Publication Detail

Design and Simulation-Based Evaluation of an Eco-Driving Strategy at Signalized Intersections Considering Mixed Traffic

UCD-ITS-RP-19-25

Reprint

Available online at: https://trid.trb.org/view/1573104

Suggested Citation:
Yang, Menglin, Pan Liu, Yueyue Fan, Jiamin Wu (2019) Design and Simulation-Based Evaluation of an Eco-Driving Strategy at Signalized Intersections Considering Mixed Traffic. Transportation Research Board 98th Annual Meeting

The primary objective of the present study is to design an eco-driving strategy at signalized intersections and evaluate its impacts considering mixed traffic of connected and automated vehicles (CAVs) and human driving vehicles. An eco-driving strategy for CAVs approaching an intersection was developed to achieve individual optimal fuel efficiency while balancing mobility and smoothness of driving. The proposed strategy considered mixed traffic of different traffic demands and vehicle types with varying penetration rates of CAVs. The control problem was transferred to a nonlinear programming problem with an approximation model to reduce computational difficulty. Numerical simulations were conducted to evaluate the impacts of the proposed eco-driving strategy considering multiple performance measures, including fuel consumption, emissions, mobility, and safety. Simulation results suggested that for the entire traffic flow, the reduction in fuel consumption ranges from 0% to 24%, and the reduction in CO2 emission ranges from -1% to 28%. Compared with baseline scenarios, mobility roughly leveled off and safety was improved significantly. Out experiments showed that the benefits of eco-driving via CAVs grow sharply as the penetration rate of CAVs increases until the rate reached somewhere between 30%-50%. While considering the indirect benefits on human driving vehicles, even at a relatively low penetration level, the benefits of the proposed eco-driving strategy can be significant.

Key words: Connected vehicles, ecodriving, exhaust gases, fuel consumption, mathematical models, signalized intersections, vehicle mix