To study the potential benefits of connected and automated vehicles (CAVs), researchers at Oak Ridge National Laboratory developed a simulation framework that analyzes the impact of partial market penetration of CAVs on fuel consumption, travel time and traffic flow in a merging on-ramp scenario under low, medium and heavy traffic volumes.
In a study published in IEEE Transactions on Intelligent Vehicles, they reported that an increased number of CAVs communicating and coordinating driving activity stabilize traffic flow and, depending on the traffic volume, can reduce fuel use by more than 40%.
Intersections, merging roadways, speed reduction zones along with the drivers’ responses to various disturbances are the primary sources of bottlenecks that contribute to traffic congestion and stop-and-go driving with significant implications in both fuel consumption and traffic stability –. In 2015, congestion caused people in urban areas in US to spend 6.9 billion hours more on the road and to purchase an extra 3.1 billion gallons of fuel, resulting in a total cost estimated at $160 billion.
Connected and automated vehicles (CAVs) provide the most intriguing opportunity for enabling users to better monitor transportation network conditions and to improve traffic flow. CAVs can be controlled at different transportation segments, e.g., intersections, merging roadways, roundabouts, speed reduction zones and can assist drivers in making better operating decisions to improve safety and reduce pollution, fuel consumption, and travel delays.—Rios-Torres and Malikopoulos
ORNL researchers created a simulation framework to study how coordinated connected and automated vehicles could improve traffic flow and reduce energy consumption during a merging on-ramp scenario while interacting with human drivers. Credit: ORNL.
The simulation results showed that the benefits in fuel consumption are realized under the following conditions:
100% penetration of CAVs under any traffic volume; and
in mixed traffic only when the traffic volume is low.
In contrast, the benefits in travel time are realized under the following conditions:
All the vehicles are CAVs traveling under medium and high traffic flows; and
in mixed traffic under medium and high traffic flows only if there are more than 50% CAVs on the road.
In the case of travel time, for lower CAVs penetration, the low number of CAVs on the roads are adversely affected by the “random” human driving patterns. … by comparing the flow-density diagrams for different CAVs penetration, we observed that as the number of CAVs on the road communicating and coordinating their operation increases the traffic patterns become more stable.—Rios-Torres and Malikopoulos
Future research will explore the impact of CAVs in various traffic scenarios and determine whether CAVs can indirectly influence the driving performance of human-driven cars.
Jackeline Rios-Torres and Andreas A. Malikopoulos (2018) “Impact of Partial Penetrations of Connected and Automated Vehicles on Fuel Consumption and Traffic Flow”