smart city infrastructures, accommodating higher traffic densities and mixed autonomous-human driving environments. Investigating fail-operational strategies and robust connectivity solutions will be pivotal for system resilience.

In summary, the paper offers a promising outlook for V2X communication as a feasible path toward smarter and more efficient urban mobility, with practical implications for future research and development in autonomous vehicle networks.