Making CAV Deployments Compatible with Complete Streets Objectives for Safe and Efficient Operation Phase I

Mahmassani, Hani S.; Hegde, Sharika J.; Raymer, Meredith; Khakpour, Amirmohammad · 2025 · ROSA P / Center for Connected and Automated Transportation. Northwestern University

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Summary

This Phase I report addresses the tension between the deployment of Connected and Autonomous Vehicles (CAVs), which prioritize system-wide efficiency, and Complete Streets objectives, which emphasize human-centered design for vulnerable users like pedestrians and cyclists. The research aims to resolve this conflict by developing a methodological framework that evaluates how CAV deployments can be made compatible with Complete Streets principles through strategic infrastructure design and interaction management. The study seeks to provide transportation planners with evidence-based tools to balance technological efficiency with safety and accessibility in limited urban space. The researchers employed three integrated analytical approaches. First, they conducted network-level analysis using area-based Network Fundamental Diagrams (NFDs) derived from SUMO microsimulations to quantify multimodal traffic flow across varying infrastructure configurations. Second, they modeled microscopic interactions between CAVs and pedestrians in two-lane environments using an extended Drift Diffusion Model to analyze pedestrian crossing decisions and their impact on vehicle flow. Third, they developed a probabilistic space utilization framework using Monte Carlo simulations to identify spatial and temporal conflict hotspots and evaluate competing demands for street space. Key findings indicate that modal separation yields substantial efficiency gains. Network throughput increased from 0.09 to 0.18 veh/min/m² when transitioning from shared to separated infrastructure, representing up to a 100% improvement in efficiency. Pedestrian separation via sidewalks generated the largest initial benefits across all modes. However, in space-constrained environments where complete separation is impossible, managing interactions becomes critical. The microscopic analysis identified optimal pedestrian-CAV interaction parameters that minimize conflicts while preserving reasonable crossing opportunities. The probabilistic framework successfully identified areas requiring systematic management strategies, demonstrating that effective interaction management is essential for maintaining safety and efficiency when physical segregation is not feasible. The study concludes that while infrastructure separation provides optimal outcomes for both CAV flow and user safety, effective management of modal interactions is necessary for real-world urban environments. The developed methodological toolkit enables planners to evaluate design alternatives, prioritize separation where feasible, and implement evidence-based strategies for managing unavoidable conflicts. This work establishes a foundation for Phase II implementation and real-world validation, offering a systematic approach to designing urban streets that accommodate both autonomous vehicle technology and the needs of vulnerable users.

Key finding

Network throughput increases from 0.09 to 0.18 veh/min/m² when transitioning from shared to separated infrastructure, demonstrating that modal separation produces substantial efficiency gains.

Methodology

modeling

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

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• traffic density