Urban Space Analysis Lab TAU - Urban movement modeling

URBAN MOVEMENT MODELING

Information on the distribution of movement volumes over the street network is essential for the planning and design of walkable and sustainable urban environments. However, as collection of pedestrian data for all city streets is unfeasible, pedestrian volume models and movement simulation are constructed in our laboratory with respect to various urban areas and different planning approaches. The model are used for planning of not-motorized movement network, creation and maintenance of livable city centers, transportation planning and for evaluating crash risk. We also developed an agent-based (AB) pedestrian volume model at the urban scale.

Agent based modeling of pedestrian mobility in an urban environment

Pedestrian flow models enable the prediction of pedestrian flow and volumes at different times of the day within the street network of a planned urban environment. As such, they can be used in urban and transportation planning for improving pedestrian wayfinding and safety, and to answer questions such as: What would be pedestrian flows after building a train station? Would the existing sidewalks and crossings be sufficient? Should new sidewalks be added? Where should trees be planted or shade elements be constructed?

A video demonstrating a model running movement simulation in project planning :

Pedestrian volume modeling

We construct pedestrian volume models by using street network' centrality measures and geographic information on the urban environment. The models are used for understanding the relations between movement and urban environments that were established according to different planning approaches and as tools for Mobility and Transportation Planning.

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The distribution of movement paths in mall at the segment level

Observed pedestrian movement volume and commercial land use distribution

Visualization of the pedestrian movement prediction model for the future state of the city

pedestrian Movement simulation

We developed an Agent Based Model (ABM) for simulating movement in urban environment. The model was constructed by transforming the various street network centrality measures and land-use variables used in space syntax modeling into agents' spatial behavior parameters. The advantage of our ABM lies in its ability to simulate the combined effect of the street network structure and land-use pattern on movement flows in urban street networks.

Recently, we have developed ABM of pedestrian flow with GAMA platform. The agents in the model represent the residents of city and commuters to the city. The model is based on three data sets were prepared - urban environment characteristics, walking behavior and pedestrian volume observations. The models have been applied in cities in Israel and abroad to predict pedestrian flow in existing and planned urban environments.

Funded by: The Israeli Smart Transportation Research Center, 2024-2026
Funded by: Israel Innovation Authority, 2023-2025

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Frequency of route selection among pedestrians

Difference in the number of pedestrians between 2019 and 2025

Selected publications:

Omer, I., & Zafrir-Reuven, O., Kaplan, N., (Upcoming in 2026), The Israeli City: Structure, morphology, sustainability.
Wolpert L., & Omer I. (2025). Comparative analysis of pedestrian volume models: Agent-based models, machine learning methods and multiple regression analysis
Omer, I. & Kaplan, N. (2019). Structural properties of the angular and metric street network’s centralities and their implications for movement flows
Omer, I., & Goldblatt, R. (2017). Using space syntax and agent-based approaches for modeling pedestrian volume at the urban scale
Omer, I., & Kaplan, N., (2016). An agent-based pedestrian model considering spatial behavior parameters
Ma, D,, Omer, I., Osaragi, T., Sandberg, M., & Jiang, B. (2018). Why topology matters in predicting human activities.
Omer, I., & Goldblatt, R. (2016). Using space syntax and Q-analysis for investigating movement patterns in buildings: The case of shopping malls.
Omer, I., Rofè, Y., & Lerman, Y. (2015). The impact of planning on pedestrian movement: contrasting pedestrian movement models in pre-modern and modern neighborhoods in Israel
Lerman, Y., Rofè, Y. & Omer, I. (2014), Using Space Syntax to Model Pedestrian Movement in Urban Transportation Planning

Evaluating Crash Risk
We developed a method for evaluating the spatial distribution of vehicle and pedestrian trafﬁc crashes relative to the volume of vehicle and pedestrian movement in urban areas.

Selected papers:

Omer, Gitelman, Rofè, Lerman, Kaplan and Doveh (2017). Evaluating Crash Risk in Urban Areas Based on Vehicle and Pedestrian Modeling

The effects of pedestrian and vehicle volumes on crash numbers and crash risks

The spatial patterns of trafﬁc volumes, crashes, and relative crash risks

The spatial patterns of hazardous locations (PI) and relative crash risks