intelligent computer vision agents optimising pti safety ... · computer vision based approach...

Intelligent Computer Vision agents Optimising PTI Safety and Train Dwell Times Lancaster University

Dr Gruffydd Morris, Professor Plamen Angelov, Lancaster University Dr Howard Parkinson, Digital Rail

COF-PTI-04 Intelligent computer vision agents optimising PTI safety and train dwell times March 2018

Project Scope

Challenge: To assess the feasibility of Computer Vision (CV) improving safety standards at the PTI while reducing impact of passengers on dwell times

3 Work Packages:

1. Asses the scope of the current issues surrounding PTI safety and impact of passenger boarding / alighting on dwell times

2. Through mode of prototype, test the capability of CV to augment safety at the PTI

3. Again through prototype, provide an analysis of busyness on trains and platforms with the goal of impacting dwell times


Project Scope

Solution to augment information available to users and stake holders

Detect object and users in or approaching the PTI.

Detect and identify users and objects on-board carriages.

Computer Vision based approach using surveillance systems

Detect and identify individual objects

Intelligent source

integration

Key: - Platform based - Carriage based

Station Staff Information

Passenger Information

Train Staff Information

Detect and identify individual objects

Passenger Information


Findings: Stakeholders have different requirements

Driver:

– High risk / on track info on approach

– Passengers near doors on dwell

– High risk (red) on depart

Platform Staff:

– Busyness on approach and dwell

– Simple alerts – what is happening where on the platform

– Safety info on depart

Control room Staff:

– Busyness only when too high

– Safety screens

Passengers

– Only busyness on approach and dwell. Nothing on depart


Findings

Can detect where passengers are on the platform (if they cross the yellow line)

Alerts can be sent to drivers, staff and other stakeholders if someone is stuck in the gap

Can get a measure of the number of passengers on both the train carriages and the platforms

All using existing camera infrastructure

Processing can be done in real time on a computer the size of a credit card (Raspberry Pi for example)


Limitations

Shadows and sun glare can interfere with detections

For gap detection, a yellow line (or similar) lengthways down the image is required

Camera perspective can be an issue if fish lens or similar is employed (regular key stoning can be compensated for)


How it works: Gap Safety

Uses CV analysis with filters applied to remove clutter

Computationally efficient

Detects static and moving objects

Distinguish between objects based on motion criteria

An example of the detection criteria of people and motion, and distinguishing between zones.


Busyness information

Both show platform loading information

–Top image: quiet around the train and quiet on the platform

–Bottom image: Shows busyness increase on platform and slight increase near train

This information set does not include gap analysis

Busyness behind the line


Busyness over the line



Under the hood: Gap analysis combined with busyness


Busyness around the line


Time over the line

Busyness around the line



Time over the line


Under the hood: Busyness on Platform and Carriages

Analyses both platforms and carriages

Provides a busyness measure for each, compensating for perspective distortion


What a Stakeholder might see: Drivers


What a Stakeholder might see: Staff

ALERT : PLATFORM 1 ZONE 2


What a Stakeholder might see: Passengers


Stakeholder benefit

Passengers (customers)

– improved safety at the PTI

– optimisation of their PTI experience

Drivers

– increase drivers experience and go some way to reduce stress and pressure.

– assist the driver to make accurate decisions

– assist the driver to maintain on-time services by reducing passenger boarding dwell time, further helping to reduce safety related incidents.

Train and Station operators –

– Improved safety of passengers through a reduction in PTI FWI incidents

– faster passenger boarding at the PTI can aid station operators in running a safer and quicker service.

– (side effect) improved passenger movement will help to reduce larger crowds and subsequently improving safety


Suggested future work

Stakeholder engagement to improve design and fit in with current workflows of the industry

Pilot programme would be useful to understand how stakeholders interact with the system

Human factors study, in collaboration with work done on other projects such as CONSIST

Questions and Thank you

intelligent computer vision agents optimising pti safety ... · computer vision based approach...

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