SATURN and DIADEM Practical Experience Toni Dichev

1. SATURN and DIADEMPractical ExperienceToni Dichev 31st Oct 2008

2. Overview • What is DIADEM? • DIADEM Approach • Model Requirements • Realism Tests / Convergence Criteria • Issues & Solutions • Practical Example • Summary: Lessons Learned & Conclusions

3. DIADEM and Variable Demand • Variable Demand Modelling Advice (VADMA) – WebTAG Guidance • Any change to transport conditions will, in principle, cause a change in demand. The purpose of variable demand modelling is to predict and quantify these changes • Trip Frequency • Trip Distribution • Mode Choice • Time of Day Choice • DIADEM (Dynamic Integrated Assignment, and Demand Modelling) software - allows you to implement variable demand modelling as recommended by WebTAG

4. Demand Modelling Using DIADEM Specify Demand Model Structure Select Model Parameters and Realism Test Prepare Forecast Networks and Reference Trip Matrices for Demand Model Assignments Run DIADEM for different Time Periods Identify Best Iteration & Reassign networks with best matrices

5. DIADEM Demand Model Structure Model needs to have appropriate split by journey purpose Which Responses to Include? Circumstances and Policy interests of assessment; Availability of Data; Dft Guidance what responses to consider

6. Realism Tests - The Essentials Base Year Validated Network Base Validated Matrix Base Year Revised Network Base Year Assigned Model Demand Segments DIADEM RUN Select/Tweak Sensitivity (Lambda) Parameters Calculate Elasticities Fuel Price Journey Time Experience from Past Studies Judgement (subjective) Take advise from the expert Contact the supplier Realistic? – Is it in accordance with general experience? Reasonable?- a subjective judgement with which you can “convince” others Ask Questions Realistic? Reasonable? No Yes Select Parameters

7. Problems Running times – can be extensive High number of computers (one for each time period/year/scenario) Difficult to reach convergence specifically for future years – unacceptable Gap values (0.2% recommended - new Guidance 0.15%) Mode Choice modelling (can’t cope with the nested Mode Choice, doesn’t pass the changes in speeds etc. to PT)

8. Help with SATURN Convergence Importance of well converged SATURN assignment (Delta <0.1%) MASL,NITA,NITA_M – convergence parameters MONACO = T – reduces problems with blocking back at single lane junctions (right turners) NUC => 50 – improves accuracy (hence instability) of signals Latest versions of SATURN help greatly in achieving convergence

9. Help with DIADEM Convergence Change the assignment method Increase the maximum number of iterations Decrease the stopping values for the gap values Decrease the value of the ‘maximum flow change’ parameter Improve your assignment convergence

10. Help with DIADEM run time Skimming minimum costs within DIADEM (only if SATURN assignment convergence < 0.1%) SAVEIT = F Assignment Method Algorithm 1 tends to converge quicker Use of the best (high spec) machines NITA = 10 MASL = 100 AUTOK = T KOMBI = 0 NITA_M = 5 DIDDLE = T

11. DIADEM – Future Year Assignments The same convergence criteria is required – can be difficult to achieve The same structure of the files as for the Realism Test Can significantly increased the running times due to assignment and DIADEM convergence Best matrices are reassigned to produce the final assignment

12. Example – Strategic Motorway Link SATURN assignment Large model with assignment times > 1.5 hours Six journey purposes AM, IP and PM models Three modelled years and 4 scenarios DIADEM – distribution and frequency responses only considered (no mode choice), WebTAG guidance used for the Lamda Values, Method of Successive Averages

13. Practical Experience

14. Summary Lessons Learned • Aware of the guidance • How to select sensitivity parameters • Convergence Criteria • Running Times

15. SATURN and DIADEMPractical ExperienceToni Dichev 31st Oct 2008