Abstract

The overall objective of this project is to develop an optimal resource allocation tool for the entire state of California using Geographic Information Systems and widely available data sources. As this tool evolves it will be used to make investment decisions in transportation infrastructure while accounting for their spatial and social distribution of impacts. Tools of this type do not exist due to lack of suitable planning support tools, lack of efforts in assembling data and information from a variety of sources, and lack of coordination in assembling the data. Suitable planning support tools can be created with analytical experimentation to identify the best methods and the first steps are taken in this project. Assembly of widely available data is also demonstrated in this project. Coordination of fragmented jurisdictions remains an elusive task that is left outside the project. When this project begun we confronted some of these issues and embarked in a path of feasibility demonstration in the form of a pilot project that gave us very encouraging results. In spite of this pilot nature aiming at demonstration of technical feasibility, substantive conclusions and findings are also extracted from each analytical step.

In this project we have two parallel analytical tracks that are a statewide macroanalysis (called the zonal based approach herein) and an individual and household based microanalysis (called the person based approach herein). In the statewide macroanalysis we study efficiency and equity in resource allocation. Resources are intended as infrastructure availability and access to activity participation offered by the combined effect of transportation infrastructure and land use measured by indicators of accessibility. Stochastic frontiers are used to study efficiency and a particular type of inequality measurement called the Theil fractal inequality index is used to study equity in the macroanalysis. The outcome of this analysis are maps identifying places in California that enjoy higher levels of service when compared to the entire state and places which succeeded in allocating resources in a relatively better way than others. In the individual microanalysis we use the accessibility indicators from the macronalysis and expand them by defining a new set of indicators at a second level of spatial (dis)aggregation. Then we use them as explanatory factors of travel behavior with focus on the use of different travel models (e.g., driving alone, use of public transportation and so forth). As expected infrastructure availability and accessibility to activity opportunities has a significant and substantive effect on the use of different modes. Many resource allocation decisions, then, will impact behavior, which in turn influences the optimality and equity conditions. This implies that decisions about where and when to allocate resources in public and private transportation needs to account for changes in behavior in a dynamic fashion, using scenarios of accessibility provision and assessing their impact by studying activity and travel behavior changes.

Abstract

The report describes three research efforts carried out under a project titled “Development of Hardware-in-the-Loop (HiL) Simulation and Paramics/VS-PLUS Integration” sponsored by the California Department of Transportation (Caltrans) under Task Order 5311. The first effort developed and evaluated traffic signal optimization with Hardware-in-the-Loop Simulation (HiLS), using the NIATT Controller Interface Device (CID) manufactured by McCain Traffic Supply to provide real-time linkage between the Paramics microscopic simulation and a NEMA TS1 controller. An adaptive control system incorporated the traffic flow prediction model to predict the traffic flows from the surrounding intersections, and an online signal optimization model was used to obtain the signal timing plan for the subsequent cycle, based on the traffic flows predicted in the previous cycle. The performance of the proposed adaptive control system was evaluated through a case study in which HiLS is applied to a small urban network in Logan, Utah. The second effort developed a Paramics plug-in that worked over a serial port connection to a specially modified 170 for HiL operation. After this initial development, the NIATT/McCain CID was configured to work as a Paramics plug-in with both 170 and 2070 controllers, and experiments were carried out to compare the performance of Paramics simulations with the UC Irvine Paramics signal controller plug-in with HiLS. In the third effort, investigation and evaluation of integrated Paramics/VS-PLUS software was carried out, resulting in a user’s guide for use of the integrated Paramics/VS-PLUS simulation software.

Abstract

The central goal of this research is to develop a systematic framework and the support tools to ease, streamline and speed up the calibration of micro simulation projects. Part III of the final report documents the accomplishments achieved in the second phase of the research project. They include the following.

First, to overcome the lengthy time it takes for GA to obtain local and global driving behavior modeling parameters, we implemented a faster heuristic optimization technique, the simultaneous perturbation stochastic approximation (SPSA) and compared its performance with other heuristic optimization methods. Results indicate that SPSA can achieve comparable calibration accuracy with much less computational time than the often used Genetic Algorithm (GA) method.

Second, we developed a much faster O-D estimation tool to obtain an initial time-dependent O-D trip table. This O-D trip table can be used as a seed table in Paramics’ own O-D estimator for further refinement, or directly used in a micro simulation. In either case, the estimation time of O-D trip tables can be considerably shortened. Since our O-D estimation tool makes use of a macroscopic traffic model (logit path flow estimator, or LPFE), a network conversion tool is therefore developed to convert Paramics’s detailed network settings to those of LPFE and vice versa.

Third, we enhanced the vehicle actuated signal control APIs in Paramics, making it more versatile to implement and simulate various types of actuated traffic control strategies found in practice. We also developed a set of guidelines to help micro simulation users to set up and check signal settings in a micro simulation project.

Finally, we developed a summary statistics tools to track, diagnose and report on the calibration as it progresses or after it terminates, and carried out a case study using the SR-41 network in Fresno to demonstrate the use of the developed tools, identify potential problems and summarizing our calibration experiences with large scale networks.

Our case study indicates that the developed calibration tools can indeed ease, streamline and speed up the calibration of micro simulation, particularly when the network concerned is large. It also reveals that the calibration of a micro simulation is a complex task that involves numerous engineering judgments and cannot be fully automated. In a micro simulation, every modeling detail matters and each must be treated properly to ensure a good simulation outcome.

Abstract

Reliable origin/destination (O-D) data are critical to many applications in transportation planning, design and operations. Because of the high costs of and challenges in obtaining reliable O-D trip matrices from surveys or other direct sampling methods, estimating O-D trip tables from a readily available data source, traffic counts, provides an attractive, economical alternative. This project investigates one such an estimation method and implements it in a user-friendly software tool called Visual PFE TD. The developed O-D estimation tool can be used to obtain both static and dynamic O-D trip tables for traffic simulation studies, project evaluations, and transportation planning in a more streamlined and less time-consuming manner. For example, it has been used to obtain an initial seed matrix for Paramics’ O-D estimator to speed up the latter’s O-D estimation process.

A logit path flow estimator (LPFE) originally proposed by Michael Bell (1995) is adopted in this research for inferring both steady and time-dependent O-D trip tables. LPFE is chosen because: 1) it incorporates the logit-based route choice model while avoiding several difficulties encountered in the conventional bi-level formulation; 2) it avoids the difficult dynamic traffic assignment problem through decomposes the dynamic O-D estimation problem into a sequence of static problems, yet takes into account of queuing by linking the static problems across time with residual queues which can be carried over from one period to subsequent periods; and finally, 3) it has been validated in a number of scenarios as a potential tool to determine O-D flows and path travel times in various transportation networks.

In this research, we extended the original LPFE formulation and improved the efficiency of solution algorithms, implemented both steady-state and time-dependent LPFE in an object-oriented programming (OOP) framework, tested the performance of LPFE using synthetic data and quantify the accuracy and reliability of its O-D trip table estimates. We also developed Visual PFE and Visual PFE-TD, the graphic user interfaces (GUI) for both static and time-dependent LPFE.

Our test case studies show that LPFE is able to produce path flows and O-D travel demands that accurately match traffic counts under the logit traffic assignment assumption. We also found that information reflecting the spatial structure of travel demands (e.g., a historical O-D table) is of great value to the improvement of the quality of O-D trip estimates, and that LPFE can still produce satisfying estimates even when traffic counts are only available on a small portion of links, as long as such structural information is maintained in the base O-D table.

Abstract

This report describes a reinterpretation of how the philosophy underlying the Cartesiusmulti-jurisdictional incident management prototype can be used as an organizing princi-ple for real-world multi-jurisdictional systems. This interpretation focuses on the power ofthe Distributed Problem Solving (DPS) approach Cartesius uses to partition analysis andoptimization functions in the system across jurisdictions. This partitioning minimizes theamount of local information that must be shared between jurisdictions and paves the way fordefining a collection of TMC-to-TMC messages that support the Cartesius DPS perspectivein a manner that respects existing deployments.

Based on this interpretation, the report recommends building a new TMC software agentthat provides operators with a view of the system from Cartesius DPS perspective. This toolwill initially be advisory in nature, providing operators with guidance regarding how localactions are likely to conflict with the actions of neighboring jurisdictions (or lack thereof).Where it is appropriate, and where local policy permits, the new management agent couldalso be connected to available control subsystems to provide operational or tactical controlin response to problems in the system.