AMPLIFIED WORK PLAN SHRP LO4. Incorporating Reliability Performance Measures in Operations and Planning Modeling Tools. Prepared by Delcan

Transcription

1 AMPLIFIED WORK PLAN SHRP LO4 Incorporating Reliability Performance Measures in Operations and Planning Modeling Tools Prepared by Delcan In Association With PB Americas Inc. Northwestern University Transportation Center February 27 th,

2 1. Introduction This document is an amplified work plan for the SHRP 2 Project L-04 and provides a detailed description of how the research plan will be carried out by the team members. It is organized as follows: Summary of responsibilities key team members Scope of work Schedule and work flow diagram Response to SHRP 2 comments on the proposal in an addendum dated Response to SHRP 2 comments received on the addendum Final Budget 2. Summary of Responsibilities Key Team Members Implementation of the work plan will be managed and directed by the following principals. Jacqueline M. Golob, Delcan Project Manager Yannis C. Stogios, Delcan Co-Principal Investigator Hani Mahmassani, Northwestern University Co-Principal Investigator Peter Vovsha, PB Co-Principal Investigator Figure 1 shows a matrix of responsibilities among the research team, with the role and level of effort for the key members of the team indicated for each task in each of the three phases of research. The second number of hours indicates the supporting staff effort dedicated to those tasks. 2

3 Task 1 Fundamental issues of travel time reliability 2 Functional Requirements 3 Framework for evaluating incidents and events 4 Candidate networks and models Jackie Golob Project Manager Yannis Stogios PI Review / /46 40 Lead 98/211 5 Data 102 Lead 106/246 Hani Mahmassani PI - 2 Review & input 17/102 Lead 52/305 Lead 89/522 19/111 7/40 Peter Vovsha PI - 3 Lead 96/54 18/44 48/112 16/74 16/74 Mark Bradley Research Advisor 48 Review 8 16 Review 8 32 Xuesong Zhou Modeling Expert Ph I report Lead Review & report consolidation 28 & review 40/132 17/102 24/14 Review Development of simulation model 8 Demonstration of travel time reliability application model 168 Lead 132/ /50 9 Guidelines 32 40/44 10 Ph II Lead report Review & 36/106 report consolidation Ph III Incorporating reliability into Travel Models 36 86/61 116/684 Lead 28/164 Lead 31/183 14/81 25/146 64/148 18/44 24/30 24/24 Lead 128/252 Review 16 Review 8 Review 8 Review Figure 1 Responsibilities of Key Task Members Plus Assistants 3

4 3. Scope of Work Objectives of the Research As stated in the RFP: The objectives of this project are to (1) develop the capability of producing measures of reliability performance as output in traffic simulation models and planning models, and (2) determine how travel demand forecasting models can use reliability measures to produce revised estimates of travel patterns. To accomplish these objectives requires the following tasks. Phase I Background, Functional Requirements, Representative Data and Application Guidelines Task 1: Fundamental Issues of travel Time reliability in Modeling Tools As stated in the RFP: Drawing on appropriate sources, identify and synthesize the fundamental issues that reflect the computation and treatment of travel time reliability in modeling tools. Describe primary measures of effectiveness related to travel time reliability. Draw on other SHRP 2 reliability and capacity projects. Also examine work in NCHRP and NCHRP Technical Activities: Behavioral Framework To capture reliability effectively in demand models a behavioral framework is needed to capture the manner in which congestion affects travel choices. We propose investigating the following issues of relevance; 1. Perceived highway travel time 2. Different patterns of user behavior in presence of unpredictable travel times 3. Disequilibrium (lagged equilibrium) between travel demand and supply. Sources of Travel Time Variation It is recognized that there is understanding of factors responsible for approximately half of all traffic delay and uncertainty in travel time i.e. traffic incidents, work zones, weather, special events, traffic control devices, fluctuations in demand and inadequate base capacity. Going further we recognize the need to distinguish between the systematic and random variation factors in both travel demand and network supply. Task 1 will investigate and classify true random factors to be included in the reliability calculation separately for both demand and supply. 4

5 Quantification of Factors Producing Travel Time Variation Methods of quantifying the many factors of travel time variation are central to the project and Task 1 will evaluate means of dealing with the many challenges. As discussed in our proposal Task 1 will be an opportunity to synthesize the results of prior work on reliability measurement including coordination with other on-going SHRP 2 projects as well as relevant NCHRP projects such as and Team Roles and Responsibilities Task 1 PB Americas: Peter Vovsha Co-Principal Investigator is the technical lead for the product and has primary responsibility. He will prepare a memorandum on Task 1 supported by PB Americas staff. Support: Hani Mahmassani (Northwestern University) Co-Principal Investigator will correspond with the core project team, provide inputs and detailed review of the Memorandum prepared for Task 1. Yannis Stogios (Delcan) Co-principal investigator will correspond with the core project team and provide detailed review. Mark Bradley will correspond through PB Americas with input and review. Xuesong Zhou will correspond through Northwestern University with input and review. Jackie Golob (Delcan) Project Manager will correspond with the core project team and provide coordination and support for all group activities. Her responsibilities include ensuring that work and deliverables proceed on schedule. Task 2 Functional Requirements Of Stochastic Network Simulation Models As stated in the RFP: The work in this task will define the functional requirements of stochastic network simulation models (hereafter referred to as traffic operations models) needed to estimate travel time variability, including but not limited to: Be able to get travel time distributions by link, segment, trip (O-Ds), and for the entire system. Reflect combinations of recurring and nonrecurring congestion found on real networks. 5

6 Be able to quantify the change in travel time due to breakdown in flow (LOS F) Be able to distinguish and model the variability of (1) recurring congestion (e.g. randomness of travel times in saturated flow), (2) nonrecurring congestion due to fluctuations in demand and the effects of traffic control devices, and (3) nonrecurring congestion due to such factors as incidents, weather, work zones, and special events. Provide the flexibility to adapt to various agency and policy environments. Be able to replicate operations/traffic control strategies and traveler information systems. Provide calculations of reliability performance measures among the outputs. Be able to get travel time distributions by link, segment, trip (O-Ds), and for the entire system. Reflect combinations of recurring and nonrecurring congestion found on real networks. Technical Activities The key building block for producing measures of reliability in a traffic network simulation model will be particle trajectories and the associated experienced traversal times through entirety or part of the travel path. Particle trajectories could be obtained from both micro-and meso-level simulation models and the framework to be developed and adopted will unify all particle based simulations. Under Task 2 phenomenon and behaviors will be identified that account for the observed variability in network traffic performance and the most effective approach to modeling at both microscopic and mesoscopic levels will be determined. A key part of requirements development will be focused on the uses of traffic operational models in agencies at the local, metropolitan, regional and state levels in so far as reliability is concerned. Intended use determines required resolution and scale. A series of application cases will be identified. Minimum and preferred requirements will be defined. The necessary functional requirements will then be developed. The functional requirements generated will first be reviewed by the Delcan- Northwestern-PB team, an informal panel of simulation practitioners would then be 6

7 used for further input and review. Selected members of the TRB committees would also be consulted before formal review takes place by NAS. The deliverable will be a draft technical memorandum that describes the functional requirements for the inclusion of travel time reliability estimates in stochastic network simulation modeling tools. Team Roles and Responsibilities Task 2 Northwestern University: Hani Mahmassani Co-Principal Investigator is the technical lead for the product and has primary responsibility. He will prepare a Memorandum on Task 2 with support from NWU staff. Support Xuesong Zhou (University of Utah) will contribute significant input directly to the Northwestern University effort. Yannis Stogios Co-Principal Investigator (Delcan) will contribute input and review to this task and coordinate other Delcan staff input. Peter Vovsha Co-Principal Investigator (PB Americas) will contribute input and review to this task and coordinate other PB Americas staff input. Mark Bradley will contribute review efforts on this task via PB Americas. Jackie Golob (Delcan) Project Manager will correspond with the core project team and provide coordination and support and leadership as required for all group activities. Her responsibilities include ensuring that work and deliverables proceed on schedule. Task 3 Framework for Evaluating Incidents and Events As stated in the RFP: In order to provide meaning to variability in travel time, some baseline is needed. However, in saturated flow conditions, random events introduce variability that may be considered normal for the period. This calls for a formal approach to modeling random events. Develop a repeatable framework for evaluating incidents and events. The framework should be able to isolate three regimes: (1) time periods with recurring congestion (2) time periods of nonrecurring congestion due to variation in demand and the effects of traffic control devices; (3) time periods of nonrecurring congestion due to other factors such as incidents, weather, work zones, and special events. Technical Activities 7

8 Taking the basic framework developed in Tasks 1 and 2, this task will focus on exogenous sources of variation as they affect both demand and supply i.e. random events. Distinguishing these from endogenous sources lies at the foundation of our conceptual approach. We will distinguish between periods of recurring vs. nonrecurring congestion, and further between sources of so-called non-recurrent events. Activities under this approach will involve the building of a scenario generator, which provides the ability to construct scenarios that contain any mutually consistent combination of external events, both demand as well as supply related, including different traffic control plans that may be deployed under certain conditions. The deliverable will be a draft technical memorandum discussing the framework for evaluating incidents and events in the overall travel time reliability modeling application. This will then be integrated with the draft memorandum for Tasks 1 and 2 to form the first deliverable as identified in the RFP. Team Roles and Responsibilities Task 3 Northwestern University: Hani Mahmassani Co-Principal Investigator is the technical lead for the product and has primary responsibility. He will prepare a Memorandum on Task 3 significantly supported by NWU staff. Support Xuesong Zhou (University of Utah) will contribute significant input directly to the Northwestern University effort. Yannis Stogios Co-Principal Investigator (Delcan) will contribute input and review to this task and coordinate Delcan staff input. Peter Vovsha Co-Principal Investigator (PB Americas) will contribute input and review to this task and coordinate PB Americas staff input. Mark Bradley will contribute review efforts on this task via PB Americas. Jackie Golob (Delcan) Project Manager will correspond with the core project team and provide coordination and support and leadership as required for all group activities. Her responsibilities include ensuring that work and deliverables proceed on schedule. In addition she will have oversight of the first Task 1,2,3 deliverable. 8

9 Task 4 Candidate Networks and Models As stated in the RFP: This task will identify good candidate networks and model applications (i.e., simulation software available from vendors that have already been applied by transportation agencies for specific projects) that may be used to satisfy the requirements set out in Task 2. Document how the candidates satisfy the requirements. Consider partnering with one or more local agencies in carrying out the remaining tasks, particularly in Phase II. Technical Activities A series of criteria will be established for identifying, evaluating and selecting such network-model combination that will allow us to address and meet the project requirements. The criteria will reflect the technical research requirements identified in Tasks 2 & 3, as well as a series of non-technical requirements that would contribute to such model development and testing. Both mesoscopic and microscopic models will be considered. Non-technical considerations include: network size and configuration for meaningful measurement of travel time variability; in terms of configuration, the network will have to comprise (at a minimum) freeways, arterial roads and interchanges / intersections under various types of traffic control, and likely some type of managed lanes, advanced traffic management systems availability of traffic data in the form of speed / flow measurements preferably through an already operational and reliable detection system network congestion characteristics and availability of statistics / measurements of such characteristics including cause, duration, type of congestion, etc. availability of an already developed traffic operations model, with a spatial and temporal scope suitable to the purposes of this research project, or easily modifiable to accommodate the requirements identified in the above willingness of jurisdictional authority to participate as partner in the project or at least provide / share the necessary data and/or applicable base model if available 9

10 familiarity of research team staff with candidate network, data and model. Agency discussions to establish partnering requirements and support will play a critical role in the conclusions to be reached. The task will result in a draft technical memorandum discussing the rationale, criteria and selection process for identifying candidate networks and models for the simulation application. Team Roles and Responsibilities Task 4 Yannis Stogios Co-Principal Investigator (Delcan) is the technical lead for the product and has primary responsibility. He will prepare a memorandum on Task 4 with the support of Delcan staff input. Support Northwestern University: Hani Mahmassani Co-Principal Investigator will contribute review and input to this task and will coordinate NWU staff input o the task. Xuesong Zhou (University of Utah) will contribute input directly to the Northwestern University effort. Peter Vovsha Co-Principal Investigator (PB Americas) will contribute input and review to this task and coordinate PB Americas staff input. Mark Bradley will contribute review efforts on this task via PB Americas. Jackie Golob (Delcan) Project Manager will correspond with the core project team and provide coordination and support and leadership as required for all group activities. Her responsibilities include ensuring that work and deliverables proceed on schedule. Task 5 Data As stated in the RFP: The task requires obtaining data from public and/or private sources that can be used in Phase II for developing and implementing a simulation model that satisfies the requirements established in Task 2. The data should provide information on the distribution (i.e. variation) of travel time and other traffic flow variables on network links due to recurring and non-recurring congestion over a lengthy period of time (six months minimum) and should cover both recurring and non-recurring congestion on freeways and arterials. Technical Activities 10

11 The task is tightly linked to Task 4 since the requirements of Task 5 will become a criterion for the selection of a network model in Task 4. The two tasks will therefore be performed concurrently. Data sources selected, both public and private will need to fully support the requirements of the conceptual approach identified in Task 1,2 and 3. It will also be necessary to reflect the requirements specified in Task 7, Phase II. The task will result in a draft technical memorandum that will document data availability and use arrangements. Team Roles and Responsibilities Task 5 Yannis Stogios Co-Principal Investigator (Delcan) is the technical lead for the product and has primary responsibility. He will prepare a memorandum on Task 5 with the support of Delcan staff input. Support Northwestern University: Hani Mahmassani Co-Principal Investigator will contribute review and to this task and will coordinate NWU staff input to the task. Xuesong Zhou (University of Utah) will contribute input directly to the Northwestern University effort. Peter Vovsha Co-Principal Investigator (PB Americas) will contribute input and review to this task and coordinate PB Americas staff input. Mark Bradley will contribute review and input efforts on this task via PB Americas. Jackie Golob (Delcan) Project Manager will correspond with the core project team and provide coordination and support and leadership as required for all group activities. Her responsibilities include ensuring that work and deliverables proceed on schedule. Task 6 Phase I Draft Report As stated in the RFP: Task 6 encompasses the preparation of the Phase I Draft Report, including a work plan for Phase II. The report will include the following: This document will review in detail all of the preliminary steps taken to develop the means by which traffic operations and planning models can 11

12 reflect travel time reliability and generate travel time reliability as a model output. The Phase I report will: Document the fundamentals and conceptual thinking that underpin the approach Review and make recommendation for network simulation models to be applied and modified in Phase II Offer modeling approaches to deal with random events Select candidate networks including partnership agreements with agencies as required Collect the necessary supporting data set (s) to provide information on the distribution of travel time and other traffic flow variables on network links due to recurring and non-recurring congestion over a minimum time period of six months, covering recurring and nonrecurring congestion on both freeways and arterials. The final product of the Phase I report shall be the detailed Work Plan for Phase II Following response to comments received on the draft a final Phase I report will be generated for final review. The deliverables for this task are therefore: Phase I Draft Report Phase I Final Report Team Roles and Responsibilities Task 6 Jackie Golob (Delcan) Project Manager will have lead responsibility for the production of the draft and final Phase I report. Support Yannis Stogios Co-Principal Investigator (Delcan) will lead the technical support and coordinate other Delcan staff input. Northwestern University: Hani Mahmassani Co-Principal Investigator will contribute review to this task and will coordinate NWU staff input to the task. Xuesong Zhou (University of Utah) will contribute input directly to the Northwestern University effort. Peter Vovsha Co-Principal Investigator (PB Americas) will contribute input and review to this task and coordinate PB Americas staff input. Mark Bradley will contribute review and input efforts on this task via PB Americas. 12

13 Phase II Demonstration of a Traffic Simulation Model that Reflects Reliability in a Subarea of a Network and Preparation of Application Guidelines Task 7 Adaptation or development of Simulation Model As stated in the RFP: Task 7 activities will adapt and calibrate an existing traffic simulation model with the functionality described in Phase I and apply it to a reasonably large subarea of an urban network. Alternatively, build and calibarate your own model and similarly apply it. Include in the subarea at least one urban freeway, system interchanges, and surface arterial roads. Make the simulation model internally reflect travel time reliability and produce one or more reliability performance measures as an output. Run the model suing different random seeds and calibrate the basic variability in travel time due to operations at saturation, e.g. recurring congestion. Validate that the model reflects the real-world variability associated with recurring and nonrecurring congestion. Technical Activities The task begins with scoping activities to investigate in further detail how the planning and operational model will need to interact. Working meetings will be held with relevant agency staff to review certain items. Sub-tasks are: Refine end-use requirements and criteria Define required system components Define spatial definition/boundary Define temporal elements Define required component flow Confirm model capabilities Establish model configuration parameters All of the above lead to a model specification technical memorandum. Data assembly will be followed by network structure and coding to be followed by the supply side calibration, the demand side calibration and the supply/demand interaction calibration. This then leads to the output processes represented through performance measures that amongst other things can be judged to best reflect travel time reliability. The deliverable to be developed for this task will be a technical memorandum documenting the model development or adaptation exercise, including the results of the scoping, calibration, validation and output processes. 13

14 Team Roles and Responsibilities Task 7 Yannis Stogios Co-Principal Investigator (Delcan) is the technical lead for the product and has primary responsibility. He will prepare a memorandum on Task 7 with the support of Delcan staff input. Support Northwestern University: Hani Mahmassani Co-Principal Investigator will contribute both review and input to this task and will coordinate NWU staff input to the task. Xuesong Zhou (University of Utah) will contribute input directly to the Northwestern University effort. Peter Vovsha Co-Principal Investigator (PB Americas) will contribute input and review to this task and coordinate PB Americas staff input. Mark Bradley will contribute review effort on this task via PB Americas. Jackie Golob (Delcan) Project Manager will correspond with the core project team and provide coordination and support and leadership as required for all group activities. Her responsibilities include ensuring that work and deliverables proceed on schedule. Task 8 Demonstration of Travel Time Reliability Application Model As stated in the RFP: the task uses the inputs and results from earlier tasks to demonstrate the inclusion of travel time reliability in the application of the simulation model in Task 7. The model will be demonstrated to practioners, researchers, operations managers, and planners in transportation agencies and at conferences and meetings. Run scenarios that address the causes of non-recurring congestion. Show how sensitive the reliability outputs are with respect to key inputs and how traffic flow characteristics are sensitive to reliability. Our outreach activity will be aimed at demonstrating the developed model to primarily two sets of users: Practitioners and researchers, who may have a keen interest in the fundamentals of the modeling application Operations managers and planners in transportation agencies, who may be interested primarily in the practical outcome of such application 14

15 Technical Activities Pilot demonstrations of the simulation model and its travel time reliability application will be performed to members of the L04 Panel and select members of the modeling research community, prior to embarking on a broader demonstration and outreach activity. Once the demonstration scenarios and process are confirmed, the project team will initiate a series of formal outreach activities targeting the broader community of practitioners, researchers, operations managers, and planners in transportation agencies. Materials will be developed that help demonstrate the model as it includes travel time reliability. The use of visualization tools to support this effort will be emphasized. To engage the developer and academic communities, the team will work with existing specialty conferences on traffic simulation and special vendor targeted workshop sessions at major conferences such as TRB. The team members individually and collectively have close contact with several of the developers. In addition the full Delcan team has a wide array of agency contacts and will endeavor to find means to reach as many agencies as possible. Team Roles and Responsibilities Task 8 Northwestern University: Hani Mahmassani Co-Principal Investigator is the technical lead for Task 8 supported by NWU staff. Support Xuesong Zhou (University of Utah) will contribute significant input directly to the Northwestern University effort. Yannis Stogios Co-Principal Investigator (Delcan) will contribute input and review to this task and coordinate Delcan staff input. Peter Vovsha Co-Principal Investigator (PB Americas) will contribute input and review to this task and coordinate PB Americas staff input. Mark Bradley will contribute review efforts on this task via PB Americas. Jackie Golob (Delcan) Project Manager will correspond with the core project team and provide coordination and support and leadership as required for all group activities. Her responsibilities include ensuring that work and deliverables proceed on schedule. 15

16 Task 9 Develop Application Guidelines As stated in the RFP: The application guidelines for incorporating travel time reliability into traffic microsimulations should not be software specific. The guidelines shall be a stand-alone document. This task entails a distillation and synthesis of the findings from the conceptual, methodological and application-oriented development undertaken in this study into a document that would define the state of the art for incorporating travel time reliability in simulation-based operational studies. The guidelines will not be limited strictly to microscopic traffic simulation models, but rather will include any simulation that can produce individual vehicle trajectories as discussed under Task 2, where these were referred to as particle-based simulation approaches. These would include both microscopic and mesoscopic simulation tools, as well as particlehopping approaches such as implemented in TRANSIMS. Technical Activities The Application Guidelines will include the following parts: 1. Introduction, types of problems addressed, objectives and document organization 2. Operational definitions of reliability 3. Conceptual framework 4. Modeling capabilities/assumptions; 5. Delineating analysis scope for given study; 6. Calibration requirements and data sources; Validation requirements and data sources; 7. Design of simulation experiments; 8. Output analysis through Universal Graphical Interface and statistical testing; 9. Using output to support operational planning and decision-making; 10.Case study application using microscopic model 11.Case study application using mesoscopic model 12.Advanced topics: integrating reliability simulation into planning model structure Team Roles and Responsibilities Task 9 Northwestern University: Hani Mahmassani Co-Principal Investigator is the technical lead for Task 9 supported by NWU staff. Support 16

17 Xuesong Zhou (University of Utah) will contribute significant input directly to the Northwestern University effort. Yannis Stogios Co-Principal Investigator (Delcan) will contribute input and review to this task and coordinate Delcan staff input. Peter Vovsha Co-Principal Investigator (PB Americas) will contribute input and review to this task and coordinate PB Americas staff input. Mark Bradley will contribute review efforts on this task via PB Americas. Jackie Golob (Delcan) Project Manager will correspond with the core project team and provide coordination and support and leadership as required for all group activities. Her responsibilities include ensuring that work and deliverables proceed on schedule Task 10 Phase II Report As stated in the RFP: This task requires preparation and submittal of a Phase II Draft report that documents the results of Tasks 7 through 9. Documentation of the model calibration and validation shall be consistent with standard practice as described in either the FHWA or Caltrans guidelines for Applying Micro-Simulation Software. The deliverables for this task are therefore: Phase I Draft Report Phase I Final Report Team Roles and Responsibilities Task 10 Jackie Golob (Delcan) Project Manager will have lead responsibility for the production of the draft and final Phase I report. Support Yannis Stogios Co-Principal Investigator (Delcan) will lead the technical support and coordinate other Delcan staff input. Northwestern University: Hani Mahmassani Co-Principal Investigator will contribute review support to this task and will coordinate NWU staff input to the task. Xuesong Zhou (University of Utah) will contribute input directly to the Northwestern University effort. 17

18 Peter Vovsha Co-Principal Investigator (PB Americas) will contribute input and review to this task and coordinate PB Americas staff input. Mark Bradley will contribute review and input efforts on this task via PB Americas. Phase III Incorporating Reliability into Travel Demand Forecasting Models and Addressing Feedback with Simulation Models. Task 11 Incorporating Reliability into Travel Demand Models As stated in the RFP: Describe how a feedback mechanism could incorporate travel time reliability into traditional trip-based travel demand models, emerging activity based models, and route choice models. Detail how reliability could be introduced into generalized cost function (many apply to one or more of the following: generation, distribution, mode choice, route choice.) Technical Activities A revised discussion of the work activities and challenges was included in our response to comments from the SHRP 2 LO4 panel members. It is attached in full to this document within the response. The deliverables for the task are: Stand-alone Phase III Draft Report Stand-alone Phase III Final Report Team Roles and Responsibilities Task 11 PB Americas: Peter Vovsha Co-Principal Investigator is the technical lead for the product and has primary responsibility. He will prepare a memorandum on Task 11 supported by PB Americas staff. Bob Donnelly will support the task of coordination with the ongoing SHRP II CO4 project on impact of congestion and pricing on travel behavior. Support: 18

19 Hani Mahmassani (Northwestern University) Co-Principal Investigator will provide input and detailed review of the deliverable prepared for Task 11 and will coordinate input by NWU staff. Yannis Stogios (Delcan) Co-principal investigator will provide detailed review and input and coordinate input from Delcan staff. Mark Bradley will correspond through PB Americas with significant input and review. Xuesong Zhou will correspond through Northwestern University with input and review. Jackie Golob (Delcan) Project Manager will correspond with the core project team and provide coordination and support for all group activities. Her responsibilities include ensuring that work and deliverables proceed on schedule. In addition she will have oversight of the Phase III Draft and Final reports 19

20 Schedule and Work Flow Diagram 20

21 # Project Deliverables as listed below Meetings with SHRP Staff or Reliability Technical Coordinating Committee (no specific dates have been set) Quarterly Progress Reports Project Deliverables: Phase I 1. Tech Memo Tasks 1,2 & 3 2. Tech Memo Tasks 4 & 5 3. Phase I Draft Report 4. Phase I Final Report Phase II 5. Validated Model 6. Demonstration & Outreach 7. Application Guidelines Draft 8. Application Guidelines Final 9. Phase II Draft Report 10. Phase II Final Report Phase III 11. Phase III Draft Report 12. Phase III Final Report 21

22 Response to SHRP 2 LO4 Comments

23 SHRP 2 Reliability ETG Project L04, Incorporating Reliability Performance Measures in Operations and Planning Modeling Tools Addendum of Modifications to the Original Proposal by Delcan Modify and/or justify budget based on the following recommendations and observations: Project ownership. The team members are aware that SHRP would normally wish to work with one Principal Investigator representing ownership of the project. The tri-pi approach adopted for the technical work is intended to reflect the multi-disciplinary skills required for successfully approaching and conquering the unique technical challenges of this project. All three have a strong commitment to the project. This approach has proven successful in other similar multifaceted projects. There is complete concurrence amongst the team members that Delcan owns the project and has responsibility for the delivery of the project. The addition, on this occasion of a Project Manager for the duration of the project is recognition that three Principal Investigators require coordinating support to be fully effective in commitment of their attention to project tasks. Additional hours have been added for Yannis Stogios to emphasize his role as Delcan s Co-PI and this is illustrated in the revised line item budget attached to this addendum. The management organization chart remains unchanged and a lead PI is identified for each task with the exception of Task 10 the final reporting task, which is led by the Project Manager Jacqueline Golob with the full support of all Co-PIs. Dr. Hani Mahmassani s hours have been increased from 135 to 416 as requested and this is reflected in the revised budget attached to this addendum. As a general statement, the key members are not overcommitted. Their stature in the field means that their unique skills and expertise are in demand. However, they bring together long experience in project team management and dividing the work in such a way as to involve key collaborators in the work while maintaining close day-today engagement. In addition, synergy amongst various project commitments adds value to the present project. The NCHRP Project will be completed in March 2009 (A Draft Final Report is currently being reviewed by the Panel). Also, even for the several months before the completion of NCHRP 08-57, the total commitment of any of these three key members on all three projects does not 23

24 exceed 50%. From March 2009 on, the combined commitment of any of them to SHRP would not exceed 30%. The hours initially budgeted for graduate student time has been reduced to 1553 hours in order to allow the increase in Dr. Mahmassani s budgeted time. Several students are normally engaged in all research projects under Dr. Mahmassani s supervision at Northwestern as part of the graduate education and training process, thereby providing continuity. The change in hours is reflected in the budget attachment. 2. The perception that there is too much emphasis on meso simulation and DYNASMART-P is an unfortunate one, possibly due to one of the PI s involvement in the development and application of this modeling approach. The perception does not correspond to the reality of what is envisioned under this project. The central premise of our approach is that modeling reliability and its effect on network performance, including effect on the demand side, can and should be developed as a generic methodology that is independent of the specific platform on which it is implemented. Given our long experience developing simulation models at all levels of resolution, especially micro and meso simulation models, we are convinced that the development of the methodological underpinnings of modeling reliability can be done largely independently of the physics underlying the movement of individual vehicles in the network. 3. In micro-simulation models, the main logic for moving vehicles consists of car following rules (which govern vehicle acceleration and speed) and lane changing rules, reflecting feasibility and safety while translating a driver s desire to go faster than the leading vehicle or to enable a maneuver such as exiting a highway. Hamdar and Mahmassani have recently proposed an integrated approach, in which car following and lane changing are viewed in the same perspective. They have illustrated their approach and found these models to produce realistic aggregate flow behavior, including phenomena such as flow breakdown, a key cause of unreliability during peak periods. The description of the model adaptation / development tasks is also consistent with the main premise of our approach (generic methodology that is platform independent) as discussed in the response to the previous question. It is clearly the team members intent to demonstrate the approach at both the microsimulation level with the emphasis on corridor level applications as well as at a broader regional level that will utilize meso modeling approaches. Given the significance of the outcomes of Tasks 1 and 2 and the selection of the modeling network in Task 4 and data availability to be discussed in Task 5 it is somewhat premature to elaborate further in depth on the micro-simulation to be pursued in Task 7. The functional aspects of incorporating travel time reliability measures in the modeling tools must first be established. 24

25 4. Micro simulation experience - The team s foremost expert: Dr. Mahmassani brings unique depth and breadth of related knowledge in traffic science, behavioral modeling, statistical analysis, micro-simulation, and traffic network analysis methods and applications to this challenging problem. He is recognized nationally and internationally for pioneering contributions to micro-simulation models of driver behavior, including the first published application of discrete choice modeling techniques to gap acceptance and amber light stopping decisions, as well as lane changing situations. He has also made pioneering contributions to representation of individual decisions in the context of large-scale network models, resulting in practical tools that are widely used in practice. Additionally he has served as advisor to the NGSIM project, funded by FHWA, since its inception, and played an active role in defining directions for research and application for the traffic simulation community. He is the immediate past chairman of the Traffic Flow Theory and Characteristics committee of the Transportation Research Board, and served as founding chair of the Network Modeling Committee of TRB, in addition to active membership over many years in the travel behavior committees of TRB. He is a founding member of the Task Force on Traffic Simulation Models of TRB, and member of the scientific committees of most national and international conferences on traffic simulation and network modeling. Delcan has traditionally maintained a position of leadership in the areas of modeling and simulation both nationally and internationally. Delcan has one of the largest modeling groups in Canada with 12 modelers in four offices across the country.they are part of the DHV/Delcan Group of Companies International Modeling Team which has approximately 35 members worldwide specializing in modeling software development and applications. These resources and network of shared knowledge is always available to our clients and can be tapped into for this project as well, should such need arise. Wide range of transportation modeling experience with various, different types of models; starting with earlier generation micro-simulation packages (TRAF-NETSIM, CORSIM, INTEGRATION) and continuing with current state-of-the-practice Aimsun, VISSIM, PARAMICS (both SIAS and Quadstone) etc., complemented with macroscopic modeling experience (TRIPS, EMME, TRANSCAD, VISUM, etc., and now also in the field of mesoscopic modeling (DYNASMART, DYNAMEQ, Aimsun). 5. Scenario Analysis - See attachment 1. This represents a revised Task 11 which began on page 46 of the proposal. Section 11.4 is a new section which discusses the technical aspects of scenario formation. 6. Reliability approaches and vendor developments Vendor incorporation of reliability into modeling platforms. As noted in the response to item 2, our approach is envisioned to be platform-independent, and hence applicable in conjunction with various commercial and open source platforms. 25

26 Adoption by developers and incorporation within existing tools will depend on the transparency of the approach, its theoretical soundness, and ability to integrate with various modeling approach independently of the specific physics underlying vehicle movement. To engage the developer and academic communities, the team will work with existing specialty conferences on traffic simulation and special vendor targeted workshop sessions at major conferences such as TRB. The team members individually and collectively have close contact with several of the developers. 26

27 Attachment 1 TASK 11: INCORPORATING RELIABILITY INTO TRAVEL MODELS 11.1 Addressing Feedback with Simulation Models Linking travel demand forecasting to traffic micro-simulation is one of the most important aspects of the current project. The simulated traffic conditions (described not only in term of average travel time but as travel time distributions with reliability measures) should be fed back to choices of travel route, travel mode, departure time, and other possible choice dimensions (including destination choice or even decision to travel at all, i.e. trip frequency/generation choice). Incorporation of average travel time in the feedback mechanism has become a routine part of travel models and traffic assignment models. Traffic assignment models operate with (average) generalized cost combined of (average) travel time and (average) cost expressed in travel time units. This measure is directly used in route choice embedded in the network simulation procedure. Further on, travel time and cost skims are used to form mode choice utilities. The other choice dimensions (time-of-day choice, destination choice, etc) included either mode-choice Logsums or time / cost skims depending on the model structure. Incorporation of travel time reliability in the feedback mechanisms is not trivial since the travel time reliability measure in itself require several iterations with varied demand and supply conditions. The reliability measure can be introduced in the generalized cost function of route choice (in addition to average travel time and cost as described in the Technical Appendix 1). Then, the route generalized cost (or separate time, cost and reliability skims) can be used in the mode choice and upper level models. This technique however, would only address one iteration feedback of (previously generated) reliability on average travel demand. The fact that both demand and supply fluctuations affect reliability creates a certain complication. In 27

28 other words, the equilibration scheme should incorporate the process of generation of reliability measure itself. The general suggested structure that resolves this issue is presented in FIGURE 2 below. It includes only the travel time variation measure of reliability as the only practical option within the project time and budget. The key technical feature of this approach is that the very top and bottom components average demand and average travel time are preserved as they function in the conventional equilibration scheme while the reliability measures are generated by pivoting off the basic equilibrium point. FIGURE 2: SUGGESTED FEEDBACK IMPLEMENTATION Distribution of travel times is essentially modeled as a composition of three sets of probabilistic scenarios: 1) demand variation scenarios, 2) network capacity scenarios, and 3) network simulation scenarios. Each set of 28

29 scenarios has its own group of factors that cause variation. The final distribution of travel times is generated as a Cartesian combination of the demand, capacity, and simulation scenarios. It is essential to have a static demand-supply equilibrium point (between the average demand and supply) explicitly modeled for two reasons: Define the basic travel demand patterns (at least in probabilistic terms) from which the variation (scenarios) can be pivoted off. Provide the background level of congestion and associated fragility of traffic flows from which the probability of breakdowns can be derived. The average demand is a function of both average travel time and reliability (through measures like buffer time). It is assumed that the average demand and the corresponding equilibrium point are simulated separately for each season (if seasonal variation is substantial), day-of-week (if there is a systematic variation across days of week), and time-of-day period conditions though there is a linkage across the demand generation steps for different periods of a day (especially if an advanced Activity-Based model is applied). The demand fluctuation scenarios are created by application of several techniques (like Monte-Carlo variation) and auxiliary models (like special events model) described in the subsequent sections. In additional to feeding back the resulted average travel times and reliability measures to the average demand generation stage (i.e. having a global feedback), two additional (internal) feedback options will be considered: First internal feedback of scenario-specific travel times through route choice adjustments in the network simulation procedure. In this feedback, travel demand, and network capacity is considered fixed. However, route choice can change from iteration to iteration because of the factors associated with traffic control, incidents, individual variation of driving habits, as well as dynamic real-time pricing, if applied. The network simulation can also incorporate probability of flow breakdown. In the course of the project, the corresponding network simulation algorithm and route choice feedback mechanism will be established first. Then, this module will be employed within the demand-supply equilibrium framework (second internal feedback and global feedback). 29

30 Second internal feedback of travel time distributions (and any derived measure of reliability) to the demand scenario through schedule adjustments of trip departure times. In this feedback, the demand scenario in terms of trip generation, distribution, and mode choice is considered fixed while the trip departure time can change from iteration to iteration as the result of travel time fluctuations modeled by the network capacity and network simulation scenarios. The purpose of this feedback is to stabilize trip departure times for each demand scenario. This feedback is applied within the global equilibrium loop. The details of demand generation process and its sensitivity to reliability measures depend on the type of travel demand model. We plan to address both traditional (4-step) trip-based travel demand models and advanced Activity-Based models. Activity-Based modeling framework represents a more promising counterpart to microscopic and mesoscopic network simulation models because of the more compatible temporal resolution. Advanced Activity-Based models in practice already operate with min demand slices while traditional 4-step models operate with broad 3-4 hour periods. For a 4-step travel demand model, the following dimension and components of travel demand can be included in the equilibrium framework and incorporate reliability measures: Mode choice, where utility functions for highway modes (drive alone, shared ride) can include buffer time or any other reliability measure. Trip distribution, where the travel impedance function can include mode choice Logsum or directly include reliability measures. Trip time-of-day choice, specifically for highway modes, where the peak (and other period-specific) factors can include period-specific reliability measures. Trip generation, which can be made sensitive to accessibility measures (destination choice Logsums) that can include reliability measures along with average travel time and cost. For an Activity-Based travel demand model, the following dimension and components of travel demand can be included in the equilibrium framework and incorporate reliability measures: 30

31 Mode choice, where utility functions for highway modes (drive alone, shared ride) can include buffer time or any other reliability measure. Primary destination choice, where the travel impedance function can include mode choice Logsum or directly include reliability measures. Stop frequency and location choices for chained tours that are also based on travel impedance functions with reliability measures. Tour generation models (daily activity-travel pattern), which can be made sensitive to accessibility measures (destination choice Logsums) that can include reliability measures along with average travel time and cost. Tour time-of-day models (daily schedule), which can be made sensitive to time-specific reliability measures. It should be mentioned that despite certain similarities between the 4-step and Activity-Based models in the approaches to incorporate reliability feedbacks, there are some principal differences that should be taken into account. In particular, 4-step models operate with aggregate zonal flows. Thus, any demand response to reliability will be identical for all trips within the same segment. Contrary to that, Activity-Based models are based on individual microsimulation. This opens a way to implement the feedback on individual level where additional individual variation will be taken into account. Also, the utility coefficients in microsimulation models can be effectively randomized taking in to account individual variation of Value of Time and Value of Reliability. In the course of the current project we plan to investigate all feedback options in detail including a theoretical substantiation of the unique equilibrium conditions (if possible) and extensive empirical work with operational software that is capable of generating reliability measures in different regional and travel conditions. In 2009, SHRP 2 Capacity Project C10 will call for proposals from transportation agencies to actually establish part of this linkage, i.e. linking travel demand forecasting to micro-simulation. We agree that the product of Task 11 due to exploring feedback relationships between travel forecasting and simulation models will provide background for Project C10. We plan to closely coordinate with C10 team and adjust the course of work on this project if necessary for a better cooperation. In particular, we might be focusing on a specific demand model structure (according to the model and 31