Bernhard Friedrich Hanover, May 2001 Strategic Control in Metropolitan Areas Bernhard Friedrich Institute of Transport Engineering and Planning Hanover University Viking Workshop on Traffic Models in the Traffic Management May 8, 2001 Hanover

Bernhard Friedrich Hanover, May traffic information pool, strategy + servive centre level of service improvement of intermodality long term short term optimization of road traffic in networks multimodal multimedia information Traffic control in the context of urban and traffic planning sustainable urban development, new forms of mobility traffic demand transport supply

Bernhard Friedrich Hanover, May Optimization of Road Traffic MOBINET demonstration sites

Bernhard Friedrich Hanover, May Traffic Actuated  Thresholds (logical requirements)  constraints (requirements of time) Basics Data Processing  t < max  t tg+t < max tg tg := tg + t Fixed Time Control  e.g. depending on time of day  e.g. manual selection

Bernhard Friedrich Hanover, May Traffic Actuated  Thresholds (logical requirements)  constraints (requirements of time) Basics Fixed Time Control  e.g. depending on time of day  e.g. manual selection Traffic Adaptive  Traffic Demand and Traffic Flow Modelling, Impact Criteria online  Optimisation Objective Function Data Processing  t < max  t tg+t < max tg tg := tg + t

Bernhard Friedrich Hanover, May Signal Plan Potentials An Example q1 = 700 q2 = 600

Bernhard Friedrich Hanover, May Potentials Saturation and Impacts q1: q2:

Bernhard Friedrich Hanover, May Potentials Saturation and Impacts An Example Saturation Ratio r1 Total Delay W(r1) [Fzh/h] W(1,09) W(1,19)  W = 20,13 [Fzh/h] q1 = 1000 q2 = 700

Bernhard Friedrich Hanover, May State of the Art Requirements for New Concepts Distributed and Modular System Architecture Immediate Reaction to stochastic variations of traffic Using the Knowledge on OD-Streams in the Network Option to Integrate Other Traffic Modes (PT-Priority, Pedestrians)

Bernhard Friedrich Hanover, May Local Controller BALANCE System Architecture Local: Fast Reaction to Stochastic Events

Bernhard Friedrich Hanover, May Area Wide: Adaptation to Changing Demand Network Control BALANCE System Architecture Local: Fast Reaction to Stochastic Events

Bernhard Friedrich Hanover, May Markovian Chains: BALANCE Macroscopic Traffic Model

Bernhard Friedrich Hanover, May BALANCE Macroscopic Traffic Model observed queue lengths calculated queue lengths Markov Model 1

Bernhard Friedrich Hanover, May BALANCE Microscopic Traffic Model

Bernhard Friedrich Hanover, May ) Cliques (offline) BALANCE Building a Frame Signal Plan 2) Stage Scheme and Sequence (offline) 3) Cycle Time 4) Split 5) Offset tu I. II. III. IV. Coordination Fixpoint Stage I I. II. III. IV. I. II. III. IV. 2) Stage Scheme and Sequence (offline) 1) Cliques (offline)

Bernhard Friedrich Hanover, May BALANCE Field Trial  14% Savings in Delay

Bernhard Friedrich Hanover, May BALANCE Adaptive Control in München-Riem

Bernhard Friedrich Hanover, May BALANCE Impact Analysis by Simulation

Bernhard Friedrich Hanover, May Results Average Delay per Vehicle Avg. Delay [s] Fixed Time and Morning peak Evening peak

Bernhard Friedrich Hanover, May MOBINET the middle ring road in Munich control methods 1.ramp metering 2.adaptive signal control (BALANCE) 3.dynamic lane assignment 4.ring info

Bernhard Friedrich Hanover, May Strategic Level / Strategy Centre Active influence on control by the definition of traffic policies through the objective function Tactical level - area 1 Reactive Optimisation according to demand and objective function Tactical level - area n Local level – junction 1 microscopic adaptation to stochastic hours minutes seconds Duration of implementation / reacton time Strategic requirements Network state frame- plans aggregated detection values Local level – junction n Perspectives System Architecture

Bernhard Friedrich Hanover, May Perspectives Munich system architecture

Bernhard Friedrich Hanover, May Perspectives strategic control

Bernhard Friedrich Hanover, May