SlideShare una empresa de Scribd logo
1 de 33
Descargar para leer sin conexión
Geovelo, a route planner for bicycle




                      Geovelo, a route planner for bicycle

                         G. Sauvanet, E. Neron, H. Baptiste
                                          ´
                                      Laboratoire d’Informatique
                                  Universit´ Francois Rabelais Tours
                                           e
                              Polytech’Tours - D´partement Informatique
                                                e
                                       64, Avenue Jean Portalis
                                             37200 Tours
                                               FRANCE


                                          11 juillet 2010




G. Sauvanet, E. N´ron, H. Baptiste
                 e                                  SotM 2010 - Girona                      1
Geovelo, a route planner for bicycle
 Outline


      1   Presentation


      2   The Bi-Objective Shortest Path problem
            Modeling a road network
            Mono-objective problem
            Bi-objective problem


      3   Conclusion




G. Sauvanet, E. N´ron, H. Baptiste
                 e                      SotM 2010 - Girona                      2
Geovelo, a route planner for bicycle
 Presentation

      Context
          PhD CIFRE LI/Association           Autour du Train       (March 2008)
                Autour du Train      : promoting alternative modes of travel
             like bicycle
             Today : no route planner really adapted to the bicycle in
             France

      Geovelo
          available on 3 cities (Paris, Nantes, Tours)
             Database : Postgresql/Postgis, OSM Data, Osmosis
             Website : Cloudmade maps, Openlayers
             Multi-objective routing engine

G. Sauvanet, E. N´ron, H. Baptiste
                 e                            SotM 2010 - Girona                      3
Geovelo, a route planner for bicycle
 Presentation




G. Sauvanet, E. N´ron, H. Baptiste
                 e                   SotM 2010 - Girona                      4
Geovelo, a route planner for bicycle
 Presentation




G. Sauvanet, E. N´ron, H. Baptiste
                 e                   SotM 2010 - Girona                      4
Geovelo, a route planner for bicycle
 Outline


      1   Presentation


      2   The Bi-Objective Shortest Path problem
            Modeling a road network
            Mono-objective problem
            Bi-objective problem


      3   Conclusion




G. Sauvanet, E. N´ron, H. Baptiste
                 e                      SotM 2010 - Girona                      5
Geovelo, a route planner for bicycle
 Modeling a road network


                                                   Let G = (V , A) be a
                                                   graph with :
                                                          V the set of
                                                          nodes,
                                                          A the set of arcs,
                                                          the cost function
                                                          distance : A →
                                                          R+
                                                          insecurity : A →
                                                          R+



G. Sauvanet, E. N´ron, H. Baptiste
                 e                   SotM 2010 - Girona                        6
Geovelo, a route planner for bicycle
 Modeling a road network


                                                   Let G = (V , A) be a
                                                   graph with :
                                                          V the set of
                                                          nodes,
                                                          A the set of arcs,
                                                          the cost function
                                                          distance : A →
                                                          R+
                                                          insecurity : A →
                                                          R+



G. Sauvanet, E. N´ron, H. Baptiste
                 e                   SotM 2010 - Girona                        6
Geovelo, a route planner for bicycle
 Modeling a road network


                                                   Let G = (V , A) be a
                                                   graph with :
                                                          V the set of
                                                          nodes,
                                                          A the set of arcs,
                                                          the cost function
                                                          distance : A →
                                                          R+
                                                          insecurity : A →
                                                          R+



G. Sauvanet, E. N´ron, H. Baptiste
                 e                   SotM 2010 - Girona                        6
Geovelo, a route planner for bicycle
 Modeling a road network


                                                   Let G = (V , A) be a
                                                   graph with :
                                                          V the set of
                                                          nodes,
                                                          A the set of arcs,
                                                          the cost function
                                                          distance : A →
                                                          R+
                                                          insecurity : A →
                                                          R+



G. Sauvanet, E. N´ron, H. Baptiste
                 e                   SotM 2010 - Girona                        6
Geovelo, a route planner for bicycle
 Modeling a road network


                                                   Let G = (V , A) be a
                                                   graph with :
                                                          V the set of
                                                          nodes,
                                                          A the set of arcs,
                                                          the cost function
                                                          distance : A →
                                                          R+
                                                          insecurity : A →
                                                          R+



G. Sauvanet, E. N´ron, H. Baptiste
                 e                   SotM 2010 - Girona                        6
Geovelo, a route planner for bicycle
 Presentation of the mono-objective problem

      Mono-objective problem
      Let us define :
             a graph G ,
             a start node s and a target node t.




G. Sauvanet, E. N´ron, H. Baptiste
                 e                         SotM 2010 - Girona                      7
Geovelo, a route planner for bicycle
 Presentation of the mono-objective problem

      Mono-objective problem
      Let us define :
             a graph G ,
             a start node s and a target node t.
      Goal :
             compute shortest path p linking s to t ie
             min a∈p distance(a)




G. Sauvanet, E. N´ron, H. Baptiste
                 e                         SotM 2010 - Girona                      7
Geovelo, a route planner for bicycle
 Presentation of the mono-objective problem

      Mono-objective problem
      Let us define :
             a graph G ,
             a start node s and a target node t.
      Goal :
             compute shortest path p linking s to t ie
             min a∈p distance(a)
      Experiments on a graph with 136 199 nodes and 345 267 arcs :
             Dijkstra algorithm
             average of 0.1 seconde on 100 routes.


G. Sauvanet, E. N´ron, H. Baptiste
                 e                         SotM 2010 - Girona                      7
Geovelo, a route planner for bicycle
 Presentation of the bi-objective problem


      Bi-objective problem
           2 objectives : minimize distance and insecurity
                    2 conflicting objectives
                    ⇒ shortest route is often adapted for the car, so it is
                    dangerous for bicycle
             Insecurity of a path = sum of the insecurity of each arc of the
             path
             Insecurity = distance . insecurity coefficient (inspired from
             dangerous material transportation)
                    insecurity coefficient depends on the nature of an arc : bicycle
                    path, bike lane, no facilities, etc.



G. Sauvanet, E. N´ron, H. Baptiste
                 e                               SotM 2010 - Girona                      8
Geovelo, a route planner for bicycle
 Presentation of the bi-objective problem

      Problem
          Solving bi-objective shortest path problem is hard
             Not an unique path, but a set of efficient paths
             Example on Paris : > 500 efficient paths and computation
             time > 1 minute

      Basic solution
           Transform bi-objective problem in mono-objective problem
             Linear combination of distance and insecurity : new cost(a) =
             α.distance(a) + (1 − α).insecurity (a)
      ⇒ fast and used by many (all ?) route planner, but not really good


G. Sauvanet, E. N´ron, H. Baptiste
                 e                         SotM 2010 - Girona                      9
Geovelo, a route planner for bicycle
 Presentation of the bi-objective problem




G. Sauvanet, E. N´ron, H. Baptiste
                 e                   SotM 2010 - Girona                      10
Geovelo, a route planner for bicycle
 Presentation of the bi-objective problem




G. Sauvanet, E. N´ron, H. Baptiste
                 e                   SotM 2010 - Girona                      10
Geovelo, a route planner for bicycle
 Presentation of the bi-objective problem




G. Sauvanet, E. N´ron, H. Baptiste
                 e                   SotM 2010 - Girona                      11
Geovelo, a route planner for bicycle
 Presentation of the bi-objective problem




G. Sauvanet, E. N´ron, H. Baptiste
                 e                   SotM 2010 - Girona                      12
Geovelo, a route planner for bicycle
 Presentation of the bi-objective problem




G. Sauvanet, E. N´ron, H. Baptiste
                 e                   SotM 2010 - Girona                      13
Geovelo, a route planner for bicycle
 Presentation of the bi-objective problem




G. Sauvanet, E. N´ron, H. Baptiste
                 e                   SotM 2010 - Girona                      14
Geovelo, a route planner for bicycle
 Presentation of the bi-objective problem




G. Sauvanet, E. N´ron, H. Baptiste
                 e                   SotM 2010 - Girona                      15
Geovelo, a route planner for bicycle
 Presentation of the bi-objective problem




G. Sauvanet, E. N´ron, H. Baptiste
                 e                   SotM 2010 - Girona                      16
Geovelo, a route planner for bicycle
 Presentation of the bi-objective problem




      new cost(a) = α1 .distance(a) + (1 − α1 ).insecurity (a)
G. Sauvanet, E. N´ron, H. Baptiste
                 e                        SotM 2010 - Girona                      16
Geovelo, a route planner for bicycle
 Presentation of the bi-objective problem




      new cost(a) = α1 .distance(a) + (1 − α1 ).insecurity (a)
G. Sauvanet, E. N´ron, H. Baptiste
                 e                        SotM 2010 - Girona                      16
Geovelo, a route planner for bicycle
 Presentation of the bi-objective problem




      new cost(a) = α2 .distance(a) + (1 − α2 ).insecurity (a)
G. Sauvanet, E. N´ron, H. Baptiste
                 e                        SotM 2010 - Girona                      16
Geovelo, a route planner for bicycle
 Presentation of the bi-objective problem




      new cost(a) = α2 .distance(a) + (1 − α2 ).insecurity (a)
G. Sauvanet, E. N´ron, H. Baptiste
                 e                        SotM 2010 - Girona                      16
Geovelo, a route planner for bicycle
 Presentation of the bi-objective problem




      new cost(a) = α3 .distance(a) + (1 − α3 ).insecurity (a)
G. Sauvanet, E. N´ron, H. Baptiste
                 e                        SotM 2010 - Girona                      16
Geovelo, a route planner for bicycle
 Presentation of the bi-objective problem




G. Sauvanet, E. N´ron, H. Baptiste
                 e                   SotM 2010 - Girona                      16
Geovelo, a route planner for bicycle
 Research



      Our research
       1 Compute all efficient paths : improvements of labeling

          algorithms for bi-objective problem [ROADEF 2009, MOPGP
          2010]
         2   Compute the best compromise path : [ISCO 2010, JMMA
             2010]




G. Sauvanet, E. N´ron, H. Baptiste
                 e                     SotM 2010 - Girona                      17
Geovelo, a route planner for bicycle
 Outline


      1   Presentation


      2   The Bi-Objective Shortest Path problem
            Modeling a road network
            Mono-objective problem
            Bi-objective problem


      3   Conclusion




G. Sauvanet, E. N´ron, H. Baptiste
                 e                      SotM 2010 - Girona                      18
Geovelo, a route planner for bicycle
 Conclusion


      Conclusion :
             Prototype works (http://www.geovelo.fr).

      Further work :
             user feedback on OSM data
             Test with more objectives (effort, tourist Interest...)
             Mobile version
             Let user set preferences of the routing engine




G. Sauvanet, E. N´ron, H. Baptiste
                 e                          SotM 2010 - Girona                       19

Más contenido relacionado

Último

WomenInAutomation2024: AI and Automation for eveyone
WomenInAutomation2024: AI and Automation for eveyoneWomenInAutomation2024: AI and Automation for eveyone
WomenInAutomation2024: AI and Automation for eveyoneUiPathCommunity
 
Potential of AI (Generative AI) in Business: Learnings and Insights
Potential of AI (Generative AI) in Business: Learnings and InsightsPotential of AI (Generative AI) in Business: Learnings and Insights
Potential of AI (Generative AI) in Business: Learnings and InsightsRavi Sanghani
 
Kuma Meshes Part I - The basics - A tutorial
Kuma Meshes Part I - The basics - A tutorialKuma Meshes Part I - The basics - A tutorial
Kuma Meshes Part I - The basics - A tutorialJoão Esperancinha
 
Generative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfGenerative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfIngrid Airi González
 
Landscape Catalogue 2024 Australia-1.pdf
Landscape Catalogue 2024 Australia-1.pdfLandscape Catalogue 2024 Australia-1.pdf
Landscape Catalogue 2024 Australia-1.pdfAarwolf Industries LLC
 
Glenn Lazarus- Why Your Observability Strategy Needs Security Observability
Glenn Lazarus- Why Your Observability Strategy Needs Security ObservabilityGlenn Lazarus- Why Your Observability Strategy Needs Security Observability
Glenn Lazarus- Why Your Observability Strategy Needs Security Observabilityitnewsafrica
 
So einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdfSo einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdfpanagenda
 
Email Marketing Automation for Bonterra Impact Management (fka Social Solutio...
Email Marketing Automation for Bonterra Impact Management (fka Social Solutio...Email Marketing Automation for Bonterra Impact Management (fka Social Solutio...
Email Marketing Automation for Bonterra Impact Management (fka Social Solutio...Jeffrey Haguewood
 
Arizona Broadband Policy Past, Present, and Future Presentation 3/25/24
Arizona Broadband Policy Past, Present, and Future Presentation 3/25/24Arizona Broadband Policy Past, Present, and Future Presentation 3/25/24
Arizona Broadband Policy Past, Present, and Future Presentation 3/25/24Mark Goldstein
 
Testing tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examplesTesting tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examplesKari Kakkonen
 
Generative AI - Gitex v1Generative AI - Gitex v1.pptx
Generative AI - Gitex v1Generative AI - Gitex v1.pptxGenerative AI - Gitex v1Generative AI - Gitex v1.pptx
Generative AI - Gitex v1Generative AI - Gitex v1.pptxfnnc6jmgwh
 
Infrared simulation and processing on Nvidia platforms
Infrared simulation and processing on Nvidia platformsInfrared simulation and processing on Nvidia platforms
Infrared simulation and processing on Nvidia platformsYoss Cohen
 
JET Technology Labs White Paper for Virtualized Security and Encryption Techn...
JET Technology Labs White Paper for Virtualized Security and Encryption Techn...JET Technology Labs White Paper for Virtualized Security and Encryption Techn...
JET Technology Labs White Paper for Virtualized Security and Encryption Techn...amber724300
 
Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...Farhan Tariq
 
Manual 508 Accessibility Compliance Audit
Manual 508 Accessibility Compliance AuditManual 508 Accessibility Compliance Audit
Manual 508 Accessibility Compliance AuditSkynet Technologies
 
A Glance At The Java Performance Toolbox
A Glance At The Java Performance ToolboxA Glance At The Java Performance Toolbox
A Glance At The Java Performance ToolboxAna-Maria Mihalceanu
 
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyesHow to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyesThousandEyes
 
Long journey of Ruby standard library at RubyConf AU 2024
Long journey of Ruby standard library at RubyConf AU 2024Long journey of Ruby standard library at RubyConf AU 2024
Long journey of Ruby standard library at RubyConf AU 2024Hiroshi SHIBATA
 
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...Wes McKinney
 
UiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to HeroUiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to HeroUiPathCommunity
 

Último (20)

WomenInAutomation2024: AI and Automation for eveyone
WomenInAutomation2024: AI and Automation for eveyoneWomenInAutomation2024: AI and Automation for eveyone
WomenInAutomation2024: AI and Automation for eveyone
 
Potential of AI (Generative AI) in Business: Learnings and Insights
Potential of AI (Generative AI) in Business: Learnings and InsightsPotential of AI (Generative AI) in Business: Learnings and Insights
Potential of AI (Generative AI) in Business: Learnings and Insights
 
Kuma Meshes Part I - The basics - A tutorial
Kuma Meshes Part I - The basics - A tutorialKuma Meshes Part I - The basics - A tutorial
Kuma Meshes Part I - The basics - A tutorial
 
Generative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdfGenerative Artificial Intelligence: How generative AI works.pdf
Generative Artificial Intelligence: How generative AI works.pdf
 
Landscape Catalogue 2024 Australia-1.pdf
Landscape Catalogue 2024 Australia-1.pdfLandscape Catalogue 2024 Australia-1.pdf
Landscape Catalogue 2024 Australia-1.pdf
 
Glenn Lazarus- Why Your Observability Strategy Needs Security Observability
Glenn Lazarus- Why Your Observability Strategy Needs Security ObservabilityGlenn Lazarus- Why Your Observability Strategy Needs Security Observability
Glenn Lazarus- Why Your Observability Strategy Needs Security Observability
 
So einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdfSo einfach geht modernes Roaming fuer Notes und Nomad.pdf
So einfach geht modernes Roaming fuer Notes und Nomad.pdf
 
Email Marketing Automation for Bonterra Impact Management (fka Social Solutio...
Email Marketing Automation for Bonterra Impact Management (fka Social Solutio...Email Marketing Automation for Bonterra Impact Management (fka Social Solutio...
Email Marketing Automation for Bonterra Impact Management (fka Social Solutio...
 
Arizona Broadband Policy Past, Present, and Future Presentation 3/25/24
Arizona Broadband Policy Past, Present, and Future Presentation 3/25/24Arizona Broadband Policy Past, Present, and Future Presentation 3/25/24
Arizona Broadband Policy Past, Present, and Future Presentation 3/25/24
 
Testing tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examplesTesting tools and AI - ideas what to try with some tool examples
Testing tools and AI - ideas what to try with some tool examples
 
Generative AI - Gitex v1Generative AI - Gitex v1.pptx
Generative AI - Gitex v1Generative AI - Gitex v1.pptxGenerative AI - Gitex v1Generative AI - Gitex v1.pptx
Generative AI - Gitex v1Generative AI - Gitex v1.pptx
 
Infrared simulation and processing on Nvidia platforms
Infrared simulation and processing on Nvidia platformsInfrared simulation and processing on Nvidia platforms
Infrared simulation and processing on Nvidia platforms
 
JET Technology Labs White Paper for Virtualized Security and Encryption Techn...
JET Technology Labs White Paper for Virtualized Security and Encryption Techn...JET Technology Labs White Paper for Virtualized Security and Encryption Techn...
JET Technology Labs White Paper for Virtualized Security and Encryption Techn...
 
Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...Genislab builds better products and faster go-to-market with Lean project man...
Genislab builds better products and faster go-to-market with Lean project man...
 
Manual 508 Accessibility Compliance Audit
Manual 508 Accessibility Compliance AuditManual 508 Accessibility Compliance Audit
Manual 508 Accessibility Compliance Audit
 
A Glance At The Java Performance Toolbox
A Glance At The Java Performance ToolboxA Glance At The Java Performance Toolbox
A Glance At The Java Performance Toolbox
 
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyesHow to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
How to Effectively Monitor SD-WAN and SASE Environments with ThousandEyes
 
Long journey of Ruby standard library at RubyConf AU 2024
Long journey of Ruby standard library at RubyConf AU 2024Long journey of Ruby standard library at RubyConf AU 2024
Long journey of Ruby standard library at RubyConf AU 2024
 
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
The Future Roadmap for the Composable Data Stack - Wes McKinney - Data Counci...
 
UiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to HeroUiPath Community: Communication Mining from Zero to Hero
UiPath Community: Communication Mining from Zero to Hero
 

[SOTM10] Geovelo, a route planner for bicycle

  • 1. Geovelo, a route planner for bicycle Geovelo, a route planner for bicycle G. Sauvanet, E. Neron, H. Baptiste ´ Laboratoire d’Informatique Universit´ Francois Rabelais Tours e Polytech’Tours - D´partement Informatique e 64, Avenue Jean Portalis 37200 Tours FRANCE 11 juillet 2010 G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 1
  • 2. Geovelo, a route planner for bicycle Outline 1 Presentation 2 The Bi-Objective Shortest Path problem Modeling a road network Mono-objective problem Bi-objective problem 3 Conclusion G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 2
  • 3. Geovelo, a route planner for bicycle Presentation Context PhD CIFRE LI/Association Autour du Train (March 2008) Autour du Train : promoting alternative modes of travel like bicycle Today : no route planner really adapted to the bicycle in France Geovelo available on 3 cities (Paris, Nantes, Tours) Database : Postgresql/Postgis, OSM Data, Osmosis Website : Cloudmade maps, Openlayers Multi-objective routing engine G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 3
  • 4. Geovelo, a route planner for bicycle Presentation G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 4
  • 5. Geovelo, a route planner for bicycle Presentation G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 4
  • 6. Geovelo, a route planner for bicycle Outline 1 Presentation 2 The Bi-Objective Shortest Path problem Modeling a road network Mono-objective problem Bi-objective problem 3 Conclusion G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 5
  • 7. Geovelo, a route planner for bicycle Modeling a road network Let G = (V , A) be a graph with : V the set of nodes, A the set of arcs, the cost function distance : A → R+ insecurity : A → R+ G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 6
  • 8. Geovelo, a route planner for bicycle Modeling a road network Let G = (V , A) be a graph with : V the set of nodes, A the set of arcs, the cost function distance : A → R+ insecurity : A → R+ G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 6
  • 9. Geovelo, a route planner for bicycle Modeling a road network Let G = (V , A) be a graph with : V the set of nodes, A the set of arcs, the cost function distance : A → R+ insecurity : A → R+ G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 6
  • 10. Geovelo, a route planner for bicycle Modeling a road network Let G = (V , A) be a graph with : V the set of nodes, A the set of arcs, the cost function distance : A → R+ insecurity : A → R+ G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 6
  • 11. Geovelo, a route planner for bicycle Modeling a road network Let G = (V , A) be a graph with : V the set of nodes, A the set of arcs, the cost function distance : A → R+ insecurity : A → R+ G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 6
  • 12. Geovelo, a route planner for bicycle Presentation of the mono-objective problem Mono-objective problem Let us define : a graph G , a start node s and a target node t. G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 7
  • 13. Geovelo, a route planner for bicycle Presentation of the mono-objective problem Mono-objective problem Let us define : a graph G , a start node s and a target node t. Goal : compute shortest path p linking s to t ie min a∈p distance(a) G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 7
  • 14. Geovelo, a route planner for bicycle Presentation of the mono-objective problem Mono-objective problem Let us define : a graph G , a start node s and a target node t. Goal : compute shortest path p linking s to t ie min a∈p distance(a) Experiments on a graph with 136 199 nodes and 345 267 arcs : Dijkstra algorithm average of 0.1 seconde on 100 routes. G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 7
  • 15. Geovelo, a route planner for bicycle Presentation of the bi-objective problem Bi-objective problem 2 objectives : minimize distance and insecurity 2 conflicting objectives ⇒ shortest route is often adapted for the car, so it is dangerous for bicycle Insecurity of a path = sum of the insecurity of each arc of the path Insecurity = distance . insecurity coefficient (inspired from dangerous material transportation) insecurity coefficient depends on the nature of an arc : bicycle path, bike lane, no facilities, etc. G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 8
  • 16. Geovelo, a route planner for bicycle Presentation of the bi-objective problem Problem Solving bi-objective shortest path problem is hard Not an unique path, but a set of efficient paths Example on Paris : > 500 efficient paths and computation time > 1 minute Basic solution Transform bi-objective problem in mono-objective problem Linear combination of distance and insecurity : new cost(a) = α.distance(a) + (1 − α).insecurity (a) ⇒ fast and used by many (all ?) route planner, but not really good G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 9
  • 17. Geovelo, a route planner for bicycle Presentation of the bi-objective problem G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 10
  • 18. Geovelo, a route planner for bicycle Presentation of the bi-objective problem G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 10
  • 19. Geovelo, a route planner for bicycle Presentation of the bi-objective problem G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 11
  • 20. Geovelo, a route planner for bicycle Presentation of the bi-objective problem G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 12
  • 21. Geovelo, a route planner for bicycle Presentation of the bi-objective problem G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 13
  • 22. Geovelo, a route planner for bicycle Presentation of the bi-objective problem G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 14
  • 23. Geovelo, a route planner for bicycle Presentation of the bi-objective problem G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 15
  • 24. Geovelo, a route planner for bicycle Presentation of the bi-objective problem G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 16
  • 25. Geovelo, a route planner for bicycle Presentation of the bi-objective problem new cost(a) = α1 .distance(a) + (1 − α1 ).insecurity (a) G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 16
  • 26. Geovelo, a route planner for bicycle Presentation of the bi-objective problem new cost(a) = α1 .distance(a) + (1 − α1 ).insecurity (a) G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 16
  • 27. Geovelo, a route planner for bicycle Presentation of the bi-objective problem new cost(a) = α2 .distance(a) + (1 − α2 ).insecurity (a) G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 16
  • 28. Geovelo, a route planner for bicycle Presentation of the bi-objective problem new cost(a) = α2 .distance(a) + (1 − α2 ).insecurity (a) G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 16
  • 29. Geovelo, a route planner for bicycle Presentation of the bi-objective problem new cost(a) = α3 .distance(a) + (1 − α3 ).insecurity (a) G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 16
  • 30. Geovelo, a route planner for bicycle Presentation of the bi-objective problem G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 16
  • 31. Geovelo, a route planner for bicycle Research Our research 1 Compute all efficient paths : improvements of labeling algorithms for bi-objective problem [ROADEF 2009, MOPGP 2010] 2 Compute the best compromise path : [ISCO 2010, JMMA 2010] G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 17
  • 32. Geovelo, a route planner for bicycle Outline 1 Presentation 2 The Bi-Objective Shortest Path problem Modeling a road network Mono-objective problem Bi-objective problem 3 Conclusion G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 18
  • 33. Geovelo, a route planner for bicycle Conclusion Conclusion : Prototype works (http://www.geovelo.fr). Further work : user feedback on OSM data Test with more objectives (effort, tourist Interest...) Mobile version Let user set preferences of the routing engine G. Sauvanet, E. N´ron, H. Baptiste e SotM 2010 - Girona 19