PRE2018 4 Group7

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Group members:

Name	Student ID	Email	Study
Emiliyan Greshkov	1281666	e.greshkov@student.tue.nl	Computer Science
Thomas Janss	1006697	t.f.w.janss@student.tue.nl	Mechanical Engineering
Perry Kloet	1236356	p.a.j.kloet@student.tue.nl	Computer Science
Bram Schut	1019001	b.b.j.schut@student.tue.nl	Computer Science
Sem de Werdt	1017882	s.j.a.d.werdt@student.tue.nl	Automotive Technology

General information:

Problem statement and objectives

As our urban environment grows, so does the need for means of transport for commuters and leisure travellers. Trains are getting cramped and more overcrowded. This makes it increasingly more important to use the available space and seating optimally to maximize the amount of people in the train and the comfort in which these people can travel.

A lot can be improved in terms of space usage in trains. We want to achieve this goal by providing train passengers with accurate and real-time boarding data. This data can be used to give the passengers information on where best to board the train. We will deliver a system to measure live information about compartments, with a good accuracy/cost ratio. This information can be displayed on all kinds of interfaces,such as websites and apps, but also on interactive train platforms or on screens within the trains.

Our focus during the project will be on trains in the Dutch railway network, since trains, stations, railway networks and stakeholders differ a lot all over the world so it will be hard to make a uniform design that will work everywhere. However, this system design can get tweaked for implementation in different trains.

Many railway companies are already experimenting on this subject. The state of the art in the Netherlands is the NS, who is showing in their app, how crowded each compartment is. They get this information by building a scale in the tracks of each station and weigh each compartment. However this method only creates a rough estimate of how crowded each compartment is and this measuring can only be done upon departure of the train. We want to make a system that does active measuring, that can make an estimation in real-time and have a higher accuracy than the system that NS is using now.

In this project we will focus on three parts. The first part is the measuring. As said above we want to measure in real-time and achieve a higher accuracy. Part two is the processing of this measuring data. What information can we get from this data and in what ways it can be used. The final part of the project will be how this information can be communicated to the train passengers. There we will give examples in what ways this data can be used to make passengers better distribute over the train.

Previous done work

1) NS App, The NS app shows how crowded each carriage is on some trajects, using sensors in the rails that measure the weight of the train.
2) Schiphol airport train station, has an Intelligent Platform Bar (IPB) giving the passengers boarding information like where the doors will be.
3) s'Hertogenbosch train station has an Intelligent Platform Bar showing if there is space in the carriage.
4) Trainstation in Stuttgarden Germany has a luminous platform

Users

Sort of users <br\> Researching the user’s needs is of large importance for the current crowding in trains. A distinction between different groups of users could be made: Primary, secondary and tertiary users. Train travelers belong to the primary user group. Secondary users consist out of train companies or track operators. Tertiary users typically consist of software/system developers. <br\><br\> Train travelers will benefit from an increased spread of people along the train. Passengers will be able to spread out more at the platform, due to displayed information before the arrival of the train at the platform. Having boarded the train, the chance of a seat will be higher than when randomly boarding the train. This way, uneven distribution of clusters of travelers in different carriages can be prevented. This ensures more comfort for passengers, both inside of the train and while boarding or waiting for the train.<br\> <br\> Secondary users also profit from this new technology as a side effect. Fewer irritated travelers will complain, providing a better image for train operators such as NS (Nederlandse Spoorwegen) or DB (DeutscheBahn). Next to that, with better spread of passengers, the amount of carriages of a train can be optimized/minimized, leading to lower costs for these public transport companies. <br\><br\> The tertiary users consist of software and system developers. More technology in the train means that they have more work, leading to a higher revenue for these companies. Next to this, improvements on the platform also have an influence on Prorail, which manages the platforms. These platforms could be designed in a better way, leading to a higher train density at stations located in mostly populated environments. <br\>

User requirements
Primary users:<br\>

• Passengers should be distributed equally over the carriages to improve the chance of getting a seat to maximize comfort
• Passengers should be be able to know in advance where they can board the train with the assistance of a user-friendly interface
• Passenger privacy should be respected, thus their data should only be used for counting

Secondary users:<br\>

• NS should have a proper way of counting people inside of a train
• Ns should be able to know exactly what kind of material is used

Approach, milestones and deliverables

Approach
The problem will be divided into two subproblems. A counting system and a user interface. The counting system has to accurately count to amount of people in each compartment and compare it with the available space to get the information about the available space. For this, nowadays a weigh bridge is used. However, we want to provide real-time data, since there is much activity around arrival or departure in a train. The user interface has to pass the information on to the passengers in a clear and understandable way. This user interface will consist of tiles that can have different colors or an LED screen providing information. Next to the tiles at the platform, an integrated app which also will be shown inside the trains will be developed. Combining both should provide the best possible solution for the problem of overcrowded train compartments and ineffective use of space.
Milestones
The first milestone is finding out which counting technique will be used. When this is known, the basic layout for the app can be made. Also the basic layout for the physical system can get designed then. Second milestone is writing the code and checking if it works, by applying different test cases. In the meantime, the counting system can be completely designed and constructed. Merging these two systems is the next milestone. Coupling this data to NS' live data will be the last milestone.

Deliverables
The deliverables at the end of the project will be a real-time system that accurately counts the amount of people in each compartment, and a user interface that passes that information onwards to the passengers as effectively as possible. Both parts will be combined to make a total system that gets accurate information about the occupation of each compartment and passes it onwards to the passengers through a straightforward user interface within the train, at the platform and in the app.

Content

Counting

Figure 1: Smartphone usage

Counting people could be done in various ways. Currently, NS already uses weightbridges (19), Amtrak and some busses in America are using treadle mats (8) and infra red beams are used in South-Africa to monitor the corrupt behaviour of some bus drivers (7). However, all these options require quite some adaptions to the public transportation or the railnetwork itself and therefore can be quite expensive. A more prommesing option would be using the location of a mobile phone of travelers. For this application Bliptrack could be used. Blibtrack is a system that can detect WiFi/BLE/Bluetooth-enabled devices (18). By placing these sensors at inside critical places, such as inside the coupé and at the balcony, a proper measurement can be made of how many mobile phones are present inside the train. However, there is a small group of people that is not accounted for in the trains: People that are not using their phone because they just don't, or people that do not even have a phone. Figure 1 shows the amount of people living in the Netherlands without a phone. A questionaire under 3000 people has showed that 87 percent of Dutch citizens are in possesion of a phone. The most promising growing group consists of seniors. That group was growing by 19 percent per year in 2016, while 18-34 ghas grown with 3 percent and 35-54 with 7 percent. Other instances like statica find of mobile phone usage of 85 percent. Of those approximate 14.5 million people, 52 percent use their phone while using public transportation. Therefore, this application makes a good chance of implementing counting via WiFi/BLE/Bluetooth. An important fact to note is that only ~40% of those smarthpone-users actually have bluetooth turned on [citation needed], and the ns already has a wifi network

Needed Data

In order to be able to effectively determine the rate of occupancy for each compartment, the following few pieces of data are needed:

• The lengths and positions of all passenger cars upon arival.
• The (average) weight of passenger cars when empty.
• The average human's weight. According to the London School of Hygiene & Tropical Medicine the average human worldwide weights around 62kg, and in the netherlands - around 69kg.
  People also carry clothes and carry luggage - which should also be taken into account.
• The number of seats in each passenger car, so that it can be calculated whenever a carriage has no free seats, or even additional, standing passengers as well.

https://www.telegraph.co.uk/news/earth/earthnews/9345086/The-worlds-fattest-countries-how-do-you-compare.html

Data Processing

Knowing the needed data, whenever a carriage gets weighed with the passengers inside, by subtracting its empty weight and dividing by the average person's weight we can get how many people would be in that compartment. Calculating the number of people on the comparment can also be done using alternative methods such as pressure mats or infra red beams.
Then, the ratio of people in each compartment to the seat capacity can be mapped to colours from green to red, which would depict how full each compartment is, and this would be sent to the display and shown to the users.

Platform indication

Figure 2: DB Stuttgart-Bad Cannstatt

In 2018, the German railway operator has tested a form of "assisted" boarding in Stuttgart-Bad Cannstatt at a S-Bahn station. Information about the train is given via tiles with LEDs. Occupancy rates are just like the Netherlands estimated via load of the train and some new methods, such as CCTV, door sensors and ticket information. The concrete slaps at the platform can provide information where the doors are located and how busy the coupés approxmiately are. However, there are a lot of things that cannot be done yet with this system. Therefore, this project will focus on improving the customer experience of these tiles. A few requirements are set for these tiles. The tile should be able to:

• Show where the doors will be
• Show where 1st and 2nd class is located (also top or bottom)
• Show how full the carriages are
• Show where special carriages are located (e.g. wheelchair or bicycle)
• Show that traveler has not reached the boarding area yet
• Show that a train cannot be boarded
• Show that a train is about to leave

<br\> The tiles should at least consist of three seperate colors of LEDs. Red, which can be associated with 1st class, blue, which can be associated with 2nd class and white or any other color, which indicates where the doors are located. The most convenient pattern for these platform tiles is a cross with LED diods and two horizontal strips of LED diods in the middle of the tile. There are two possible ways for the doors, either only LED diods could light up where doors will locate, or information could be displayed at small LED screens. The two horizontal lines can cope with indication where first class and second class is located by adjusting the color. By adjusting the DPI (Dots Per Inch) of those lines, the occupancy of a carriage can be displayed, where a low DPI-concentration would stand for many places available and a continuous line means a full carriage. At the small LED screens, also additional information like wheel carriage et cetera could be displayed. For trains that cannot be boarded due to arrival on their final destination, all crosses could emit red light, reminding the passenger to board another train. While decoupling trains due to under-occupancy, which happens a lot at stations like Eindhoven and Amsterdam, arrows could indicate the train travelers to board the front of the train.<br\> <br\> <br\>

Figure 3: Concepts tile

Planning

Week	What to do	Person(s)
3	In-depth research
4	Concepting
5	Detailing
6	Building and Testing
7	Finish prototype
8	Prepare presentation
9	Finish wiki

Who's doing what?
The problem will be split into several parts. Each group member will work on a part that best fits their skills to optimize the end results.

Relevant scientific papers:

Research

1) https://www.alstom.com/our-solutions/digital-mobility/optimet-real-time-train-occupancy-smoother-passenger-flow-platforms
2) https://www.researchgate.net/publication/280735165_A_robust_system_for_counting_people_using_an_infrared_sensor_and_a_camera
3) https://www.dilax.com/en/public-mobility/portfolio/seat-management/
4) https://www.researchgate.net/publication/323027620_Smart_Bus_An_Automated_Passenger_Counting_System
5) https://www.google.nl/url?sa=t&rct=j&q=&esrc=s&source=web&cd=21&cad=rja&uact=8&ved=2ahUKEwiCudCpgPbhAhUJr6QKHRJQBlM4ChAWMAp6BAgIEAI&url=https%3A%2F%2Fpdfs.semanticscholar.org%2F55a0%2F9a9adb1e7905f99607846f7a286e3f39bf17.pdf&usg=AOvVaw0ZK1-RYUZ15nYZshrA0cHs
6) https://www.usenix.org/legacy/events/hotos03/tech/full_papers/gruteser/gruteser_html/
7) https://www.researchgate.net/publication/267387412_APPROPRIATE_TECHNOLOGY_FOR_AUTOMATIC_PASSENGER_COUNTING_ON_PUBLIC_TRANSPORT_VEHICLES_IN_SOUTH_AFRICA <br\> 8) https://www.google.com/url?sa=t&rct=j&q=&esrc=s&source=web&cd=9&cad=rja&uact=8&ved=2ahUKEwiR9p2Uw4HiAhWNZ1AKHUeuBI4QFjAIegQIAhAC&url=http%3A%2F%2Fwww.movetec.fi%2Fimages%2Fpdf%2FTapeswitch-tuntoreunat.pdf&usg=AOvVaw0I2j-QILXPBH48Jq9N8T_d <br\> 9) http://www.instantcounting.com/technology.html
10) https://reader.elsevier.com/reader/sd/pii/S2352146517307159?token=960AEE718A60D47CF7E7F08701AD27EDC69A9913B5CBAA27DE0D3C81DA363B16C3FF122C62F1C5A3EB601DE44AE97706
11) https://www.tandfonline.com/doi/abs/10.1080/23249935.2013.795199?casa_token=U8PLb3o3OP8AAAAA:0a6jqeVO-6AR9W3YHihtHAag3XO5rRUyfBMkblxZQqgccoFb-AFONkHsasHFF4kCI8CDsYv7PV1B
12) https://ieeexplore.ieee.org/abstract/document/5715528
13) https://www.ns.nl/reisinformatie/service-verbeteren/zitplaatszoeker.html
14) https://www-sciencedirect-com.dianus.libr.tue.nl/science/article/pii/0262885694900531

16) https://patents.google.com/patent/US7788063B2/en
17) https://trid.trb.org/view/481481
18) https://blipsystems.com/hardware-overview/
19) https://nos.nl/artikel/2271485-ns-vrije-zitplaatsen-op-meer-trajecten-in-app-te-zien.html
20) https://repository.tudelft.nl/islandora/object/uuid:a67e550b-5c38-456e-9e21-90802ad36f6a?collection=education
21) https://www.researchgate.net/publication/276408492_Semisupervised_Pedestrian_Counting_With_Temporal_and_Spatial_Consistencies
22) https://www.its.ucla.edu/wp-content/uploads/sites/6/2015/11/passenger-flows-in-underground-railways-stations-platform.pdf
23) http://www.strc.ch/2017/Bosina_EtAl.pdf
24) http://ijtte.com/uploads/2018-12-08/b2ddb9bc-d1c1-4333ijtte.2018.8(4).04.pdf
25) https://www.deutschebahn.com/en/Digitalization/DB_Digital/productworld/Luminous_Plazfrom_en-1214708
26) https://onlinelibrary.wiley.com/doi/abs/10.1002/atr.5670180102
27) https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=8117189
28) https://www.mdpi.com/1424-8220/12/10/14196

Categorize

Counting people:
1,2,3,4,7,8,9,11,12,14,17,18,21
Application itself:
4, 19, 25
Walking behaviour at platform:<br\> 10,20,22, 23, 24

1:
Alstom is a company that provided sensors tecnology (passive IR) to count people boarding and deboarding. At the platform, LED's show which compartments are full and which are not. With colors they influence people where they board. THe system is modular and can therefore be placed at any station of any length.
2:
pyro-electric infrared (PIR) sensor and a camera (2). Two possible ways: detection-based and map-based methods. Latter option more precise in counting (10,11). Differential PIR sensors used, since this is only possibility for differentiate between entry and exit of an environment and ordinary activities in that area by analyzing body movement. A couple of modules are used that consist of multiple PIR sensors. This data is collected and are input for a list of classifiers. Wavelet transform is used to create output signal. Using only camera yields ~ 80% efficiency, while integrating PIR has ~ 100% efficiency (Tutorial: https://www.youtube.com/watch?v=6Fdrr_1guok )<br\> 3:<br\> DILAX' active infrared sensors are capable of detecting people entering a door. The system is only active while doors are open. Each DILAX LAN can operate 382 sensors. The system is capable of counting in dense popluated areas with a high accuracy.
4:
Also, a pressure sensor could be used. Pressure sensors behaves like a open-closed circuit which delivers voltage while closed that can be placed underneath the padding of the seat. The Voltage is converted from a real output to a binary output which is created by Arduino. The application can read the amount of 0's and 1's and can convert that into images. The used pressure pad detects weight from 20 kg and higher.<br\> 7: <br\> Next to PIR, infrared beams could be used that detect when interrupted. Can be either active or passive: Passive sensors sense IRradiation and with that can find moveing direction, active sensors actually can locate the person. Ultrasonic sensor works approxiametly the same way. Test in South Africa: 28000 Rand (1866 euros) per bus with 1 sensor per door. This gives an accuracy level of 95%, while 3 sensors per door give 99%. Other methods are also given in this article, giving treadle mats, IR again, load cell and normal camera.<br\> 8: <br\> Tapeswitch is a company that produces copyright public transport equipment. Among those also belongs the treadle mat which already are in use at Amtrak trains, Copenhagen and melbourne. These mats commenly are produced with multiple zones that have different functionalities: Opening and closing a door or actions such as counting passengers. <br\> 9: <br\> Instant counting is a company that provided treadle mats with the provided software. This software is capable of detecting the movement of a person when boarding/deboarding. It is possible to link 90 of these mats to eachother in one system. An interface shows the amount of people entering and the amount of people exiting. The system can detect direction of walking and can track different people simmultaniously.
10:
Maybe not directly relevant, but we could take into account how people walk accros the station to the destinated train to improve user experience (USE-aspects)
11:
A system that estimated the number of passengers using the weight of the train. This has the huge advantage that errors in measurement do not propagate (ex: if you use an infraredsensor and you miss one passenger leaving, the system will always keep counting one too many. Weightsensors don't have this issue)
See 13 (<- not an article), appearantly, the ns is already doing this, so we need to expand on this idea.
Appearantly, this idea has been pattented (see 16)
12:
Using face recognition. Might be a bit overkill to install an entire camera for this one purpose, and might give some privacy issues, but seems straigforward
14:<br\> Counting with IR can sometimes give difficulties in dense areas. Image sequence processing does not. Divided into two parts: Target detection and target validation and direction-estimation. This way, the algorithm is rather fast. The system is more accurate and still fast in dense areas.
17:
A study on how to interpret data from multiple pressure sensors (a "pressure mat")
18:
This company counts the ammount of people going in or out a door using sensors that track WiFi/BLE/Bluetooth-enabled devices. When someone walks past this sensor with his mobile phone he wil get counted and tracked with a user ID. When he later leaves the door, the count will go down again.
19:
NS launches an app, that helps find passangers train seating, by putting weight sensors in the tracks, which measure the weight distribution of each carriage.
20:
Research from TU Delft about spreading passangers over the platform. Giving crowdness information did not lead to much more spreading. Giving passengers personal boarding advice has better results.
21:<br\> Available techniques of APC suffer from using sequences of seperate frames, where much energy is being lost. To address this issue, this paper proposes a semisupervised methodology to extract temporal consistency in a continuous sequence of unlabeled frames. The experimental results show that this is more robust and does not require much training data 22:
This study examines the planning and analysis of station passenger queuing and flows to offer rail transit station designers and transit system operators guidance on how to best accommodate and manage their rail passengers.
23:
Study of passanger flows, with hypothesis about passanger behaviour. They study the important factors for stations getting more crowded.
24:
Analysis on how passengers distribute along the platform.
25:
Application of a luminous platform in Stuttgart-Bad Cannstatt station
27:
Bluetooth counting in a city