The Elevator ExampleElevator SystemKey Point 6: TransfersKey Point 8: CapacityKey Point 8: Capacity (continued)Key Point 9: SupplyDirect Elevator ServiceAnother Elevator ConfigurationKey Point 11: Infrastructure “Shape”Key Point 14: Cost/Level-of-Service Trade-offsKey Point 15: Demand ConsolidationKey Point 16: “Lumpy” Investment Investments in capacity are often lumpy (e.g., infrastructure). Capacity of Single Key Point 17: Capacity, Cost and Level-of-ServiceOur Next Concept -- Peaking Volume vs. Time of DayKey Point 18: PeakingOur Next ConceptKey Point 19: Volume = (level-of-service); Transportation Demand Transportation Demand: LOS vs. VolumeKey Point 21: Different Time ScalesEquilibrium between Supply and DemandKey Point 22: EquilibriumKey Point 26: StochasticityStochasticity Stochasticity in traffic volume is different than peaking.Measuring Transportation System Performance Performance Measures and CostKey Point 28: Performance MeasuresKey Points -- Summary (1)Key Points -- Summary (2)Key Points -- Summary (3)Key Points -- Summary (4)Key Points -- Summary (5)Key Points -- Summary (6)SPEAKER: Joseph M. SussmanMIT1.201J/11.545J, ESD.210J Introduction to Transportation SystemsFall 2006LECTURES 2, 3, & 4DISPLAYSSeptember 12, 14, & 19, 2006Part IIIThe Elevator Example Elevators are simple compared to some of the more complex transportation systems, but they can be instructive and illustrative.  With this simple example we can gain insight into overall system behavior that we can apply to more complex systems.Elevator SystemFigure 6.1ElevatorsA601B CFigure by MIT OCW.Key Point 6: TransfersIntermodal and intramodal transfers are key determinants of service quality and cost.Transfers between elements of the transportation system are often inefficient. In the elevator example, a transfer from the walk-mode as one comes into the building, to the elevator-mode, implies some waiting and, hence, some inefficiency.Key Point 8: Capacity“Capacity” is a complex, multi-dimensional system characteristic affected by:infrastructurevehiclestechnologylaborinstitutional factorsoperating policyexternal factors (e.g., “clean air”, safety, regulation)Key Point 8: Capacity (continued)In the elevator example,  We could increase the number of elevators. We can also change vehicle technology. For example, we could have larger or faster elevators. We could have capacity improvements as a result of control technologies and smarter algorithms for dispatching.Key Point 9: SupplyLevel-of-service = f (volume); Transportation Supply. As volume approaches capacity, level-of-service deteriorates dramatically -- the “hockey stick” phenomenon.LOS vs. Volume: The Hockey StickFigure 6.3LOSVolumeCapacity"Hockey Stick"Figure by MIT OCW.Direct Elevator ServiceFigure 7.1605958210Figure by MIT OCW.Another Elevator ConfigurationFigure 7.2101 2 3 4 5 62030405060Figure by MIT OCW.What configuration of elevators makes the most sense?What is the basic trade-off here from the viewpoint of the building owner?Key Point 11: Infrastructure “Shape”The “shape” of transportation infrastructure impacts the fabric of “geo-economic” structures.Key Point 14: Cost/Level-of-Service Trade-offsCost/level-of-service trade-offs are a fundamental tension for the transportation provider and for the transportation customer, as well as between them.Key Point 15: Demand ConsolidationConsolidation of like-demands is often used as a cost-minimizing strategy.For example, when an airline runs a hub-and-spoke operation, it is consolidating people from different origins who have common destinations into airplanes to lower costs.Key Point 16: “Lumpy” InvestmentInvestments in capacity are often lumpy (e.g., infrastructure).Capacity of Single vs. Double Track Rail LineFigure 7.7Single Track(Operations in both directions)SidingsDouble TrackWestboundEastboundFigure by MIT OCW.Key Point 17: Capacity, Cost and Level-of-ServiceThe linkages between capacity, cost and level-of-service -- the lumpiness of investment juxtaposed with the “hockey stick” level-of-service function as volume approaches capacity -- is the central challenge of transportation systems design.If we underinvest in capacity, our level-of-service may be uncompetitive. If we overinvest, level-of-service may be fine, but costs will be high and our prices may not be competitive. Making this decision, faced with lumpy investments and the “hockey stick” LOS/volume relation, is difficult indeed. This leads to the central challenge of transportation system design.Our Next Concept -- PeakingVolume vs. Time of DayFigure 8.1VolumeArriving at workPackage pick-upReturn from lunch peakGoing to lunch peakLeaving work7 am 4 pmTime of DayNoonVolume7 am 4 pmTime of DayNoonUp DirectionDown DirectionFigure by MIT OCW.How much capacity should we provide?Different Capacity DecisionsSo what do we do? We cannot choose such a low capacity that customer levels-of-service during peak periods are unacceptable. At the same time, however, we cannot provide a level-of-service such that nobody ever has to wait -- it’s not economical. So, capacity3may be a good compromise. The question of design capacity and how we accommodate temporal peaks in demand is Key Point 18.Figure 8.2Time of DayCapacity1Capacity2= Average demandCapacity3VolumeFigure by MIT OCW.Key Point 18: PeakingTemporal peaking in demand: a fundamental issue is design capacity -- how often do we not satisfy demand?Our Next Concept The volume that a transportation service attracts is a function of the level-of-service provided to customers. If the level-of-service deteriorates, less people will want to use the service.  This is simply a micro-economic concept. For example, if a movie theater doubles its price, therefore making its service less attractive -- in this case, more expensive -- fewer people will go to that movie theater. If a movie theater halves its price, more people will go.Key Point 19: Volume = ƒ(level-of-service); Transportation DemandTransportation Demand: LOS vs. VolumeFigure 8.3VolumeLOSDemandFigure by MIT OCW.Key Point 21: Different Time ScalesDifferent transportation system components and relevant external systems operate and change at different time scales, e.g.,Short run -- operating policy Medium run -- auto ownership Long run -- infrastructure, land use.Equilibrium