The Economic Principles in Transportation Planning

Transcription

1 2016 Fall Semester Weekly Seminar The Economic Principles in Transportation Planning GUANGCHUAN YANG B.Eng., M.Sc. in Transportation Engineering and Planning October 20, 2016 Center for Advanced Transportation Education and Research (CATER) University of Nevada, Reno Reno, NV

2 Contents Demand Supply Curve Commute Paradox Bus Lane Issue 2

3 Traffic Congestion 3

4 A Simple Question If urban road capacity is increased, does this result in some improvement in traffic speeds, or does it make congestion worse? 4

5 The I-10 Story In , I-10 from the Phoenix airport to Queen Creek in Arizona 5

6 Reopen with Six Lanes 6

7 Six Months Later Congestion returned with a vengeance 7

8 Why 8

9 The Law of Demand Transportation can be viewed as a normal consumer good For example, the demand for car trips: Goes up (down) when the real price of car travel falls (increases) Goes up (down) when the real price of substitutes (e.g. bus travel) increases (falls) Goes up (down) when real income increases (falls) 9

10 The Law of Supply If the price of transport increases (decreases), supply of transport will increase (decrease) If input prices increase (decrease), the supply of transport will decrease (increase) Technological advances and government support may be expected to increase supply 10

11 Price Price Demand Supply Curves Change of Supply Change of Demand S 1 S 2 S E 1 E 2 P 1 P 2 P 2 E 2 P 1 E 1 D 2 D D 1 Q 1 Q 2 Quantity Q 1 Q 2 Quantity 11

12 Braess Paradox Dietrich Braess ( ), German Mathematician Adding extra capacity to a network, when the moving entities selfishly choose their route, can in some cases reduce overall performance. A rational driver would switch from a longer route to a shorter route 12

13 Numerical Example t=v/100 Origin Destination V = 4000 t=v/100 T OAD = V A T OBD = 45 + V B 100 T OAD = T OBD, and V A +V B = 4000 V A = V B = 2000 T OAD = T OBD = = 65 13

14 Numerical Example t=v/100 Origin t 0 Destination t=v/100 T OAD = V A T OABD = V A V B 100 T OBD = 45 + V B 100 MAX (T OA ) = = 40 < T OB MAX (T ABD ) = = 40 < T AD Shortest Route: T OABD = = 80 T OAD = T OBD = = 85 14

15 Downs-Thomson Paradox Anthony Downs & J. M. Thomson An increase in road capacities, by causing shifts from public transit to private transport, could lead to a new traffic equilibrium where total transport costs are higher. 15

16 Mogridge Conjecture Martin J. H. Mogridge ( ), U.K. Transportation Analyst A decrease in road capacities, or better, an increase in mass transit capacity, could shift car users to buses and can therefore decrease total travel times. Fundamental of London Congestion Charging and Bus Priority projects 16

17 Installation of Bus Lane What Will Happen After Converting A General Lane to A Bus Lane? Zuo, Z., G. Yang, C. Shao. Modal Shift of Car Travellers to Buses based on Bus Priority. Proceedings of the 91 st Annual Meeting of Transportation Research Board, Washington D. C., Yang, G. Estimation of Modal Shifts from Car Users to Buses based on Bus Priority. M.Sc. Thesis, University of Southampton, U.K.,

18 Bus Lane Planning Issues What is the optimal bus share ratio to maximize system performance? Traffic volume threshold for converting a general lane to a bus lane. 18

19 Description of Dynamic Equilibrium a. Convert a general lane to a bus lane b. Traffic flow condition after modal shift of car travelers to buses c. Equilibrium traffic flow 19

20 Ideal Bus Share Ratio 20

21 Modeling Modal Shifts Cost of car per trip P 0 P 1 Cost Reduction Supply curve for bus E 1 E 0 Capacity Reduction Supply curve for car Cost of bus per trip Modal Shifts Car trips Q 1 Q 0 Bus trips Total demands Q 21

22 Utility Function Utility: the degree of satisfaction that an individual derive from his available mode choices. Generalized costs of its attributes, usually as a linear weighted sum of all the attributes, such as: U car = a 11 Time car + a 12 Cost car U bus = a 21 IVT bus + a 22 Cost bus + a 23 Access bus + a 24 Wait bus + a 25 Interchange bus 22

23 Bi-Logit Mode Choice Model P n = expu n n M expu m P car = exp U car exp U car+exp U bus P n is the probability of choosing mode n; U n is the utility function of mode n; U m is the utility function of any mode m in the choice set; M is the total number of available alternative modes. P bus = 1 P car Coefficients Attibutes A person Mode Choice Probability by car Probability by bus 23

24 Solution to Bus Lane System Equilibrium John G. Wardrop ( ), U.K. Transportation Analyst User Equilibrium Principle: The journey times in all routes actually used are equal and less than those which would be experienced by a single vehicle on any unused route. System Optimal Principle: At equilibrium the average journey time is minimum. This implies that each user behaves cooperatively in choosing his own route to ensure the most efficient use of the whole system. 24

25 A Bi-Level Programming Problem START Initial modal split without bus priority Implementation of bus priorities: how they impact travel costs Lower level (User equilibrium principle) New modal split with bus priority END Is travel costs of two links reach equilibrium Yes Identify the modal shift extent and optimal bus share No Assume a bus share Upper level (System optimal principle) Choose another feasible answer Calculate the total travel time of roadway system No Is this answer minimizes the total travel time? Yes Identify the optimal bus share END 25

26 Results 26

27 The Vicious Circle Traffic Congestion More Private Traffic Road Construction Modal Shifts Demand Management 27

28 Your Choice? 28

29 Summary Adding capacity to a network may stimulate unnecessary travel demands (The laws of demand and supply) The occurrence of commute paradox was mainly attributed to the change of route and/or mode Demand management strategies aim to regulate and adjust traffic market (Nash Equilibrium) 29

30 Downs Law (as An Explanation to I-10 Story ) Anthony Downs (1930 -) U.S. Economist An increase in traffic capacity on commuter expressways in urban areas results in a rise in travel demand that erodes much of the capacity-enhanced traffic improvement. In colloquial terms: If you build them, they will come! 30

31 Acknowledgements The presenter thanks Prof. Zhongyi Zuo of Dalian Jiaotong University for his discussions; Prof. John Preston of University of Southampton and Prof. Shunfeng Song of University of Nevada, Reno for their instructions of transportation economics. 31

32 References - Theories Braess, D., A. Nagurney, and T. Wakolbinger. On a paradox of traffic planning. Transportation Science, Volume 39, 2005, pp Downs, A. The law of peak-hour expressway congestion. Traffic Quarterly, Vol.16(3), 1962, pp Mogridge, M.J.H. Travel in Towns: Jam Yesterday, Jam Today and Jam Tomorrow? The Macmillan Press, London and Basingstoke,1990. Mogridge, M., D. Holden, J. Bird, G. Terzis. The Downs Thomson paradox and the transportation planning process. International Journal of Transportation Economics, Vol.14(3), 1987, pp Mogridge, M.J.H. The self-defeating nature of urban road capacity policy. Transport Policy, 4(1), 1997, pp Wardrop, J. G. Some theoretical aspects of road traffic research. Proceedings of Institution of Civil Engineers, PART II, 1(2), 1952, pp Sheffi, Y. Urban Transportation Networks: Equilibrium Analysis with Mathematical Programming. Prentice-Hall Inc., Englewood Cliffs, NJ, Ben-Akiva, M., S. Lerman. Discrete choice analysis: theory and application to travel demand. MIT Press:Cambridge, MA, Ortuzar, J. de D., Willumsen, L.G. Modelling transport (third edition). John Wiley &Sons Inc., New York,

33 References - Practices Song, S., J. Wang. Theoretical Analysis, Experience Reference and Preliminary Conception of Traffic Congestion Pricing in China. Journal of Chang an University (Social Science Edition), Vol.16(4), 2014, pp (In Chinese) Zuo, Z., G. Yang, C. Shao. Modal shift of car travellers to buses based on bus priority. The 91st Annual Meeting of Transportation Research Board, Washington D. C., Vedagipi, P., V. Arasan. Modelling modal shift due to the enhanced level of bus service. Transport, Vol.24(2), 2009, pp Sheffi, Y. A simple equilibrium analysis of designating a freeway lane to exclusive bus use. Transportation Research Record, No.775,1981, pp Currie, G., M. Sarvi, B. Young. A new approach to evaluating on-road public transport priority projects: balancing the demand for limited road-space. Transportation, Vol.34(4), 2007, pp Huang, H.J. Pricing and logit-based mode choice models of a transit and highway system with elastic demand. European Journal of Operational Research, Vol.140(3), 2002, pp Sun, H., B. Si, J. Wu. Combined model for flow assignment and mode split in twomodes traffic network. Journal of Transportation Systems Engineering and Information Technology, Vol.8(4), 2008, pp

34 Guangchuan Yang UNR CATER 34