Electric Vehicles (EVs) significantly reduce energy consumption and emissions from on-road operations and help create more sustainable transportation environment by reducing emissions from the entire well-to wheel energy cycle. Differences between hybrid electric vehicle (HEV), plug-in hybrid electric vehicle (PHEV), and battery electric vehicles (BEV) users is an important element in understanding potential impacts on travel demand and vehicle adoption, the fact that these vehicles may be adopted into households that undertake very different vehicle activities and energy usage patterns has not been a primary focus in the literature. This study differentiates between HEV, PHEV, and BEV users across three factors: owner household socio-demographic attributes, household daily travel patterns, and household energy usage profiles. The analyses examine factors that appear to influence users’ preferences towards specific EV types and how the selection of different EV types potentially relates to household socio demographics and daily travel patterns. The 2019 Puget Sound Regional Council travel survey data set serves as the main analytical dataset. Influential factors identified as significant through statistical approaches are employed as variables for developing a two-phase choice model for determining potential EV-purchasing households and their choice of specific EV type. As EVs continue to capture increasing market share over time, these research findings and the resulting vehicle type choice model are expected to significantly improve future travel demand model development, allowing activity-based travel demand models to assign specific vehicles to specific households and then to individual trips in planning scenario analysis.

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Ongoing assessment of system performance monitoring is critical to successful and efficient transportation planning, ensuring that infrastructure investments provide a desired return on investment. As with any new transportation facility, it is important to understand how Express Lane facilities affect travel behavior, resulting on-road vehicle activity, and subsequent person-throughput (a function of vehicle occupancy) as part of the facility performance assessment. This report summarizes the vehicle and person throughput analysis for the I-75 Northwest Corridor (NWC) and I-85 Express Lanes in Atlanta, GA, undertaken by the Georgia Institute of Technology research team for the State Road and Tollway Authority (SRTA). The research team tracked changes in observed vehicle throughput on four managed lane corridors and collected vehicle occupancy (persons per vehicle) data to assess changes in both vehicle throughput and person throughput associated with the opening of new Express Lane facilities. The team collected traffic volumes by video observation (GDOT’s Georgia NaviGAtor machine vision system and SRTA’s vehicle activity monitoring system). The team implemented a large-scale data collection effort for vehicle occupancy across all general purpose freeway lanes and from SRTA’s Express Lanes over a two-year period (before-and-after the opening of the Express Lanes). Between the baseline year (2018) and post-opening year (2019), the team observed a decrease in average vehicle occupancy (persons/vehicle), coupled with a significant increase in traffic volumes, especially on the NWC. The combined effect of increased traffic volumes and decreased occupancy still led to an overall increase in person throughput at all sites. Vehicle throughput on the I-85 corridor increased by about 5-7% and person throughput increased by 1-2% in the morning peak, and increased by around 10% for vehicles and 5% for persons in the evening peak. Vehicle throughput increased by more than 35% on I-575 in the AM and PM peaks, and by the same on I-75 in the AM peaks (only minor increases were noted in the PM peaks), likely due to the diversion of commute traffic from arterials onto the freeway corridor once the Express Lanes opened and congestion declined. Based upon vehicle throughput and occupancy distributions, the largest share of the increase in vehicle throughput in the peak periods came from an influx of single-occupant vehicle activity onto the corridor. Even though the number of carpools traversing the I-575 corridor increased slightly during the morning peak, the overall carpool mode share (percentage of carpools) decreased after the significantly greater numbers of single-occupant vehicles began using the corridor.

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