Evidence map›Paper›PMID 41939007›Full record

ArticleTransportation research record2025

Behavior of a Person-Following Robot in Pedestrian Environments: Laboratory Experimentation and Simulation.

Ruowei Li, Farah Ghizzawi, Tho V Le, Matthew J Roorda

Abstract read
In one paragraph

Article in Transportation research record, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ruowei LiDepartment of Civil & Mineral Engineering, University of Toronto, Toronto, ON, Canada.ORCID https://orcid.org/0009-0006-1356-3031
Farah GhizzawiDepartment of Civil & Mineral Engineering, University of Toronto, Toronto, ON, Canada.ORCID https://orcid.org/0000-0001-8345-7249
Tho V LeSchool of Engineering Technology, Purdue University, West Lafayette, IN, USA.ORCID https://orcid.org/0000-0003-0166-2412
Matthew J RoordaDepartment of Civil & Mineral Engineering, University of Toronto, Toronto, ON, Canada.ORCID https://orcid.org/0000-0001-6724-0154

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As e-commerce continues to grow, the demand for fast and efficient last-mile delivery is increasing. Person-following robots is a solution that is now beginning to be deployed to assist foot couriers in performing last-mile delivery tasks in public areas, such as underground pedestrian walkways and malls. Although they have proved their capacity to operate successfully in uncrowded and highly regulated spaces like warehouses, it is still uncertain whether their performance would be satisfactory in crowded, unstructured, and complex environments. This study proposes a simulation approach for evaluating the performance of a commercial person-following delivery robot in dynamic pedestrian environments. Laboratory experiments were conducted to understand the robot's operating characteristics. Based on empirical observation, a computer simulation model of the robot was developed in a pedestrian simulator, which was calibrated and validated with experimental data. This model was expanded to include pedestrian crowds such that the performance of the robot was evaluated under various crowding scenarios. Research limitations and recommendations for future work are identified.

Indexed as

city logistics and last-mile strategieshuman factorspedestriansrobot-pedestrian interactionsimulation delivery robot

Identifiers

PMID41939007
PMCPMC13046279

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.