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A review of current online bicycle routing portals
and their potential role in promoting safer bicycling
Martin Loidl | martin.loidl@sbg.ac.at
Robin Wendel | robin.wendel@sbg.ac.at
Bernhard Zagel | bernhard.zagel@sbg.ac.at
International Cycling Safety Congress
Bologna, Nov. 3rd- 4th 2016
2
safety = f (infrastructure + x)
Photos: M. Loidl (Salzburg)
 Gold standard: separated cycling facilities
 e.g. Pucher & Buehler 2008, Teschke et al. 2012
 But: we don‘t ride in an ideal world
Safety
3
Photo: ECF (Flickr, CC)
Options?
Safety
4
Provide adequate and safe infrastructure 
Equip and train bicyclists 
Provide information about safe routes 
Safety concerns „Ideal world“Information
 Keep people
from riding
 Infrastructure
 Route choice
Effect?
 Debate on role of information in mode choice
 Behaviour change through information? » e.g. Innocenti et al. (2013):
“first choice bias”
 Little research on information and route choice among bicyclists
 Bicycle routing ≠ car routing
Current situation
5
Route choice
criteria
Age
Gender
Trip purpose
Experience
Equipment
Physical condition
Route choice criteria
6
Hochmair (2005)
Broach et al. (2012)
Krenn et al. (2014)
 ± consensus on relevant routing criteria
 Hochmair (2005) applies them to routing information » classes:
Route choice criteria
7
Route optimization
8
 Model-based
 Crash data (prevent roads with more occurrences)
 User feedback
 Pre-route planning apps and mobile navigation devices
 Crowd-sourced data
Current situation
9
Hypothesis:
Safety is hardly ever addressed explicitly in
information/ routing/ navigation applications.
 30 pre-trip route planning web applications
 Freely available, no registration, desktop version
Evaluation
10
Criteria defining “safety” according to
Hochmair (2005) Routing criteria
 Safe Area
 Lighted at Night
 Avoid Busy Intersections
 Bike Lane
 Good Street Condition
 Avoid Public Transport
 No Wrong-Enter of One-Ways
 Avoid Roundabouts
 Distance
 Time
 Gradient
 Pavement
 Road Category
 Safety (+ definition, if available)
 Scenery (+ definition, if available)
 Comfort (+ definition, if available)
 Other
Data
11
Evaluation data are available:
https://gicycle.wordpress.com
 Bicycle routing is not a niche functionality!
 Rich variety of content, functionality, usability
 Major differences between bicycle routing portal and routing portal
with bicycle routing functionality
Results
12
https://www.google.com/maps http://efa.vvs.de/bike
 Most often verbally labeled routing criteria
 Hardly ever with explanation and/or documentation
Results
13
0
1
2
3
4
5
6
7
NumberofRoutingCriteria
Median = 3
 „Safety“ as routing criterion
Results
14
Hochmair (2005)
Routing criteria
 No correlation between routing criteria, data source and
geographical coverage
Results
15
 „Safety“ as relevant topic widely ignored
 Thus, effect of information provision for route choice can not be
assessed
 Implicit consideration of safety aspects
 Bicycle infrastructure
 „Comfortable“ routes
 Complexity of route choice not appropriately reflected
 One-fits-it-all solutions
 Data and technology are not the limiting factors
 Open data, OGD, crowdsourcing initiatives
Discussion
16
Conclusions
17
Winters et al. (2011)
 Safety is critical for mode choice + route choice
 Route choice is complex and individual
 Data and technology allow for adaption, personalization, real-time, …
 Objective and subjective safety threats
 Models, analyses + feedback, crowdsourced data
 Geographical Information Systems (GIS) have the capabilities
to integrated various perspectives and fuel user-tailored
information portals
Conclusions
18
@gicycle_
gicycle.wordpress.com
BROACH, J., DILL, J. & GLIEBE, J. 2012. Where do cyclists ride? A route choice model developed with revealed preference GPS data.
Transportation Research Part A: Policy and Practice, 46, 1730–1740.
HOCHMAIR, H. 2005. Towards a classification of route selection criteria for route planning tools. In: FISHER, P. (ed.) Developments
in Spatial Data Handling. Springer.
INNOCENTI, A., LATTARULO, P. & PAZIENZA, M. G. 2013. Car stickiness: Heuristics and biases in travel choice. Transport Policy, 25,
158-168.
KRENN, P. J., OJA, P. & TITZE, S. 2014. Route choices of transport bicyclists: a comparison of actually used and shortest routes.
International Journal of Behavioral Nutrition and Physical Activity, 11, 1-7.
WINTERS, M., DAVIDSON, G., KAO, D. & TESCHKE, K. 2011. Motivators and deterrents of bicycling: comparing influences on
decisions to ride. Transportation, 38, 153-168.
References
19

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A review of current online bicycle routing portals and their potential role in promoting safer bicycling

  • 1. A review of current online bicycle routing portals and their potential role in promoting safer bicycling Martin Loidl | martin.loidl@sbg.ac.at Robin Wendel | robin.wendel@sbg.ac.at Bernhard Zagel | bernhard.zagel@sbg.ac.at International Cycling Safety Congress Bologna, Nov. 3rd- 4th 2016
  • 2. 2 safety = f (infrastructure + x) Photos: M. Loidl (Salzburg)
  • 3.  Gold standard: separated cycling facilities  e.g. Pucher & Buehler 2008, Teschke et al. 2012  But: we don‘t ride in an ideal world Safety 3 Photo: ECF (Flickr, CC) Options?
  • 4. Safety 4 Provide adequate and safe infrastructure  Equip and train bicyclists  Provide information about safe routes  Safety concerns „Ideal world“Information  Keep people from riding  Infrastructure  Route choice Effect?
  • 5.  Debate on role of information in mode choice  Behaviour change through information? » e.g. Innocenti et al. (2013): “first choice bias”  Little research on information and route choice among bicyclists  Bicycle routing ≠ car routing Current situation 5 Route choice criteria Age Gender Trip purpose Experience Equipment Physical condition
  • 6. Route choice criteria 6 Hochmair (2005) Broach et al. (2012) Krenn et al. (2014)
  • 7.  ± consensus on relevant routing criteria  Hochmair (2005) applies them to routing information » classes: Route choice criteria 7
  • 8. Route optimization 8  Model-based  Crash data (prevent roads with more occurrences)  User feedback
  • 9.  Pre-route planning apps and mobile navigation devices  Crowd-sourced data Current situation 9 Hypothesis: Safety is hardly ever addressed explicitly in information/ routing/ navigation applications.
  • 10.  30 pre-trip route planning web applications  Freely available, no registration, desktop version Evaluation 10 Criteria defining “safety” according to Hochmair (2005) Routing criteria  Safe Area  Lighted at Night  Avoid Busy Intersections  Bike Lane  Good Street Condition  Avoid Public Transport  No Wrong-Enter of One-Ways  Avoid Roundabouts  Distance  Time  Gradient  Pavement  Road Category  Safety (+ definition, if available)  Scenery (+ definition, if available)  Comfort (+ definition, if available)  Other
  • 11. Data 11 Evaluation data are available: https://gicycle.wordpress.com
  • 12.  Bicycle routing is not a niche functionality!  Rich variety of content, functionality, usability  Major differences between bicycle routing portal and routing portal with bicycle routing functionality Results 12 https://www.google.com/maps http://efa.vvs.de/bike
  • 13.  Most often verbally labeled routing criteria  Hardly ever with explanation and/or documentation Results 13 0 1 2 3 4 5 6 7 NumberofRoutingCriteria Median = 3
  • 14.  „Safety“ as routing criterion Results 14 Hochmair (2005) Routing criteria
  • 15.  No correlation between routing criteria, data source and geographical coverage Results 15
  • 16.  „Safety“ as relevant topic widely ignored  Thus, effect of information provision for route choice can not be assessed  Implicit consideration of safety aspects  Bicycle infrastructure  „Comfortable“ routes  Complexity of route choice not appropriately reflected  One-fits-it-all solutions  Data and technology are not the limiting factors  Open data, OGD, crowdsourcing initiatives Discussion 16
  • 18.  Safety is critical for mode choice + route choice  Route choice is complex and individual  Data and technology allow for adaption, personalization, real-time, …  Objective and subjective safety threats  Models, analyses + feedback, crowdsourced data  Geographical Information Systems (GIS) have the capabilities to integrated various perspectives and fuel user-tailored information portals Conclusions 18 @gicycle_ gicycle.wordpress.com
  • 19. BROACH, J., DILL, J. & GLIEBE, J. 2012. Where do cyclists ride? A route choice model developed with revealed preference GPS data. Transportation Research Part A: Policy and Practice, 46, 1730–1740. HOCHMAIR, H. 2005. Towards a classification of route selection criteria for route planning tools. In: FISHER, P. (ed.) Developments in Spatial Data Handling. Springer. INNOCENTI, A., LATTARULO, P. & PAZIENZA, M. G. 2013. Car stickiness: Heuristics and biases in travel choice. Transport Policy, 25, 158-168. KRENN, P. J., OJA, P. & TITZE, S. 2014. Route choices of transport bicyclists: a comparison of actually used and shortest routes. International Journal of Behavioral Nutrition and Physical Activity, 11, 1-7. WINTERS, M., DAVIDSON, G., KAO, D. & TESCHKE, K. 2011. Motivators and deterrents of bicycling: comparing influences on decisions to ride. Transportation, 38, 153-168. References 19