Implementation of Connected and Autonomous Vehicles in Cities Could Have Neutral Effects on the Total Travel Time Costs: Modeling and Analysis for a Circular City
A modeling experiment by researchers from the University of Santiago, Chile and the Technical University of Catalonia sought to understand the impacts of Connected and Automated Vehicle (CAV) adoption in urban spaces.
The mathematical model, based on a theoretical circular city structure, incorporated various projected impacts of CAV usage. These included a lowering of travel-cost, given the increased freedom of CAV users; increased average speeds and road capacity, given CAVs' platooning capabilities; and a decrease in operational costs, because of CAVs' increased fuel efficiency. The model used continuous approximations to understand the impacts of CAV adoption, considering simulated demand zones across the city.
The researchers analyzed the overall impact of CAV adoption by examining the total cost to users and agencies, as well as the total congestion level. Both were analyzed for various rates of CAV market penetration. The model found that while the total cost fluctuated for different values of market penetration, it overall decreased as penetration rates increased.
However, the analysis also found that congestion could increase relative to the current system for middling values of market penetration--particularly when between 20 percent and 50 percent of vehicles are automated.
Agencies seeking to promote CAV adoption should anticipate that negative results could arise during the process of transitioning from manual to automatic vehicles. The increase in congestion is expected to be completely outweighed by the point of 70-80 percent CAV adoption, for a significant overall increase in efficiency.
On the whole, the mixed results from the analysis indicate that CAV adoption--which is likely to take a significant amount of time--will not be a unilateral benefit to cities, and in fact many of the positive changes will be mostly or completely offset by changes in traveler behavior.