Evaluating neighbourhood roads through agent-based modelling: A step towards the optimal pedestrian desire path system

Neighbourhood roads are critical for developing walkable cities and improving residents' health. This study introduces a prototype system, the Road Evaluation by Desire Path Simulation System (RED-PaSS), based on agent-based modelling (ABM) designed to assess the alignment of roads with pedestrian natural movement. RED-PaSS simulates pedestrian movement to generate optimal desire path systems, representing the most direct and natural paths pedestrians would choose in urban settings. The system evaluates existing roads against these simulated desire paths using key metrics, including road patch distance, road segment alignment with desire paths, and origin–destination (OD) flow efficiency and compares road networks using a ranking index. In the case study, the RED-PaSS was applied to evaluate and rank 708 US neighbourhood-scale road networks using an open-source road dataset from Zillow. Results showed that the roads closely aligned with the simulated desire paths offer more direct and efficient pedestrian routes, enhancing their natural walking movement. In contrast, poorly aligned roads often force pedestrians to take indirect routes, reducing their walkability and efficiency. Incorporating optimal desire paths with road networks also reduces average pedestrian walking distance (for example, by approximately 28%, decreasing from 43 to 31 metres in a sample neighbourhood). Moreover, the ranking of the 708 road networks demonstrated Zipf’s law distribution R 2 = 0.95 , indicating that the majority have poor alignment with their optimal desire paths while very few align well. The top-ranked neighbourhoods demonstrated higher alignment scores and better coverage, effectively connecting areas with high pedestrian demand. The RED-PaSS offers actionable insights for designing walkable cities by predicting optimal desire paths and identifying discrepancies between existing roads and the optimal, which can serve as a valuable tool for urban planners creating more pedestrian-friendly urban environments.