Vehicles that possess interconnectivity features improve the rate at which they traverse intersections, while those automated vehicles lacking such connectivity can actually impede traffic due to their safety protocols. The findings stress the critical role of vehicular communication and interaction with traffic management systems in balancing safety and travel efficiency.
Recent research indicates that “connected” vehicles, which can wirelessly interact with each other, significantly facilitate the movement of traffic at crossroads. On the contrary, automated vehicles that lack communication capabilities can extend the time required to pass through intersections. The primary reason for this is safety considerations.
Ali Hajbabaie, the primary author of the research paper and an associate professor in the field of civil, construction, and environmental engineering at North Carolina State University, states, “Public interest in automated vehicles is primarily fueled by two factors: enhancing the safety of passengers and reducing transit durations.”
“While there exists considerable research suggesting that automated vehicles do indeed elevate safety levels, our computational modeling-based study posits that mere automation is insufficient for minimizing travel time. For a true optimization of travel time, vehicles need to be both automated and connected, allowing them to communicate with each other as well as with traffic management systems governing intersections.”
For the purpose of this study, a computational simulation model was employed to mimic varying traffic conditions. Four categories of vehicles were considered in the model: Human-Driven Vehicles (HVs); Connected Vehicles (CVs), which are operated by humans but share data with other connected vehicles and traffic control systems; Automated Vehicles (AVs); and Connected Automated Vehicles (CAVs).
Hajbabaie explains, “Due to their programmed safety features, it is presumed that AVs operate more cautiously in comparison to human drivers. This conservative driving style is partially responsible for their increased safety. CVs and CAVs, however, are engineered to receive advance information on the status of traffic lights, enabling them to modify their speeds to avoid unnecessary stops at intersections. Consequently, the traffic flow of CVs and CAVs is likely to be more fluid and have fewer stops as opposed to HVs and AVs.”
In the study, 57 different traffic simulations were executed to evaluate the influence of various variables on the time required to pass through an intersection. These simulations took into account different combinations of HVs, AVs, CVs, and CAVs.
A prominent conclusion drawn from the study was that a greater proportion of CVs and CAVs on the road led to an increase in the capacity of the intersection. More vehicles could transit through the intersection more rapidly when a higher percentage of vehicles had connectivity features. Increased intersection capacity consequently leads to a reduction in the number of vehicles queuing at red lights.
“Nevertheless, we observed that a higher concentration of AVs, which lack connectivity, resulted in slower intersection transit times,” notes Hajbabaie. “These AVs are programmed to be risk-averse to avoid collisions. Our findings underline the necessity to integrate connectivity features in both individual vehicles and overarching traffic control systems.”
The study’s limitation is its reliance on computational modeling. “Real-world field tests involving a mixed fleet of HVs, AVs, CVs, and CAVs within a connected traffic control system can be complex and financially prohibitive,” Hajbabaie adds. “Furthermore, including human drivers in these tests could present safety risks, making these computational simulations especially valuable for identifying potential challenges before they become life-threatening issues.”
The study, titled “Effects of Connectivity and Automation on Saturation Headway and Capacity at Signalized Intersections,” was authored by Ali Hajbabaie, Mehrdad Tajalli, and Eleni Bardaka and was published on August 11, 2023, in the Transportation Research Record: Journal of the Transportation Research Board. It received financial backing from the North Carolina Department of Transportation.
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Frequently Asked Questions (FAQs) about vehicle connectivity
What is the main finding of the recent study on automated vehicles and traffic flow?
The main finding of the study is that while connected vehicles improve traffic flow at intersections, automated vehicles that lack such connectivity can actually slow down traffic. The study emphasizes the importance of vehicle-to-vehicle communication and interaction with traffic control systems for both safety and efficiency.
Who conducted the research and what methodology was used?
The research was conducted by Ali Hajbabaie, an associate professor at North Carolina State University, along with other researchers. The team employed a computational simulation model to mimic varying traffic conditions and ran 57 different traffic simulations to assess the impact of various variables on intersection travel time.
What types of vehicles were considered in the study?
The study considered four types of vehicles: Human-Driven Vehicles (HVs), Connected Vehicles (CVs), Automated Vehicles (AVs), and Connected Automated Vehicles (CAVs).
How do Connected Vehicles (CVs) and Connected Automated Vehicles (CAVs) improve traffic flow?
CVs and CAVs are designed to wirelessly communicate with each other and with traffic control systems. This allows them to adjust their speeds to avoid unnecessary stops at intersections, resulting in smoother traffic flow and increased intersection capacity.
Why do automated vehicles without connectivity slow down traffic?
Automated vehicles without connectivity features are programmed to drive conservatively to enhance safety. This risk-averse behavior results in slower transit times through intersections, as compared to human-driven or connected vehicles.
What are the implications of this study for the future development of automated vehicles?
The study suggests that for optimal traffic flow and safety, future development should focus on integrating connectivity features in both individual vehicles and overarching traffic control systems.
What are the limitations of this study?
The study relies on computational modeling, which is a limiting factor. Real-world field tests involving a mixed fleet of different types of vehicles can be complex, financially prohibitive, and could present safety risks.
Was the study supported or funded by any organization?
Yes, the study received financial support from the North Carolina Department of Transportation.
More about vehicle connectivity
- Transportation Research Record: Journal of the Transportation Research Board
- North Carolina State University Research
- North Carolina Department of Transportation
- Advancements in Vehicle-to-Vehicle Communication
- Computational Modeling in Traffic Management
- Safety Concerns in Automated Vehicles
- Ali Hajbabaie’s Academic Profile
7 comments
What about the environmental impact? Safer and efficient is great but are these cars gonna be green too?
That’s some food for thought. we keep hearing about how automation will solve all our problems. Guess its not that simple.
Wow, never thought about how self-driving cars could actually make traffic worse. its kinda counterintuitive if you think about it.
Im all for safety, but if it slows down everyone, what’s the point? Need a balance for sure.
Interesting, so connectivity is the key here. Might be a good time to look into companies specializing in vehicle-to-vehicle communication.
So basically, the future is in connected vehicles? Makes sense, but the tech’s gotta be secure. Last thing we need is someone hacking into the system.
The study’s just based on computational models? Would love to see some real-world testing. You can only learn so much from simulations.