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The Impact of Intersection Design on
Pedestrians’ Choice to Cross on Red
Nicolae Duduta, EMBARQ, World Resources Institute (presenter)
Qianqian Zhang, Massachusetts Institute of Technology
Matthew Kroneberger, Metropolitan Washington Council of
Governments
Transportation Research Board Annual Meeting
January 13, 2014
How can crossing on red be
reduced through improved
intersection and signal
design?
Previous studies
• Common variables used (traffic gap, pedestrian delay)
Our approach: building on previous studies and adding
variables related to intersection and signal design
Main findings
Insights for intersection design
Agenda
Existing literature on pedestrian behavior at signalized
intersections
• Traffic conditions (volume, gaps)
• Person characteristics (e.g. mobility restrictions, age)
• Design (waiting time, delay)
Modeling applications predicting pedestrian signal
compliance
• Traffic microsimulation with pedestrian modeling
Previous studies
Building on existing studies, develop a model predicting the
probability of a pedestrian crossing on red
Collected video data of pedestrian behavior at signalized
intersections in Washington DC
Developed a binary logit model predicting the probability of
a pedestrian crossing on red
Methodology
Understand the impact of all these variables:
Traffic gap
Traffic volumes
Waiting time
Pedestrian delay
Crossing distance
Type of signal phase (conflicting movements)
Our approach
Traffic gap: large gaps in traffic
increase the probability of
pedestrians crossing on red
Traffic volumes: Pedestrians
less likely to cross on busier
streets
Waiting time: longer wait times are
strongly correlated with a higher
probability of crossing on red
Pedestrian delay: Function of the
length of the pedestrian green
phase and the signal cycle. HCM
recommends keeping it under 30
seconds.
Crossing distance: Longer
crosswalks should reduce the
probability of crossing on red
Conflicting vehicle movement: Pedestrians are more
likely to wait for cross traffic, and less likely to wait for
other types of conflicts
Results
Coefficient P
Person of restricted mobility (=1 if yes, =0 otherwise) -3.813 0.000
Traffic gap (seconds until next vehicle) 0.037 0.000
Traffic volumes (vehicles / second / lane) -12.525 0.000
Average pedestrian delay (HCM formula, seconds) 0.012 0.023
Conflict with left turns (=1 if true, =0 otherwise) 0.873 0.000
All red (clearance) phase (=1 if yes, =0 otherwise) 1.020 0.001
Crosswalk length (meters) -0.298 0.000
Constant 1.576 0.000
No. of observations 1569
Log likelihood -494.342
LR chi2 (prob > chi2) 294.16 (0.000)
A positive sign indicates a higher probability of crossing on red
Prediction accuracy
0
1
2
3
4
5
6
7
Frequency
Prediction error
Traffic only
0
1
2
3
4
5
6
7
Frequency
Prediction error
Traffic and design
Tested the model’s
predictive accuracy for
specific intersection and
signal configurations
Compared the accuracy
under different
specifications
No benchmark in the
literature, but the accuracy
is comparable to that of
pedestrian route choice
models in transit terminals
Design insights
Pedestrians are more likely to comply with the red signal at an
intersection that features a short signal cycle and a simple signal
configuration
Signal compliance could be improved by:
• Keeping the signal cycle short
• Maximizing the length of the pedestrian green phase
• Avoiding complex signal configurations
Signal compliance and safety
While crossing on red is a risk factor for pedestrians, the relationship
between crossing on red and safety is complex
Pedestrians appear more likely to cross on red at safer locations
(shorter crosswalks, lower traffic volumes)
Thank you
Nicolae Duduta, nduduta@wri.org

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  • 1. The Impact of Intersection Design on Pedestrians’ Choice to Cross on Red Nicolae Duduta, EMBARQ, World Resources Institute (presenter) Qianqian Zhang, Massachusetts Institute of Technology Matthew Kroneberger, Metropolitan Washington Council of Governments Transportation Research Board Annual Meeting January 13, 2014
  • 2. How can crossing on red be reduced through improved intersection and signal design?
  • 3. Previous studies • Common variables used (traffic gap, pedestrian delay) Our approach: building on previous studies and adding variables related to intersection and signal design Main findings Insights for intersection design Agenda
  • 4. Existing literature on pedestrian behavior at signalized intersections • Traffic conditions (volume, gaps) • Person characteristics (e.g. mobility restrictions, age) • Design (waiting time, delay) Modeling applications predicting pedestrian signal compliance • Traffic microsimulation with pedestrian modeling Previous studies
  • 5. Building on existing studies, develop a model predicting the probability of a pedestrian crossing on red Collected video data of pedestrian behavior at signalized intersections in Washington DC Developed a binary logit model predicting the probability of a pedestrian crossing on red Methodology
  • 6. Understand the impact of all these variables: Traffic gap Traffic volumes Waiting time Pedestrian delay Crossing distance Type of signal phase (conflicting movements) Our approach
  • 7. Traffic gap: large gaps in traffic increase the probability of pedestrians crossing on red
  • 8. Traffic volumes: Pedestrians less likely to cross on busier streets
  • 9. Waiting time: longer wait times are strongly correlated with a higher probability of crossing on red
  • 10. Pedestrian delay: Function of the length of the pedestrian green phase and the signal cycle. HCM recommends keeping it under 30 seconds.
  • 11. Crossing distance: Longer crosswalks should reduce the probability of crossing on red
  • 12. Conflicting vehicle movement: Pedestrians are more likely to wait for cross traffic, and less likely to wait for other types of conflicts
  • 13. Results Coefficient P Person of restricted mobility (=1 if yes, =0 otherwise) -3.813 0.000 Traffic gap (seconds until next vehicle) 0.037 0.000 Traffic volumes (vehicles / second / lane) -12.525 0.000 Average pedestrian delay (HCM formula, seconds) 0.012 0.023 Conflict with left turns (=1 if true, =0 otherwise) 0.873 0.000 All red (clearance) phase (=1 if yes, =0 otherwise) 1.020 0.001 Crosswalk length (meters) -0.298 0.000 Constant 1.576 0.000 No. of observations 1569 Log likelihood -494.342 LR chi2 (prob > chi2) 294.16 (0.000) A positive sign indicates a higher probability of crossing on red
  • 14. Prediction accuracy 0 1 2 3 4 5 6 7 Frequency Prediction error Traffic only 0 1 2 3 4 5 6 7 Frequency Prediction error Traffic and design Tested the model’s predictive accuracy for specific intersection and signal configurations Compared the accuracy under different specifications No benchmark in the literature, but the accuracy is comparable to that of pedestrian route choice models in transit terminals
  • 15. Design insights Pedestrians are more likely to comply with the red signal at an intersection that features a short signal cycle and a simple signal configuration Signal compliance could be improved by: • Keeping the signal cycle short • Maximizing the length of the pedestrian green phase • Avoiding complex signal configurations
  • 16. Signal compliance and safety While crossing on red is a risk factor for pedestrians, the relationship between crossing on red and safety is complex Pedestrians appear more likely to cross on red at safer locations (shorter crosswalks, lower traffic volumes)
  • 17. Thank you Nicolae Duduta, nduduta@wri.org