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Asal Mehditabrizi

3 papers hereh-index 335 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author2
  • middle author1

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cs.RO1
  • physics.soc-ph1
  • stat.AP1

identity via Semantic Scholar / OpenAlex

most citedA deep reinforcement learning approach to assess the low-altitude airspace capacity for urban air mobility

2 citations · 2 across the 3 of their papers we have counts for

collaborators

3 papers

physics.soc-ph2024

Integrating En Route and Home Proximity in EV Charging Accessibility: A Spatial Analysis in the Washington Metropolitan Area

Asal Mehditabrizi, Behnam Tahmasbi, Saeed Saleh Namadi +1

This study evaluates the accessibility of public EV charging stations in the Washington metropolitan area using a comprehensive measure that accounts for both destination-based and…

stat.AP2024

Using Geographically Weighted Models to Explore Temporal and Spatial Varying Impacts on Commute Trip Change Due to Covid-19

Saeed Saleh Namadi, Behnam Tahmasbi, Asal Mehditabrizi +2

COVID-19 has deeply affected daily life and travel behaviors. Understanding these changes is crucial, prompting an investigation into socio-demographic and socio-economic factors.…

cs.RO2023★ 2 cited

A deep reinforcement learning approach to assess the low-altitude airspace capacity for urban air mobility

Asal Mehditabrizi, Mahdi Samadzad, Sina Sabzekar

Urban air mobility is the new mode of transportation aiming to provide a fast and secure way of travel by utilizing the low-altitude airspace. This goal cannot be achieved without…

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