@ CHI '25: ACM Conference on Human Factors in Computing Systems
The Robotability Score
Enabling Harmonious Robot Navigation on Urban Streets
The Robotability Score (R) measures how suitable urban streets are for autonomous robot navigation. It combines 24 indicators of the built environment into one number, so researchers and planners can compare locations and predict where robots can operate without disrupting the people around them. We built and validated a proof-of-concept score for all of New York City.
What is The Robotability Score?
The Robotability Score (R) is a novel metric that quantifies how suitable urban environments are for autonomous robot navigation. Through expert interviews and surveys, we've developed a standardized framework for evaluating urban landscapes to reduce uncertainty in robot deployment while respecting established mobility patterns.
Streets with high Robotability are both more navigable for robots and less disruptive to pedestrians. We've constructed a proof-of-concept Robotability Score for New York City using a wealth of open datasets from NYC OpenData. Pedestrian demand comes from the NYC DOT Pedestrian Mobility Plan, which grades every city street from Citywide Baseline to Global Corridor. Bicycle and vehicle traffic are inferred from a dataset of 8 million dashcam images taken around the city in late 2023.
Key Features
Our findings reveal that these factors collectively account for 48% of the total Robotability Score. Areas with highest R are 4.3 times more "robotable" than areas with lowest R.
Complete Indicator List
The score draws on 24 indicators. Hover over any term to see how we measure it. Each indicator is paired with a sample set of weights to show how the Robotability Score might change under different indicator values.
- Sidewalk width0 = narrow, 1 = wide
- Pedestrian density0 = high density, 1 = low density
- Density of street furniture (e.g. garbage, poles)0 = high density, 1 = moderate density, 2 = low density, 3 = no furniture
- Sidewalk / Surface roughness0 = gravel, 1 = cobblestones, 2 = smooth asphalt
- Surface condition0 = potholes, 1 = major cracks, 2 = minor cracks, 3 = smooth
- Wireless communication infrastructure0 = no infrastructure, 1 = basic Wi-Fi, 2 = 5G, IoT
- Slope gradient0 = high slope, 1 = no slope
- Presence of charging stations0 = no charging stations nearby, 1 = multiple charging stations in proximity
- Local attitudes towards robots0 = highly negative, 1 = somewhat negative, 2 = neutral, 3 = somewhat positive, 4 = highly positive
- Curb ramp availability0 = no curb ramps, 1 = curb ramps at some intersections, 2 = curb ramps at most intersections, 3 = curb ramps with tactile paving
- Weather conditions0 = ice, 1 = snow, 2 = puddles, 3 = leaves, 4 = clear
- Crowd dynamics0 = emergency, 1 = commuting, 2 = shopping, 3 = leisure
- Traffic management0 = no system, 1 = basic signage, 2 = street lights, 3 = advanced traffic control
- Surveillance coverage (CCTV)0 = no coverage, 1 = low coverage, 2 = moderate coverage, 3 = high coverage
- Zoning laws and regulation0 = no regulations, 1 = moderate stringency, 2 = high stringency
- Bike lane availability0 = no bike lanes, 1 = bike lanes on most roads, 2 = separated bike lanes on all roads
- Street lighting0 = no lighting, 1 = excellent lighting
- Existence of shade0 = no shade, 1 = extensive shade
- GPS signal strength0 = no signal, 1 = very strong signal
- Pedestrian flow0 = very high flow, 1 = very low flow
- Bicycle traffic0 = very high traffic, 1 = very low traffic
- Vehicle traffic0 = very high traffic, 1 = very low traffic
- Existence of detailed digital maps0 = no digital maps, 1 = highly detailed maps
- Intersection safety0 = no infrastructure, 1 = basic crosswalks, 2 = zebra crossings with signals, 3 = advanced intersection management
Proof-of-Concept Video
Project Team
Paper Citation
If you use our work in your research, please cite our paper:
@inproceedings{10.1145/3706598.3714009,
author = {Franchi, Matthew and Parreira, Maria Teresa and Bu, Fanjun and Ju, Wendy},
title = {The Robotability Score: Enabling Harmonious Robot Navigation on Urban Streets},
year = {2025},
isbn = {9798400713941},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3706598.3714009},
doi = {10.1145/3706598.3714009},
booktitle = {Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems},
articleno = {737},
numpages = {17},
series = {CHI '25}
}