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Exploring the Shortest Route Options: Applying
Environmental Indicators to Calculating Shortest Route
Matthew Pulis                                Maria Attard                                              Methodology
MSc. Informatics Student                  GIS Laboratory, Geography Division    The study tests different routing algorithms based on changes in:
University of Malta                       University of Malta                      Weather conditions;
                                                                                   Road conditions including:
                                                                                         planned road blocks;
Email: matthew@solutions-lab.net            Email: maria.attard@um.edu.mt                temporary road blocks such as traffic congestion or
                                                                                          accidents.
                                                                                   Vehicle used(engine and type of vehicle);
                                                                                   Road gradient

                                                                                The Dynamic Systems Development Methodology (DSDM) was
                             Objectives                                         applied to this study and MoSCoW (Must Could Should Would)
                                                                                requirements were drawn up in order to prioritise the core
                                                                                requirements
 Enhancing present LBS systems by adding functionalities and
   variables that favour fuel savings as well as shortest route                 Identifying a good quality dataset was a key concern in this study.
                                                                                The dataset needed to feature different gradient type of streets
 Develop a system using Open Source GIS (using the PostGIS and
                                                                                and traffic directions (One-Way and Bi-Directional segments).
   pgRouting extensions)
                                                                                Traffic conditions are affected by weather and network
 The     user    manipulates      the   following    variables:   weather
                                                                                information. The weather website used for this study
   conditions, road network, traffic status, vehicle specification data         (www.wunderground.com) provided an updated RSS feed. The
                                                                                reports from wunderground.com are not very specific, so it is left
   and road gradient to achieve shortest and most fuel efficient route
                                                                                to a randomizing engine to decide the effect on weather over the
                                                                                streets. Such technique was computed following Gera [10].




                                                                                Traffic conditions are affected by weather and
                           Introduction                                         network information. The weather website
                                                                                used for this study (www.wunderground.com)
 Geographic Information Systems (GIS) can be used for different                 provided an updated RSS feed.
 uses, particularly Location Based Services (LBS). This system will be
 operable both of desktop or mobile devices with the latter having a            The reports from wunderground.com are not
 randomised point representing the current location. This concept               very specific, so it is left to a randomizing
 model uses some randomised data providing route planning                       engine to decide the effect on weather over
 dependent on the type of route chosen by the driver, and also taking           the streets. Such technique was computed
 into consideration weather and roads, with live data in order to avoid         following Gera [10].
 blocked roads due to for example an accident or flooding.

 Transport Geographic Information Systems (T-GIS)                              Network information was more difficult to find. A randomizing
 GIS are being applied in many industries mainly but not                       engine was created to simulate traffic block on the roads. For the
 limiting, public safety, resource management, government                      scope of the project, it was decided that a random generating
 roads, road networking and so on. A GIS can be seen as a stack of             function for disabling roads would be needed, producing an XML
 different map layers, be it raster or vector, where each layer is             file. A Sample RSS reader was scripted to extract the random
 geographically aligned to each other [1].                                     generated data. The generated data will have random type of
                                                                               events with a corresponding randomised time factor. This
 The challenges in T-GIS’s are related to Data Management, Data                randomising technique was inspired from Karl et al. [11].
 Manipulation and Data Analysis. Dueker & Butler [2] argue that
 sharing T-GIS data is “both an important issue and a difficult one”. The      After extensive research for the desired data, including gradient
 different applications also affect how streets are broken into logical        and turn restrictions, GRASS data book was used [12]. GRASS
 statements which can be prepared for information extracts. In                 software was used to combine the raster files with the vector files.
 contrast with what Thill [3] claims with regard to the lack of data           This new Shape file was checked for altitude changes, and after
 manipulation required by society, Downey [4] claims that these                successfully exporting the data into a 3-D plane, the Shape File was
 techniques have improved. Similarly by Wootton & Spainhour [5], that          exported to PostGIS using OGR tool. The dataset chosen is made up
 state the recent improvements with regard to data manipulation tools          of sixteen types of road classes, three State road segments, about
 in GIS. One other development has been Open Source GIS.                       two thousand highway segments, another circa twenty five
                                                                               thousand primary road segments and almost ten thousand
 Studies conclude that optimization techniques in solving pickup and           secondary road segments.
 delivery problems are not promising [6]. The main application of these
 techniques is when a route is needed between a source vertex and a            The technique used to enable or disable roads included the
 target one. Thus routing algorithms can be deemed more successful             creation of two columns in the table, one showing attribute access
 when the starting and ending vertices are known prior to the                  for normal vehicles, and one for emergency access. So as to keep
 exercise, rather than trying to minimise paths when visiting vertices         such dynamic data apart from the main spatial data, views were
 [6]. Different studies propose different algorithms to identify a route       used. What is stored actually on the database is the Expiry data of
 starting from a single vertex can reach all the rest of the vertices in the   the ban, which when compared with the current timestamp of the
 network. These are called single-source SPAs or single-source queries         query, if it is earlier, it means the road can be used (having a TRUE
 [7]. A benefit of these queries is that they can be enhanced to allow for     status) else, status will be set to FALSE making it impossible to be
 secondary constraints, such as Boolean weights or differential costs.         called for routing. Thus in the database only the expiry date is
                                                                               stored making it possible to be heavily indexed by using B-Tree
 Lin [8] looked at fuel use by applying the expertise of (taxi) drivers, in    Indexing method. A similar technique was used to display the
 preparing their routes within the city. Many of the routes chosen were        reason, if the segment was banned:
 very similar, given the time of the day. This contrasted with Leshed et
 al. [9] where many of the responses showed that a consideration of            CASE WHEN
 time of day, speed, fuel consumption and congestion.                              streets_proper.unavailable_until    <     'now'∷text∷timestamp                                                                 Conclusion
                                                                               without time zone THEN ''∷text
                                                                               ELSE streets_proper.reason                                              The way the functions proposed in pgRouting have been
                                                                               END AS reason                                                           extended, allows for further development on this area. This can lead
                                                                                                                                                       other project teams, working in the Open Source field to continue
                                                                               The proposed routing function, extends the Shortest_Path_SP()           enhancing this model. Another enhancement seen in this project is the
                                                                               PL/PGsql function in the pgRouting package. This function was           outcome of the fuel consumption technique. This technique, when used
                                                                               modified to accept another parameter. The wrapping function             in a real life situation should minimize consumption. In contrast with
                                                                               makes also possible capturing the source and target                     techniques used earlier on, such as the one used by Ericsson et al [14]
                                                                               edges, something which required two extra SQL calls in the              and by van der Voort et al [15], this technique does not rely on the driver.
                                                                               pgRouting function. Another enhancement provided on this                Whilst keeping a shorter distance helps fuel consumption, efforts done
                                                                               function is the ability to allow the specification of the rule column   by the engine are minimised. Having the network updated with current
                                                                               to use when doing the routing. Wherever possible, the function is       traffic and weather situation, enables the system to provide the user
                                                                               using both spatial and non spatial indexing. For example the “&&”       with a closer picture to reality.
                                                                               notion make use of the GIS index present on the geospatial table.

                                                                               The following flowchart summarises the algorithm used in this
                                                                               methodology. Starting from computing the vehicle to rain level
                                                                               ratio, thus taking into consideration the height of the vehicle from
                                                                               the ground, it progresses to obtain the starting point of the route
                                                                               and the target point. The route is computed by checking that all
                                                                                                                                                                                                              References
                                                                               points which need to be traversed by the vehicle respect the            [1]Lloyd, B., Queen, P. and R., C. The Basics of Geographic Information Systems. University of Minnesota Extension. 1993.
                                                                                                                                                       [2]Dueker, Kenneth and Butler, Allison. A geographic information system framework for transportation data sharing. [book auth.] J C Thill.
                                                                                                                                                       Geographic Information Systems in Transportation Research. I. Tenessee : Pergamon, 2000, 2, pp. 13-36.
                                                                               gradient to vehicle ratio, and also the vehicle to rain level ratio.    [3]Thill, Jean-Claude. Geographic Information Systems for Transportation in Perspective. Geographic Information Systems in Transportation Research.
                                                                                                                                                       I. Buffalo : Pergamon, 2000, pp. 3-13.

                                                                               Such ratio prevents the vehicle traversing road segments which are      [4]Using Geographic Information Systems to Reconceptualize Spatial Relationships and Ecological Context. Downey, Liam. 2, s.l. : University of
                                                                                                                                                       Colorado, September 2006, American Journal of Sociology, Vol. 112, pp. 567-612.
                                                                                                                                                       [5]Examining Deficiencies in Florida Pedestrian Crash Data. Wootton, Isaac A. and Spainhour, Lisa K. s.l. : Transportation Research Board of the
                                                                               blocked due to adverse weather or steep gradient which force the        National Academies, December 13, 2007, Transportation Research Record, Vol. 2002 / 2007, pp. 31-38.
                                                                                                                                                       [6]Solving a Dynamic and Stochastic Vehicle Routing Problem with a Sample Scenario Hedging Heuristic. Mitrović-Minić, S and Laporte, G. 7, s.l. :
                                                                                                                                                       Elsevier, August 2004, Transportation Research Part B: Methodological, Vol. 38, pp. 635-655.
                                                                               driver to use low gears thus consuming more fuel [13]. To provide       [7]Smith, M.J., Goodchild, M.F. and Longley, P.A. Geospatial Analysis - a comprehensive guide. 2. Leicester : Matador, 2008.
                                                                                                                                                       [8]Lin, Feng Tyan. An Experience Based Routing Method. 7th Inter-University Seminar on. s.l. : University of the Philippines, March 1, 2002.

                                                                               only active road segments the WHERE clause is attached a ‘WHERE         [9]In-Car GPS Navigation: Engagement In-Car GPS Navigation: Engagement. Leshed, Gilly, et al. Florence : ACM, 2008. Proceeding of the twenty-sixth
                                                                                                                                                       annual SIGCHI conference on Human factors in computing systems. pp. 1675-1684 . Session : Driving in My Car.
                                                                                                                                                       [10]Gera, (personal communication) Mark Vella. Info about Weather. [E-Mail]. February 11, 2008.
                                                                               status = TRUE’.                                                         [11]Delivery of Real-Time and Predictive Travel Time Information: Experiences from a Melbourne Trial. Karl, C.A., Charles, S and Trayford, R.
                                                                                                                                                       Toronto : s.n., 1999. Proceedings of 6th World Congress on Intelligent Transport Systems.
                                                                                                                                                       [12]Neteler, Markus and Mitasova, Helen. Open Source GIS: A GRASS GIS Approach. NC Original Data Set Sources, Metadata.
                                                                                                                                                       [13]Estimation Model of Vehicle Emission Considering Variation of Running Speed. Oneyama, H, Oguchi, T and Kuwahara, M. 5, 2001, Journal of the
                                                                                                                                                       Eastern Asia Society for Transportation, Vol. 4, pp. 105-117.
                                                                                                                                                       [14]Optimizing route choice for lowest fuel consumption – Potential effects of a new driver support tool. Ericsson, Eva, Larsson, Hanna and
                                                                                                                                                       Brundell-Freij, Karin. 6, Cote : Elsevier, 2006, Transportation research. Part C, Emerging technologies, Vol.14, pp.369-383.
                                                                                                                                                       [15]A prototype fuel-efficiency support tool. van der Voort, M., Dougherty, M.S. and van Maarseveen, M. 4, s.l. : Elsevier, August
                                                                                                                                                       2001, Transportation Research Part C: Emerging Technologies, Vol. 9, pp. 279-296.

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Poster: Exploring the shortest route options: Applying Environmental Indicators to Calculating Shortest Route

  • 1. Exploring the Shortest Route Options: Applying Environmental Indicators to Calculating Shortest Route Matthew Pulis Maria Attard Methodology MSc. Informatics Student GIS Laboratory, Geography Division The study tests different routing algorithms based on changes in: University of Malta University of Malta  Weather conditions;  Road conditions including:  planned road blocks; Email: matthew@solutions-lab.net Email: maria.attard@um.edu.mt  temporary road blocks such as traffic congestion or accidents.  Vehicle used(engine and type of vehicle);  Road gradient The Dynamic Systems Development Methodology (DSDM) was Objectives applied to this study and MoSCoW (Must Could Should Would) requirements were drawn up in order to prioritise the core requirements  Enhancing present LBS systems by adding functionalities and variables that favour fuel savings as well as shortest route Identifying a good quality dataset was a key concern in this study. The dataset needed to feature different gradient type of streets  Develop a system using Open Source GIS (using the PostGIS and and traffic directions (One-Way and Bi-Directional segments). pgRouting extensions) Traffic conditions are affected by weather and network  The user manipulates the following variables: weather information. The weather website used for this study conditions, road network, traffic status, vehicle specification data (www.wunderground.com) provided an updated RSS feed. The reports from wunderground.com are not very specific, so it is left and road gradient to achieve shortest and most fuel efficient route to a randomizing engine to decide the effect on weather over the streets. Such technique was computed following Gera [10]. Traffic conditions are affected by weather and Introduction network information. The weather website used for this study (www.wunderground.com) Geographic Information Systems (GIS) can be used for different provided an updated RSS feed. uses, particularly Location Based Services (LBS). This system will be operable both of desktop or mobile devices with the latter having a The reports from wunderground.com are not randomised point representing the current location. This concept very specific, so it is left to a randomizing model uses some randomised data providing route planning engine to decide the effect on weather over dependent on the type of route chosen by the driver, and also taking the streets. Such technique was computed into consideration weather and roads, with live data in order to avoid following Gera [10]. blocked roads due to for example an accident or flooding. Transport Geographic Information Systems (T-GIS) Network information was more difficult to find. A randomizing GIS are being applied in many industries mainly but not engine was created to simulate traffic block on the roads. For the limiting, public safety, resource management, government scope of the project, it was decided that a random generating roads, road networking and so on. A GIS can be seen as a stack of function for disabling roads would be needed, producing an XML different map layers, be it raster or vector, where each layer is file. A Sample RSS reader was scripted to extract the random geographically aligned to each other [1]. generated data. The generated data will have random type of events with a corresponding randomised time factor. This The challenges in T-GIS’s are related to Data Management, Data randomising technique was inspired from Karl et al. [11]. Manipulation and Data Analysis. Dueker & Butler [2] argue that sharing T-GIS data is “both an important issue and a difficult one”. The After extensive research for the desired data, including gradient different applications also affect how streets are broken into logical and turn restrictions, GRASS data book was used [12]. GRASS statements which can be prepared for information extracts. In software was used to combine the raster files with the vector files. contrast with what Thill [3] claims with regard to the lack of data This new Shape file was checked for altitude changes, and after manipulation required by society, Downey [4] claims that these successfully exporting the data into a 3-D plane, the Shape File was techniques have improved. Similarly by Wootton & Spainhour [5], that exported to PostGIS using OGR tool. The dataset chosen is made up state the recent improvements with regard to data manipulation tools of sixteen types of road classes, three State road segments, about in GIS. One other development has been Open Source GIS. two thousand highway segments, another circa twenty five thousand primary road segments and almost ten thousand Studies conclude that optimization techniques in solving pickup and secondary road segments. delivery problems are not promising [6]. The main application of these techniques is when a route is needed between a source vertex and a The technique used to enable or disable roads included the target one. Thus routing algorithms can be deemed more successful creation of two columns in the table, one showing attribute access when the starting and ending vertices are known prior to the for normal vehicles, and one for emergency access. So as to keep exercise, rather than trying to minimise paths when visiting vertices such dynamic data apart from the main spatial data, views were [6]. Different studies propose different algorithms to identify a route used. What is stored actually on the database is the Expiry data of starting from a single vertex can reach all the rest of the vertices in the the ban, which when compared with the current timestamp of the network. These are called single-source SPAs or single-source queries query, if it is earlier, it means the road can be used (having a TRUE [7]. A benefit of these queries is that they can be enhanced to allow for status) else, status will be set to FALSE making it impossible to be secondary constraints, such as Boolean weights or differential costs. called for routing. Thus in the database only the expiry date is stored making it possible to be heavily indexed by using B-Tree Lin [8] looked at fuel use by applying the expertise of (taxi) drivers, in Indexing method. A similar technique was used to display the preparing their routes within the city. Many of the routes chosen were reason, if the segment was banned: very similar, given the time of the day. This contrasted with Leshed et al. [9] where many of the responses showed that a consideration of CASE WHEN time of day, speed, fuel consumption and congestion. streets_proper.unavailable_until < 'now'∷text∷timestamp Conclusion without time zone THEN ''∷text ELSE streets_proper.reason The way the functions proposed in pgRouting have been END AS reason extended, allows for further development on this area. This can lead other project teams, working in the Open Source field to continue The proposed routing function, extends the Shortest_Path_SP() enhancing this model. Another enhancement seen in this project is the PL/PGsql function in the pgRouting package. This function was outcome of the fuel consumption technique. This technique, when used modified to accept another parameter. The wrapping function in a real life situation should minimize consumption. In contrast with makes also possible capturing the source and target techniques used earlier on, such as the one used by Ericsson et al [14] edges, something which required two extra SQL calls in the and by van der Voort et al [15], this technique does not rely on the driver. pgRouting function. Another enhancement provided on this Whilst keeping a shorter distance helps fuel consumption, efforts done function is the ability to allow the specification of the rule column by the engine are minimised. Having the network updated with current to use when doing the routing. Wherever possible, the function is traffic and weather situation, enables the system to provide the user using both spatial and non spatial indexing. For example the “&&” with a closer picture to reality. notion make use of the GIS index present on the geospatial table. The following flowchart summarises the algorithm used in this methodology. Starting from computing the vehicle to rain level ratio, thus taking into consideration the height of the vehicle from the ground, it progresses to obtain the starting point of the route and the target point. The route is computed by checking that all References points which need to be traversed by the vehicle respect the [1]Lloyd, B., Queen, P. and R., C. The Basics of Geographic Information Systems. University of Minnesota Extension. 1993. [2]Dueker, Kenneth and Butler, Allison. A geographic information system framework for transportation data sharing. [book auth.] J C Thill. Geographic Information Systems in Transportation Research. I. Tenessee : Pergamon, 2000, 2, pp. 13-36. gradient to vehicle ratio, and also the vehicle to rain level ratio. [3]Thill, Jean-Claude. Geographic Information Systems for Transportation in Perspective. Geographic Information Systems in Transportation Research. I. Buffalo : Pergamon, 2000, pp. 3-13. Such ratio prevents the vehicle traversing road segments which are [4]Using Geographic Information Systems to Reconceptualize Spatial Relationships and Ecological Context. Downey, Liam. 2, s.l. : University of Colorado, September 2006, American Journal of Sociology, Vol. 112, pp. 567-612. [5]Examining Deficiencies in Florida Pedestrian Crash Data. Wootton, Isaac A. and Spainhour, Lisa K. s.l. : Transportation Research Board of the blocked due to adverse weather or steep gradient which force the National Academies, December 13, 2007, Transportation Research Record, Vol. 2002 / 2007, pp. 31-38. [6]Solving a Dynamic and Stochastic Vehicle Routing Problem with a Sample Scenario Hedging Heuristic. Mitrović-Minić, S and Laporte, G. 7, s.l. : Elsevier, August 2004, Transportation Research Part B: Methodological, Vol. 38, pp. 635-655. driver to use low gears thus consuming more fuel [13]. To provide [7]Smith, M.J., Goodchild, M.F. and Longley, P.A. Geospatial Analysis - a comprehensive guide. 2. Leicester : Matador, 2008. [8]Lin, Feng Tyan. An Experience Based Routing Method. 7th Inter-University Seminar on. s.l. : University of the Philippines, March 1, 2002. only active road segments the WHERE clause is attached a ‘WHERE [9]In-Car GPS Navigation: Engagement In-Car GPS Navigation: Engagement. Leshed, Gilly, et al. Florence : ACM, 2008. Proceeding of the twenty-sixth annual SIGCHI conference on Human factors in computing systems. pp. 1675-1684 . Session : Driving in My Car. [10]Gera, (personal communication) Mark Vella. Info about Weather. [E-Mail]. February 11, 2008. status = TRUE’. [11]Delivery of Real-Time and Predictive Travel Time Information: Experiences from a Melbourne Trial. Karl, C.A., Charles, S and Trayford, R. Toronto : s.n., 1999. Proceedings of 6th World Congress on Intelligent Transport Systems. [12]Neteler, Markus and Mitasova, Helen. Open Source GIS: A GRASS GIS Approach. NC Original Data Set Sources, Metadata. [13]Estimation Model of Vehicle Emission Considering Variation of Running Speed. Oneyama, H, Oguchi, T and Kuwahara, M. 5, 2001, Journal of the Eastern Asia Society for Transportation, Vol. 4, pp. 105-117. [14]Optimizing route choice for lowest fuel consumption – Potential effects of a new driver support tool. Ericsson, Eva, Larsson, Hanna and Brundell-Freij, Karin. 6, Cote : Elsevier, 2006, Transportation research. Part C, Emerging technologies, Vol.14, pp.369-383. [15]A prototype fuel-efficiency support tool. van der Voort, M., Dougherty, M.S. and van Maarseveen, M. 4, s.l. : Elsevier, August 2001, Transportation Research Part C: Emerging Technologies, Vol. 9, pp. 279-296.