Methodology

The study focused on the PM peak (4:45 PM to 5:45 PM) on three different simulation networks: a generic urban freeway segment with a merge; a 15-mile freeway section of I-95 including seven interchanges; and a 7.8-mile segment of I-81 with varying grades and no interchanges. The research team investigated capacity changes using VISSIM traffic simulation software with an intelligent cruise control car following model. Twenty-one scenarios were developed to test different market penetration rates for LVs, AVs, and CAVs. Scenarios for I-81 varied by vehicle composition with Heavy Vehicles (HV) percentages of 0, 30, and 50 percent. For I-95, demand was increased to 150 and 200 percent of the current demand for all ramps and mainline inputs to the simulation to see how increasing demand would be affected by the AV and CAV technologies. I-95 scenarios were considered with 100 percent AV and 100 percent CAV only.  A paired two-tailed t-test was performed for all the scenarios to determine whether the difference between results obtained from different technology distributions was significant.

Findings

• In the case of higher penetration rates of AVs and CAVs, the increased capacity was significant. With 100 percent AV scenario, the capacity increased by 28.7 percent on the basic freeway segments and 48.4 percent at the merging freeway segments. CAVs, on the other hand, increased capacity by 91.3 percent on the basic freeway segments and 59.8 percent at the merging segments.
• The introduction of AVs could increase capacity even at low penetration rates. Compared with the 100 percent LV scenario, the capacity increase was estimated at 6.3 percent for the 80 percent LV, 20 percent AV scenario, and 12.9 percent for the 80 percent LV, 20 percent CAV scenario.
• The aggressive scenario increased the capacity up to 42 percent on the basic freeway segment and increased it up to 13.9 percent at the merging freeway segment. In some merging cases, the aggressive driving parameters decreased capacity because the aggressive driving interrupted smooth merging.
• CAVs and AVs yielded better throughput in most scenarios, and CAVs outperformed AVs during congestion. CAVs, as compared to LVs, produced a throughput increase between 16 and 27 percent. AVs, on the other hand, increased throughput between 15 and 21 percent.
• On congested segments, the 100 percent AV scenario showed the most significant differences in average traffic speed as compared with the 100 percent LV scenario. Average speed in the AV scenario was up to 18 percent greater than the LV scenario under the 150 percent demand case, and up to 14 percent greater under the 200 percent demand case.
• AVs and CAVs improve performance in corridors with extended grades and high truck volumes. The greatest improvements over the 100 percent LV scenario were found in the 100 percent CAV scenario. Capacity increases with traffic consisting of 0, 30, and 50 percent HVs were 86, 65, and 63 percent, respectively.
• Increased speeds were found with increasing AV and CAV market penetrations. In scenarios with increased presence of HVs and lower speeds, AVs and CAVs were more capable of showing significant speed increases over the LV only scenario (up to 49 percent for the CAV only case).