Limitations of Adaptive Control
David Hale
University of Florida
Preview
 Ineffective heuristic methods
 Ineffective at certain congestion levels
 Lack of accountability
 Low market share
 Competing technologies
Heuristic Methods
 Fast, but ineffective
 Equisat (SCATS)
 Greedy algorithm (InSync)
 Hill-climb (TRANSYT)
 Slow, but effective
 Simulated annealing
 Genetic algorithm
 Derivative-free methods
Improvement Percentage (%)
35.0
30.0
25.0
SA
HC
GA (T)
GA (R)
20.0
15.0
10.0
5.0
0.0
0.0
50.0
100.0
Run Time (seconds)
150.0
z
y
C
Optimality
B
x
A
Run Time
Delay
Increased Complexity
Signal Timing
Adapting vs. Optimizing
Non-Adaptive,
Quasi-Adaptive
Quick Optimization
Thorough Optimization
Synchro, T7F,
Vistro
HCS-Streets, T7F,
Vistro, ArteryLite
Fully Adaptive
SCATS, InSync
(none)
Accountability
 Capacity analysis? NO
 Simulation? DIFFICULT
 Most simulation products can’t do it
 VISSIM API = extra $$$
 High level of expertise
 Time-consuming
 Expensive
Market Share
 Decades of availability (1960’s)
 SCATS (1976), SCOOT (1981)
 Fewer than 5% of signals
 Why?
 Costs too high?
 Uncertainty about benefits?
 Lack of accountability?
Competing Technologies
 Data-driven
 Quasi-adaptive
 Stronger algorithms
“automated performance measures
allow agencies to optimize and
manage signals without extensive
field data collection, a central traffic
management or adaptive system, or
a communications infrastructure”
Limitations of Adaptive Control
David Hale
University of Florida