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Greenhouse gas emissions have dramatically risen since the early 1900s withU.S. transportation generating 28% of U.S. emissions. As such, there isinterest in reducing transportation-related emissions. Specifically,sustainability research has sprouted around signalized intersections asintersections allow different streams of traffic to cross and changedirections. Recent research has developed mixed traffic control eco-drivingstrategies at signalized intersections to decrease emissions. However, theinherent structure of a signalized intersection generates increased emissionsby creating frequent acceleration/deceleration events, excessive idling fromtraffic congestion, and stop-and-go waves. Thus, we believe unsignalizedintersections hold potential for further sustainability improvements. In thiswork, we provide an emissions analysis on unsignalized intersections withcomplex, real-world topologies and traffic demands where mixed traffic controlstrategies are employed by robot vehicles (RVs) to reduce wait times andcongestion. We find with at least 10% RV penetration rate, RVs generate lessfuel consumption, CO2 emissions, and NOx emissions than signalizedintersections by up to 27%, 27% and 28%, respectively. With at least 30% RVs,CO and HC emissions are reduced by up to 42% and 43%, respectively.Additionally, RVs can reduce network-wide emissions despite only employingtheir strategies at intersections.

Analyzing Emissions and Energy Efficiency at Unsignalized Real-world Intersections Under Mixed Traffic Control