This paper examined how automated vehicles can be controlled to improve mobility and reduce fuel consumption as they approach speed reduction zones on freeways. The fundamental idea of Speed Harmonization is to eliminate bottlenecks and keep traffic moving at constant speeds.
Optimal acceleration/deceleration profiles were developed with respect given to estimated safety parameters needed to avoid rear-end collisions. Researchers then formulated a proposed control algorithm that adjusts speed prior to the reduction zone and compared against three alternatives.
Using a microscopic simulation model test bed, the researchers evaluated the proposed control algorithm's performance compared with three other approaches.
- Baseline - Human driving performance based on the Weidmann car-following model
- Variable speed limit (VSL) -using SPEed ControllIng ALgorIthm using Shock wave Theory (SPECIALIST).
- Vehicular-based Speed Harmonization (SPD-HARM) algorithm
Findings from the study indicated that the proposed approach significantly reduces both fuel consumption and travel time.
Considering varied traffic volume levels, fuel consumption for each vehicle was reduced by 19 to 22 percent when using the proposed control algorithm, as compared to the baseline scenario in which human-driven vehicles were considered, by 12 to 17 percent compared to a variable speed limit algorithm, and by 18 to 34 percent compared to a vehicular-based speed harmonization (SPD-HARM) algorithm.
In addition, travel time was improved by 26 to 30 percent using the proposed control algorithm as compared to the baseline scenario, by 3 to 19 percent compared to the VSL algorithm, and by 31 to 39 percent compared to the vehicular-based SPD-HARM algorithm.