The capacity drop phenomenon, which reduces the maximum bottleneck discharge rate following the onset of congestion, is a critical restriction in transportation networks that causes additional traffic congestion. Consequently, preventing or reducing the occurrence of the capacity drop not only mitigates traffic congestion, but can also produce environmental and traffic safety benefits. To address this issue, this project developed and evaluated a speed harmonization (SH) algorithm based on a bi-level feedback control system with the assistance of vehicle-to-infrastructure (V2I) communications. The algorithm computes advisory speed limits for individual vehicles to prevent the breakdown of downstream bottleneck discharge by regulating traffic flow approaching the bottleneck, which in turn reduces traffic stream delay, emissions and fuel consumption levels. To assess the benefits of the algorithm, a section of Interstate 66 in Northern Virginia was simulated with the INTEGRATION microscopic traffic simulation model, and five trailers were installed on the road to collect real-time traffic data for each vehicle equipped with V2I communications to implement the SH algorithm. The simulations demonstrated that the algorithm significantly mitigated road congestion when a capacity drop occurred at a bottleneck. Also, the study results showed that higher market penetration rates (MPRs) of vehicles equipped with the SH algorithm led to higher SH algorithm benefits. In particular, at 100% MPR, the bottleneck discharge flow rate increased by up to 1.5%, and the vehicular delay decreased by about 22%. Moreover, with the SH algorithm, CO2 and fuel consumption levels were reduced by up to 3.5%. A 100% MPR is the best-case scenario. However, the results also demonstrated that an MPR of even 10% is sufficient to produce overall emission and fuel consumption savings.


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