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David Hale (Leidos).  Ineffective heuristic methods  Ineffective at certain congestion levels  Lack of accountability  Low market share  Competing.

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Presentation on theme: "David Hale (Leidos).  Ineffective heuristic methods  Ineffective at certain congestion levels  Lack of accountability  Low market share  Competing."— Presentation transcript:

1 David Hale (Leidos)

2  Ineffective heuristic methods  Ineffective at certain congestion levels  Lack of accountability  Low market share  Competing technologies

3 ASCT’s optimize complex networks in only a few seconds. Is this enough time to produce a good solution? Or, is it only enough time to produce a “quick and dirty” solution? Industrial engineering experts would not be impressed.  Fast Methods (not effective)  “Equisat”  Webster’s method  Greedy algorithm  Hill-climbing  Slow Methods (effective)  Simulated annealing  Evolutionary algorithms  Derivative-free methods

4 y z x Run Time Delay Reduction A B C

5 (none) Non-Adaptive, Quasi-Adaptive Fully Adaptive Quick Optimization Thorough Optimization

6 “If geared toward sporadic demand, they’re effective. In corridors with defined peaks and aggressive timing, they experience diminishing returns.” Delay Degree of Saturation 0.801.00

7 “The industry needs a tool to quantify myriad adaptive products.” “People are implementing these systems without a real analysis.”  Proprietary, secret algorithms  Capacity analysis? NO  Simulation? DIFFICULT  Most products can’t do it  VISSIM API = extra $$$  Too much time, money, expertise

8 “There is just way too much marketing.”  Advertising over science?  Capitalism, good and bad  Cherry-picked case studies  67% said ASCT was good for oversaturated conditions  Law & Order  ITE Community discussion on ASCT  Experts with decades of signal experience  ASCT is just “one tool in the toolbox”  ASCT “has its place”

9 “With less than 5% market share after 5 decades, acceptance is not consistent with successful technologies.” “Adaptive control in its infancy?”  Decades of availability (1960’s)  SCATS (1976), SCOOT (1981)  Fewer than 5% of signals are adaptive  Why?  Costs too high  Uncertainty about benefits

10 “Automated performance measures allow agencies to optimize and manage signals without an adaptive system.”  Data driven  Quasi-adaptive  Stronger algorithms

11 “The industry needs a tool to quantify myriad adaptive products.” “People are implementing these systems without a real analysis.” “If geared toward sporadic demand, they’re effective. In corridors with defined peaks and aggressive timing, they experience diminishing returns.” “We only use them when other options have failed.” “There is just way too much marketing.” “Clearly the jury is out on where they should be deployed.” “From my experience it is smoke and mirrors.” “With less than 5% market share after 5 decades, acceptance is not consistent with successful technologies.” “Automated performance measures allow agencies to optimize and manage signals without an adaptive system.”

12  Traffic too light = not cost effective  Delay not sensitive below 80% saturation  Traffic too heavy = not cost effective  Everything is pre-timed over 120% saturation  No platoon progression  Cycle, offsets, phasing sequence insignificant  Traffic medium = sometimes cost effective  Sporadic demand (movie theater, football stadium)  Unpredictable pedestrian activity  Emergency vehicles  Incidents / accidents

13 David Hale (Leidos)


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