Systematic method for the multifunctional allocation of street space

Cities are increasingly rethinking their approaches to transport system planning and design to improve mobility, quality of life, and urban resilience, within a framework of sustainability and equity. In this context, the allocation of public space emerges as a critical lever. Yet, street design decisions remain largely shaped by political and technical trade-offs, reinforcing the dominance of the mobility function, primarily dominated by the automobile, at the expense of place-making and environmental considerations.

In Montreal, private cars occupy approximately 75% of street space while accounting for only 66% of total trips, with roadside areas further burdened by stationary vehicles (Lefebvre-Ropars, 2021; ARTM, 2023). This spatial imbalance is compounded by other planning deficiencies, notably a tree canopy coverage of just 21%, falling short of the 30% threshold deemed necessary for climate resilience (CMM, 2024; OCPM, 2024).

Recent studies suggest that a strategic reorientation of mobility policies, anchored in more equitable street-space distribution, could halve car passenger- kilometers while tripling cycling and doubling public transit use (Axhausen, 2025). Responding to this challenge, the present research develops an indicator-based methodology grounded in principles of equity and utility to guide the balanced reallocation of street space.

The proposed approach begins with a typology of multimodal and multifunctional street configurations, calibrated to the range of right-of-way widths found across the network. These typologies feed into an iterative optimization process using a genetic algorithm to maximize a composite function that integrates, among other factors, network capacity, travel time, and diversity of uses.

Empirical analysis will draw on origin–destination survey data and detailed street network attributes from the Montreal region. Given the availability of comparable datasets across Quebec, the methodology is designed to be replicable in other urban contexts. Ultimately, this project will yield a scalable decision-support tool for street-space allocation, equipping cities with a strategic framework for multimodal transport planning and resilient urban design.