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Junction Modelling in a Strategic Transport Model Wee Liang Lim Henry Le Land Transport Authority, Singapore.

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Presentation on theme: "Junction Modelling in a Strategic Transport Model Wee Liang Lim Henry Le Land Transport Authority, Singapore."— Presentation transcript:

1 Junction Modelling in a Strategic Transport Model Wee Liang Lim Henry Le Land Transport Authority, Singapore

2 Outline Background Objective Overview of the LTA Strategic Transport Model Review of iterative junction modelling Revised junction modelling Comparison of performance results Conclusions

3 Background Singapore A city state 648 km 2 area ; 4.1 mil population. 109 km rail lines (MRT/LRT), 150 km expressways 575 km major arterial roads, 1500 signalised junctions EMME/2 Strategic Transport Model Used widely to forecast travel demand for planning & design of transport proposals, also calculate user benefits Enhanced over the years Incorporated “iterative” junction modelling in 2000 Recently revised junction modelling

4 Objective To present a review of the iterative approach in junction modelling and its limitations. To present a revised & simpler approach in junction modelling and its improvements in model convergence

5 Trip Generation Trip Distribution Mode Split Peak Hour Factors Trip Assignment Model Inputs Model Outputs Model Step iteration HBW (car, m/c, taxi, LRT, MRT, bus, c/o bus) HBS (car, LRT, MRT, bus, school bus) HBB, HBL, NHB Daily OD matrices by mode and trip purpose - travel times - highway volumes - transit volumes - other performance measures for downstream analysis (e.g. financial, economic analysis) Model outputs - car, m/c, taxi - LRT/MRT - c/o bus, school bus - bus Peak hour matrices, AM, PM & OP by mode HBW (highway, transit) HBS, HBB, HBL, NHB Trip distribution matrices by trip purpose and main mode HBW, HBS, HBB HBL, NHB Daily trip ends by purpose OVERVIEW OF LTA STRATEGIC TRANSPORT MODEL - Planning Data: population, employment, school enrolment. - Car ownership, - Dwelling types & others Land use data Trip rate data From assignments - Car, m/c, Taxi - LRT/MRT/Bus Skims of time and cost From HIS and traffic count data Peak hour factors by trip purpose, mode and area - tourist trips, airport trips - goods vehicle trips Special trip matrices - links, junctions - travel time, delay functions - transit services Network From HIS and SP survey Mode split parameters Trip distribution functions HIS data

6 Junction Modelling - Iterative Approach Review Standard Calculate link delay Assign Traffic Start Check Convergence No END Yes Calculate link delay Calculate Junction delay Calculate movement capacity & effective green time Iterative Approach Run assignment for N iterations Start Check Convergence No END Yes Assignment Procedure

7 Iterative Approach Review Turn penalty (delay) function (tpf): User defined turn data –UP1: 6 digits to store 1:No. of lanes 2: No. of short lanes 3:Shared lane description 4: Signal control or not 5:Opposed information6: unused –UP2: unopposed green time & opposed green time –UP3: cycle time Extra user turn data: effective green time & capacity Junction Coding

8 Iterative Approach Review Delay function was based on SIDRA Formulae Delay = uniform delay + Overflow delay Function of cycle time, green split, arrival flow and movement capacity Delay Function for Signalised Movement D(delay) = c/2*(1-u) 2 /(1-u*x) + 900*(x-1 + Sqr((x-1) 2 + 4x/C))

9 Iterative Approach Review Unopposed Movement –Capacity = Saturation flow*green time/cycle time Opposed Movement: –Opposing movement & flow –Effective saturation flow –Effective capacity for opposed movement Movement in a shared lane: –Capacity is proportioned to the ratio of its flow over total lane flow. Movement Capacity

10 Assignment & convergence instability. Factors identified: (i) Steep junction delay curve (ii) Iterative calculation of movement capacity Iterative Approach Review Limitation s 1st Iteration 3rd Iteration 2nd Iteration 4th Iteration

11 REVISED JUNCTION MODELLING

12 Revised Approach To represent realistically the junction delay in a strategic network To improve model convergence and therefore assignment stability and accuracy Objectives

13 Junction Modelling - Revised Approach Assignment Procedure Calculate link delay Calculate Junction delay Calculate movement capacity & effective green time Iterative Approach Assign Traffic Start Check Convergence No END Yes Calculate link delay Calculate Junction delay Calculate movement capacity & effective green time Revised Approach Assign Traffic Start Check Convergence No END Yes

14 Revised Approach To reduce the steep gradient of the iterative delay curve Revised Delay Function Delay = {0.25 + 0.25 (V/C)}*{c-g} for V/C <1 {0.5 + 1.5 (V/C-1)}*{c-g} 1 < V/C < 2 {2 + 2 (V/C - 2)}* {c-g}2 < V/C Source: V/C < 1: uniform delay V/C > 1: calibration of the base model

15 Revised Approach Different base saturation flow (veh/hour) Left ThroughRight 17001960 1800 Simplified calculation for shared lane movements Saturation flow = base saturation flow/no. movements Added calculation for short Lane Saturation flow = storage length/(vehicle space* mov. green time) (Capacity  400 veh/hr) Simplified calculation for opposed movement Saturation flow = base saturation flow/3 (Capacity  200 veh/hr) Revised & Improved Calculation of Movement Capacity

16 COMPARISON OF PERFORMANCE RESULTS

17 Comparison of movement delays Left Movement Iterative: Ave 16.8 sec Revised: Ave 22.2 sec 32% increase

18 Iterative: Ave 30.0 sec Revised: Ave 27.0 sec 10% reduction Through Movement Comparison of movement delays

19 Iterative: Ave 38.4 sec Revised: Ave 43.2 sec 12.5 % Increase Right Movement Comparison of movement delays

20 Comparison of network travel time 1999 Network - AM peak Observations: Junction delay increased despite delay curve smoothened Link travel time reduction => more efficient route choice, more converged assignment

21 Comparison between modelled and observed traffic volumes

22 Comparison between modelled and observed travel time

23 Improvement in model convergence Comparison of model running time on the 2015 network The revised approach has improved model convergence through reducing number of iterations & running time. Note: (38) number of iterations per highway assignment

24 Conclusion Junction delay is a major contributor to a journey time in an urban network. Full incorporation of SIDRA to a strategic transport model may not suitable. Revised and simpler approach to calculation of junction delay was presented The revised model represents realistic movement delays, travel times and traffic demand in a network. Model converges faster and predicts stable travel time & saving for transport schemes.


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