Proper evaluation of traffic operations integrating connected and autonomous vehicles (CAVs) requires accurate representation of these emerging technologies in microscopic simulation. This paper evaluates the ability of microscopic simulator PTV-VISSIM (Version 10.0) to simulate CAVs, and presents a comprehensive CAV model extension. In addition, emissions modeling is integrated with VISSIM to calculate real-time energy and emission estimates. The evaluation of VISSIM revealed that its internal CAV modeling has several limitations, such as modeling connectivity and complex vehicle behavior. For external modeling, there are two available VISSIM interfaces. The Component Object Model (COM) Application Programming Interface (API) is the superior approach for fetching data and modeling connectivity, whereas the External Driver Model (EDM) is a better tool for lateral and longitudinal control. The simulation extension developed leveraged both interfaces. An isolated signalized intersection was simulated to demonstrate the impact of connected vehicle (CV), autonomous vehicle (AV), and CAV traffic on speed, delay, and travel time. In addition, trajectory data, combined with the Motor Vehicle Emission Simulator (MOVES) method, were utilized to obtain energy, fuel consumption, and greenhouse gas emissions. The results show that CAVs result in net improvement in travel time and speed. However, emissions did not follow the same trend. While increasing AV penetration rates resulted in emissions reductions, increasing CV and CAV penetration rates resulted in higher emissions. While the CV logic chosen for testing seeks to maximize the likelihood of vehicle arrival-on-green, the algorithm likely results in increased variations in second-by-second accelerations, leading to overall higher emissions.
The Smart Cities Collaborative aims to mitigate transportation challenges and inequities with new approaches and technologies (e.g., ridesharing). Therefore, assessing community transportation needs is essential. The team explored the travel behaviors, challenges, and/or opportunities among low- and high-socioeconomic status (SES) communities. Using Community-Based Participatory Research principles, four focus groups were conducted to investigate residents’ behaviors and experiences with transportation availability, accessibility, affordability, acceptability, and adaptability. Focus groups were recorded, transcribed, and verified before thematic and content data analysis. Participants with low SES ( n = 11) discussed user-friendliness, uncleanliness, and bus accessibility challenges. Comparatively, the participants with high SES ( n = 12) discussed traffic congestion and parking. Both communities had concerns about safety and limited bus services and routes. Alternatively, opportunities included a convenient fixed-route shuttle. All groups stated the bus fare was affordable unless multiple fares or rideshare were needed. Findings provide valuable insight when developing equitable transportation recommendations.
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