1. CHANGING BEHAVIOURS
THROUGH USER
INTERACTION
PRESENTED BY URIE BEZUIDENHOUT
DA VINCI TRANSPORT PLANNING
UNIVERSITY OF AUCKLAND

2. SO HOW BAD IS
CONGESTION?
It depends on how you
define congestion and
what you compare it to
$1billion per a?
$702.m
$101.m
$77.m
$540
$210
$204
AUCKLAND WELLINGTON CHRISTCHURCH
CONGESTION COST (2004)
Total ($mpa) Person $pa)

3. WHAT CAN WE DO ABOUT IT?
Now
Autonomous vehicles
Medium to Long termShort Term
Medium Term

4. INFLUENCING DRIVER BEHAVIOUR
Now
Short Term

5. TRAJECTORY PLOTS

6. FLUSHING OUT QUEUES
Queued @ Red
Queued
Platoon
Detector Zone
Free flow
Platoon

7. 0
1
2
3
4
5
6
7
8
9
10
11
S1 S2 S3 S4 S5 S6 S7 S8 S9 S10 S11 S13 S14 S15 S16 S17 S18 S19 S20 S21 S22 S23 S24 S25 S26 S27
Q-LENGTH(VEH)
CYCLE REFERENCE
NEW Q-Predict Model Accuracy

8. RESEARCH CASE STUDY – Auckland CBD

9. EXPERIMENTAL EVIDENCE
Sense
traffic
Optimise
signals
Drivers
divert
Route
flow
changes
Signal
timing
changes

10. OBJECTIVES
• Quantify theoretical maximum efficiency
• Signals can estimate queue
• Optimise OFFSET on cycle-by-cycle – queue minimisation
• Only selected corridors optimised
• Apply MUSIC - OPERA algorithm
• Drivers alter routes in response to signal changes

11. RESULTS – NETWORK WIDE
Short term (Medium term)
• Cyclical queues - 8% (-28%)
• Overcapacity queues - 4% (-31%)
• Stop-start queues - 39% (-59%)
• Travel time reduction - 5% (-20%)

12. OPERA OPTIMISING BENEFITS
-25 % travel
time
$ 400
Savings/person/year
$0.25 billion /year
Travel time savings for
Auckland
500,000
trips in peak hr
11 min
trip in peak hr

13. • Competing signage
• Short block lengths
• Visually complex
• Queues
• Pedestrians and cyclists
DRIVER BEHAVIOUR
13

14. DRIVER WORKLOAD
14

15. TASK ANALYSIS - INTERSECTIONS
15

16. FIXATION

17. GAZE HEATMAP

18. DYNAMIC HAZARDS

19. DYNAMIC HAZARDS

20. CALIBRATING DRIVERS
• Use queues to discourage movements
• Flush out queues before arrival
• Greenwave along alternative route
• 4 - 6 weeks to get measurable benefits