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Improving transport in Malta using GIS and LBS

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A presentation prepared to the University of Malta as part of my MSc. Informatics. This seminar discusses ways and improvements how can a GIS driven system help and improve the current situation in ...

A presentation prepared to the University of Malta as part of my MSc. Informatics. This seminar discusses ways and improvements how can a GIS driven system help and improve the current situation in Malta. This presentation also provides a survey discussing how the Maltese view the public transport and gives out interesting conclusions as to where the GIS needs to tackle. The study focuses mainly on ways as to where and how to improve the routes, promoting cultural places, buses ETA and taxi fleet handling amongst others.

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Improving transport in Malta using GIS and LBS Improving transport in Malta using GIS and LBS Presentation Transcript

  • Matthew Pulis MSc. Informatics Student University of Malta January 2009
  • Introduction
    • Introduction to the main terms of the study:
      • Location Based Services (LBS)
      • Geographic Information Systems (GIS)
        • Transport Geographic Information Systems (T-GIS)
    • Identifying the key players in the industry:
      • Private Sector (private vehicle drivers)
      • Public Sector
        • Public Transport
        • Road Network
      • Third parties affecting the traffic flow
      • Information bearers
  • What is a GIS?
    • A combination of “ hardware, software, and data for capturing, managing, analyzing, and displaying all forms of geographically referenced information ” (ESRI, 2007) .
    • When compared to maps, GIS has the advantage that data presentation and storage are separate (Bernhardsen, 2002) .
    • Such an IS can be used for resource management, vehicle routing, environment impacts assessment, geography planning to name a few.
    View slide
  • What are LBS?
    • LBS can be seen as applications that use the user’s physical location to provide a custom service (Schiller & Voissard, 2004)
    • Such a service is a personalised service to the user, and unique due to the current location the user is at.
    • Making use of such services can “ save time and aggravation in our increasingly wireless world ” (Capella & Bennett, 2002) .
    • According to Research and Markets (2006) , by 2010 it is estimated that revenues generated from LBS will reach €622 million
    View slide
  • E-Government
    • M-government is defined as the strategy and its implementation involving the utilization of all kinds of wireless and mobile technology, services, applications and devices for improving benefits for citizens, business and all government units (Kushchu and Kuscu, 2003)
    • In M-government implementation, the most important issue is the alignment of organizational change with organizational strategic goals, followed by informationflow integration and then technology issues (Gang, 2005)
    M-Government
  • Sample scenarios where an LBS was used by Public Sector
    • e911 project in 1996 by the Federal Communications Commission (USA)
    • e112 project in 2003 by the EU Commission (EU)
    • Distress analyzer by Suffolk County Police (UK)
    • Wired with Wireless program by Infocomm Development Authority of Singapore
    • HK Mobile Host by HK Tourism Board
    • Real-time subway information in Stockholm (SE)
    • Crime reporting in Thailand
    • Real time bus arrival in Italy
  • Demographic Studies
  • Vehicle Details
  • Rating Malta’s Transport
  • Reactions to Govt. Proposals
  • Building the project Would electronic information tempt you to use the public transport more often? By electronic information it is understood that on every bus stop you get the ETA (Estimated Time of Arrival) of the next bus for example Will an SMS service where you can request the time of the next bus on a particular bus stop help you use the Public Transport Service more? Will a routing information screen help you increase your daily usage of Public Transport? By routing information screen, it is understood that you enter your starting bus stop and final location and the website returns to you the Bus Stop near the location, with a schedule of the upcoming bus routes with the ETA of each of the itineraries
  • Private Vehicle Handling
    • The study should focus on:
      • Balancing the vehicles over road network
      • Avoid congested areas
      • Study usage of road network
      • Better planning of new roads, and when to commence works
      • Help drivers be aware of road conditions
  • Studying automatic routing for private vehicles
    • The main difference is between Static and Dynamic routing
    • Two main studies are going to be reviewed:
      • Conflict-free Vehicle Routing: Load Balancing and Deadlock Prevention Klimm et al (2008)
        • A two-stage routing approach . In the first phase focus is granted to balancing the load on the edges of the given graph. In the second phase , the detection and avoidance of deadlock situations is investigated.
      • Dynamic Routing of Automated Guided Vehicles in Real-Time (Gawrilow et al 2007)
        • The key feature of this algorithm is that it avoids collisions, deadlocks and livelocks already at the time of route computation (conflict-free routing)
  • Static Routing Simplified deadlock situation . Both vehicles are trying to occupy the same portion/edges of the network, thereby blocking each other. Reservation procedure. Each vehicle reserves the next part of the route. Mutual exclusive reservations guarantee a collision-free execution of computed (static) paths. “ To conclude the evaluation, we remark that the static routing approach is good as long as there are only a few potential deadlocks that have to be avoided since the greedy reservation procedure is of value in this case, but if the reserved areas become larger caused by a more complicated deadlock prevention, it reaches its limits.” ( Klimm et al, 2008)
  • Dynamic Routing “ The main advantage of our model and algorithm over the known online methods is that the time-dependent behaviour of AGVs is fully modeled, such that both conflicts and deadlock situations can be prevented already at the time of route computation . The newly designed model is not only very accurate in the mapping of properties of the actual application but, as we show in our computational experiments, it is also well suited for being used in a real-world production system.” ( Gawrilow et al , 2007) Illustration of the real-time computation on three consecutive arcs with transit time 1. (a) shows the situation before the new request arrives. There is a graph with some blockings (orange) and some time-windows (green) on the time axis (y axis). The task is to compute a quickest path that respects the time-windows. This is illustrated in (b). The chosen path is blocked afterwards (see (c)).
  • Avoid Congested Networks
    • This can be done by several methods :
      • Having Automated Boards delivering
      • updated messages (Z Hui-ling et. al, 2003)
      • Drivers can subscribe to this service via a
      • website and receive SMS Alerts with traffic
      • conditions (Balke et. al, 2003)
        • This service can be further enhanced by having sensors on the road network itself and notifying the driver by SMS (whilst reaching an area) that there are problems ahead on the road ( Sharma et. al, 2004)
        • Another enhancement is the use of making available the updates as an XML / RSS feed (Pulis & Attard, 2008)
  • Building the proposed system
    • Road Sensors
    • Road Closure Database
    • Road incident Database
    GIS Server Web Server RSS / XML Feeds Electronic Notice Boards GPS Devices Traffic Lights
  • Mastering the Traffic Lights
    • “ capacity of the network strongly depends on the cycle times of the traffic lights” (Brockfeld et. al, 2001)
    • The data collected from the sensors used in the previous model, can be used to control the traffic flow too.
    • Such data can be collated in the GIS and compared to temporal rules (For example creating rules to state that traffic to Valletta before 8.30am gets priority)
    • Depending on such rules, and actual data from the sensors, priority and length of waiting times are balanced in order to ease the flow (Kosonen & Bargiela, 1999) , (Galton & Worboys,2005)
    • Using Spatio-Temporal Queries can help to estimate the waiting time at the traffic lights which can be sent to routeing devices to add to the estimated time of journey or to include in shortest time algorithms (Hinz,2007)
    Combining Spatial and Temporal Queries
  • Public Transport handling
    • The study should perform
      • Increase routes to service the whole island
      • Modify routes to cover hot spots of the island (similar to the University terminal)
      • Promote a link between cultural places and public transport for tourists
      • Add ETA service to bus routes
      • Provide an online website with online information on the service
      • Suggest travel trips via the mentioned website
  • Increasing the routes
    • Increasing the routes is an exercise which requires attention on satisfying the needs of the users
    • Studying the usage of the road network, and possible migration back of users to the public transport is a meticulous study (Murray, 2001)
    • A GIS can be used to visually present movement of people which require the need for extra routes
    • Another usage for a GIS is to study the effect of new routes, and how such routes can help in the load balancing. This can be achieved by plotting using a tempo-spatial database the rush hours against the movement of people and to which direction, so as to target such routes (Kieslinger  & Polazzi, 2004), (Tiesyte & Jensen, 2008)
  • Increasing the routes – Cost Effectively
    • Cost-Effective studies need to be performed in order to minimize the total cost objective function . The number of feasible bus routes increases drastically with the increased number of the links (streets), and thus this problem is computationally intractable for realistic urban networks (Chien et al., 2001) .
    • A Genetic Algorithm needs to be used in order to efficiently converge to the optimal solution. This can be validated by applying an exhaustive search algorithm (Peng, 2007)
  • Promoting Cultural Places
    • Setting up a near location routing mechanism for points of interest
    • Offering bus routes to cover such places of interest
    • Allow the searching of a route by the place of interest (Zammit, 2007)
    • Prepare route packages for tourists, (and enhance this service via LBS)
    • Enable the reverse queries such as “Find me the nearest walking distance cultural places to this bus stop” (Tan et al, 2005)
  • Suggesting Travel Places (contd.)
    • A typical query would take this form:
      • User sends message with the current Bus Stop Number (and an optional type of interested places). This c can also be done from a Java application which can be downloaded over WAP / Bluetooth
      • A nearest-neighbour (Li & Brimicombe, 2006) algorithm is run providing walking distance points to that bus stop
      • Once all the points are identified, a Travel Sales Person (Sharma et. al, 2005) algorithm can be used in order to provide a path which covers all such places of interest.
      • Depending on the receiving mobile set:
        • For multimedia mobile sets, images are sent
        • For text based, SMS with guidelines
        • Java App can also be used to download details about the current place and its story via Bluetooth or IrDA
  • Bus ETA
    • This can be achieved by:
      • installing a GPS receiver in each bus
      • the ETA board can be updated every
      • minute by sending the board_id
      • the main server checks the bus routes which are to pass by the mentioned bus stop
      • the actual busses servicing their route are queried and their geolocation is aquired
      • by applying a temporal algorithm such as Gambera et al (2008) , the ETA is worked out
      • the reply can be sent back to the board for display
  • Bus ETA – mobile version
    • The system is very similar to the previous one, with some minor changes to the topology
    • Instead of having the board initiating the query, it is the user which send the SMS (Ching & Carg, 2003)
      • The SMS can be made of several options:
        • Quoting the bus stop number and bus number via a CSV
        • when sending the message (Majzelj, 2006)
        • The transport authority issues an API which software
        • developers can use in their software (Gambera, 2008)
    • The process can continue similar to before, with the exception that the query now takes the form of finding the ETA of the queried bus number (translated into the actual vehicle number) to the bus stop
  • Online Journey Planner
    • This process has to be discussed in many steps
    • Starting off by pointing out the main needs for such an activity:
      • Provides an interface for the users to plan a bus trip
      • Provides an interface which can help the users decide which bus stops to use, and thereafter which is the best route
      • Provides an online interface where the users can view the schedule and the ETA of the next bus servicing the route
  • The system model
    • Road Sensors
    • Road Closure Database
    • Road incident Database
    • Bus Schedule (bus route with vehicle delivering the service)
    ETA Algorithm GIS Server Web User Web Server
  • Requirements
    • Geolocation of each bus stop
    • Having an updated list of matching vehicles to bus routes
    • Sensors on the road network to measure the traffic flow; OR/AND
    • This can be also done by having the GPS devices (on the busses) sending the current location in fixed periods , thus noting the movement done. A-GPS is suggested for such reporting. This technique is discussed in Dueker & Butler (2002)
  • Journey Planning
    • The Public Transport in Malta lacks also the facility to plan a journey. Since most of the routes start / end in the Valletta terminus, this was not much needed, but since this project is proposing the addition of new routes, such a study needs to be made.
    • An algorithm needs to be introduced in order to arrive from point X to point Y using buses in the smallest expected time . Similar proven algorithms are Boyan & Mitzenhamer (2001) and Datar & Ranagade (2000)
    • In order for the above to be usable, control should be performed by the conductors making sure that the drivers do their utmost to arrive on time, without creating extra stress (Duffy & McGoldrick, 1990)
  • Journey planning (cont.)
    • In order to have a functioning journey planner, a better usage of the Postcode has to be made. Following the introduction of the new postcodes, it is much easier to do geolocation
    • Places of interest need to be geolocated and categorised in order to be made easier to be searched for (especially by tourists)
    • Another effort in helping tourists find such places of interest, geotagging of photographs can also be done. This would allow the tourists who are familiar with places but not their names, search by photograph too (Camilleri & Mangion, 2008)
  • Issuing tickets
    • Another problem identified by the MITC (2008) report is the lack of custom tickets
    • After a journey is planned, the ticket (with the relevant fares) should be made available to be purchased online
      • Ticket can be printed similar to E-Ticket confirmation at the airport, and the conductor just confirms the transaction number with the route
      • Such ticket need not be printed and can be in the form of a magnetic card (similar to Oyster in London)
      • Another system can be similar to what Porter (2008) proposed where the balance can be credited from the mobile SIM Card
  • Receiving the results
    • The results can take different formats, and depending on the usage:
      • Web Based: Graphically showing the route, which bus stops to use, and obviously the time table of the next busses
      • SMS: An SMS with the result of the query on the itinerary to take and the next due bus
      • MMS: The map can be transformed to a JPEG which can be sent to the user over MMS, following a description in text
      • 3G / Edge: Using this service, the route can be made available using WAP. This service can also be used to enhance the service by using the current position of the user as the starting location of the journey if GPS is available on the set.
  • Using the same setup for Taxis
    • In the document published by the Government to promote the use of Taxis, this system can also be used in this scenario.
    • Typical Scenario:
      • Client wants a prompt taxi service
      • Sends a message to the dispatch office, quoting the postcode ( geolocation ) or automatically combining it with GPS from mobile set
      • A nearest-point function (Thirumalaivasan & Guruswamy 2005) is run to indicate the nearest taxi marked as available
      • A notification is displayed at the taxi driver’s device showing the route needed
      • An ETA of the taxi is sent to the customer
      • This service can be further enhanced by making a queue service for the taxis which are in the same location, e.x St. Julian’s Taxi Terminus
  • Monitoring the Taxis
    • Making sure the fares are fairly charged
      • One the main concerns why Maltese do not use Taxis in Malta (MITC, 2008)
      • Having the taxis’ location being recorded, the fares computed from the taxi-meter can be compared to an estimated fare by the authority, thus clients would have the availability to double check
    • Security for the passengers
      • Emergency button which is monitored by ADT, Police (MITC, 2008) : This service can also be enhanced with the ADT being able to monitor using a GPS tracker on each cab
    • Tax Evasion
      • Since all routes will be recorded by the ADT, a very clear picture of the amount of revenue generated can be taken by the authority, which can be compared with the Income Tax / VAT Declarations
  • Studying Pollution
    • One of the main reasons why this research is valid is to reduce pollution on our islands
    • Using a GIS, mapping of air pollution readings can be done in order to identify a high level of pollution areas and also plot such readings against temporal customs (Kim et. al, 2004)
    • By plotting such readings, public transport can be used to ease out on the traffic flow to reduce traffic, or also introducing schemes to ease out such pollution:
      • Pay-for-Pollution (Tac, 2007)
      • Congestion Charges (Prud'homme & J Bocarejo, 2005)
  • Brief ideas to finance the project
    • Location specific advertising
      • For example when a person gets down from a bus stop an advert from a shop nearby is sent
    • Related search advertising
      • If a search is done on nearest points of interest to a bus stop, ideas where to shop / dine are presented to the user
    • Advertising on TVs in Buses
      • Target advertising of shops near the next bus stop on the monitors fixed on the buses
    Imagination is the limiting factor!
  • References
    • Bernhardsen, T. (2002). Geographic Information Systems: An Introduction. Canada: John Wiley and Sons
    • Capella, A., & Bennett, V. (2002). Wherever you are, wherever you go, get the information you want to know. Online, IBM
    • ESRI. (2007). What is GIS? Retrieved September 2008, from gis.com: http://www.gis.com/whatisgis/index.html
    • Schiller, J., & Voissard, A. (2004). Location-Based Services. Morgan Kaufmann Title.
    • Research and Markets. (2006, September). Strategic Analysis of the European Mobile LBS Market.: http://www.researchandmarkets.com/reportinfo.asp?report_id=350479&t=e&cat_id=
    • I Kushchu, H Kuscu, From E-government to M-government: Facing the Inevitable?, Trinity College, Dublin, 2003
    • S. Gang, Transcending e-Government: a Case of Mobile Government in Beijing, the First European Conference on Mobile Government, Brighton, 2005
    • Klimm, Gawrilow, M¨ohring, and Stenzel, Conflict-free Vehicle Routing: Load Balancing and Deadlock Prevention, 2008
    • Gawrilow, Köhler, Möhring and Stenzel, Dynamic Routing of Automated Guided Vehicles in Real-Time, 2007
    • Z Hui-ling, X Jian-min, T Yu, H Yu-cong, S Ji-feng, The research of parking guidance and information system based on dedicated short range communication, Intelligent Transportation Systems, 2003. Proceedings. 2003 IEEE, 2003
    • WT Balke, W Kiessling, C Unbehen, Personalized Services for Mobile Route Planning: A Demonstration, Proceedings Of The International Conference On Data, 2003
    • M Pulis, M Attard, Exploring the shortest route options: Applying Environmental Indicators to Calculating Shortest Route, Proceedings of WICT 08, 2008
    • E Brockfeld, RBarlovic, ASchadschneider, M Schreckenberg, Optimizing traffic lights in a cellular automaton model for city traffic, 2001
    • I Kosonen, A Bargiela, A Distributed Traffic Monitoring and Information System, Journal of Geographic Information and Decision Analysis, 1999
    • A Galton, M Worboys, Processes and Events in Dynamic Geo-Networks, Lecture Notes In Computer Science, Springer, 2005
    • S. Hinz, The role of explicit modeling for inferring traffic activity from remote sensing date, Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International, 2007
    • Murray, Strategic analysis of public transport coverage, Socio-Economic Planning Sciences, Elsevier, 2001
    • D Tiesyte, CS Jensen, Similarity-based prediction of travel times for vehicles travelling on known routes, Proceedings of the 16th ACM SIGSPATIAL International, 2008
  • References
    • S Chien, Z Yang, E Hou , Genetic Algorithm Approach for Transit Route Planning and Design, Journal of Transportation Engineering, 2001
    • S Peng, A New Computational Model for the Design of an Urban Inter-modal Public Transit Network, Computer-Aided Civil and Infrastructure Engineering, 2007
    • R Zammit, 2008
    • E Tan, D Goh, YTheng, S Foo, An analysis of services for the mobile tourist, International Conference On Mobile Technology, Applications, And Systems, 2005
    • Y Li, A Brimicombe, Mobile Space-Time Envelopes for Location-Based Services, Transactions in GIS, 2006
    • O Sharma, D Mioc, F Anton, G Dharmaraj, Traveling Salesperson Approximation Algorithm For Real Road Networks, 2005
    • M Gambera, M Bianconi, M Mauro, R Tola , Method and system for estimating the arrival time of a public transport means at predetermined points of its path, EP1796058, 2008
    • L Ching, H.K.  Garg, Designing SMS applications for public transport service system in Singapore, The 8th International Conference on Communication Systems, 2002
    • K Dueker, A Butler, A geographic information system framework for transportation data sharing, 2000.
    • J Boyan, M Mitzenmacher, Improved results for route planning in stochastic transportation, Proceedings of the twelfth annual ACM-SIAM symposium, 2001
    • CA Duffy, AE McGoldrick, Stress and the bus driver in the UK transport industry, Work and Stress, 1990
    • C Mangion, K Camilleri, An Investigation on Server-Side Object-Scene Recognition Performance using Coarse Location Information and Camera Phone-captured Images, WICT08, 2008
    • D Thirumalaivasan, PV Guruswamy, Optimal route analysis using GIS . Retrieved June 23, 2008, from http://www.gisdevelopment.net/application/Utility/transport/utilitytr0004a.htm, 2005
    • J Kim, S Smorodinsky, M Lipsett, B Singer, A Hodgson, B Ostro, Traffic-related Air Pollution Near Busy Roads: The East Bay Children's Respiratory Health Study, 2004
    • TAC Change, EcoTransit Sydney Policy 2007, 2007
    • R Prud'homme, J Bocarejo, The London congestion charge: a tentative economic appraisal,2005
    • MITC, Taxi Report 2008, 2008
    • C Porter, Securing Federated IDm in Mobile Environments (SFIMME), 2008
    • S K. Sharma, J N.D. Gupta, Web services architecture for m-government: issues and challenges, 2003
    • W.-T. Balke, W. Kießling, C. Unbehend, "A Situation-aware Mobile Traffic Information System," Hawaii International Conference on System Sciences , vol. 9, 2003
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