International Conference on
Sensing and Modeling for Pedestrian Mobility and Safety

The conference will cover a range of topics, including the latest advancements in:

• Sensors that monitor road behaviour and detect risks in those behaviours
• Data analytics, including machine learning and deep learning, to interpret those data streams
• Models, including simulation models, to identify and characterise risk in road interactions
• Addressing reliability and universality, such as low light conditions, low positioning accuracy conditions, and rule-following versus coordinating traffic cultures
• Sensor integration
• Enriching digital twins of roads or traffic with road safety information
• Privacy aspects in tracking road users
• Novel LiDAR-Camera fusion algorithms to detect and track road users to estimate their trajectory and velocity profiles
• Novel methods to identify undesirable road user behaviour, including speeding and near-misses using detected tracks and understanding the role of road infrastructure in the observed user behaviour
• Novel frameworks for continuous monitoring of the road networks and identification of accident-prone regions based on near-misses and traffic violations
• Understanding road user behaviour, identifying any patterns, understanding and quantifying road interactions including near-misses, potential collisions, speeding, and other risky behaviour in the context of interaction between pedestrians and other road users
• Long-term monitoring frameworks for continuous monitoring of the city; data structures so as to include the ‘risk’ information in the city maps that are used by agencies and the general public
• Short-term predictions of road behaviour
• Data analytic and sensing frameworks for pedestrian infrastructure detection and monitoring.

Submission Instructions and Template:

Instructions for authors and template: click here
All submissions must be made through the Springer’s METEOR system. Click here to submit

All authors are required to register on the METEOR system for submission.

Please refer to the PDF regarding submission instructions on METEOR.

Prospective authors can submit either a full paper (at least 6 A4 pages), a case study (at least 4 A4 pages) or an abstract (max. 2 A4 pages). Accepted full papers and case studies will be considered for inclusion in the conference proceedings.

• Long abstract (upto 2 pages): The content should clearly communicate the problem statement, research gaps and provide an overview of the analyses undertaken. Please note that the long abstracts will not be considered for the conference proceedings.
• Case study (at least 4 A4 pages): The work should demonstrate new, original and unpublished applications of the proposed methodology/technology. Case studies will be considered for conference proceedings.
• Full paper (at least 6 A4 pages): Full papers must present original research with well defined research outcomes that are generalizable in nature.

Furthermore, the authors are requested to identify the most suitable track among the following options:

• Infrastructure and Road User Sensing
• Pedestrian Mobility
• Pedestrian Safety

The conference proceedings of select papers will be published through Springer with an indexed proceedings.

It is planned to publish the peer-reviewed and selected papers of the conference as proceedings with Springer in their prestigious Lecture Notes in Civil Engineering series (https://link.springer.com/series/15087). For detailed instructions for author and editors of conference proceedings, kindly visit the following link: https://www.springer.com/us/authors-editors/conference-proceedings. Select papers from the conference will be published by Springer as a proceedings book volume. Springer will conduct quality checks on the accepted papers and only papers that pass these checks will be published. Abstracts/extended abstracts and short papers (less than 4 pages) are not considered for publication.

Registrations are closed !

Step 1: Pay the registration fees via SBI Collect as per your category.

Step 2: Fill out the Google Form