This document evaluates how online bicycle routing portals address safety when providing route recommendations. It reviews 30 pre-trip route planning websites and finds that while most allow users to select routing criteria like distance and time, very few explicitly include safety as a criteria. When safety is included, it is rarely defined or explained. The document concludes that since safety is an important factor in bicyclists' route choices but is largely ignored by current routing tools, more needs to be done to better reflect the complexity of safety considerations and individual preferences in route recommendations.

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
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17. Conclusions
17
Winters et al. (2011)

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
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