Interacción e Impacto Social

The development of the transportation planning tool was initiated in the 1995-1997 Intermodal Management System Project. This project was provided for the statewide geographic information system project (GIS) which could display several modal transportation networks (e.g., highway and rail systems) plus a variety of transportation hubs and intermodal transfer services (e.g., airports, inter-city train and bus stations, rail/truck terminals, port facilities). Initially the TransCAD GIS incorporated a routing system that allows the display of highway attribute information (number of lanes, functional classification, and average daily traffic, etc.) from the INDOT highway inventory file. This connection provided for the development of a statewide travel demand model.

In order to condcut regional long-term planning using TransCAD, there is something missing that needs to be incorporated within this tool. This study focuses on using the Indiana travel demand model by incorporating crashes on segments and nodes in TransCAD for regional long-term planning. Prediction of crashes is being added in the existing networking of TransCAD. By doing so, the planners will take data from travel demand models and TransCAD in order to utilize it for long-term planning. The developed tool also predicts the changes in crash frequency and severity in response to geometry improvement and therefore can quantify the safety implications of geometry and control differences between alternative projects. This has been accomplished by extracting Crash Modification Factors from existing models and combining them. Finally, the combined model variables have been linked with TransCAD variables. The safety analysis tool has been developed for corridor studies. This task has been accomplished by developing the components of the method for corridor studies, including its manual.

2.9

Chapter summary

This chapter reviewed the various components and methodologies currently in use by Indiana and other states for highway safety in the planning process, such as crash prediction, the use of crash reduction factors, and safety software. The chapter also discussed various methods of predicting crashes and modeling techniques used for developing these models in past studies. An overview of methods for CRFs, along with their drawbacks, was also presented in this chapter.

The current models available for Indiana employed in practice need to be updated due to the following factors:

1. Better data is available through TransCAD.

2. Some data may be irrelevant; other data may not be readily obtained. 3. Current models do not contain enough variables.

There is a need to develop a model that can address these shortcomings in addition to performing the following tasks:

1. The models should be capable of predicting the expected number of crashes in the planning stage when more detailed actual information is not available.

2. The process of crash prediction should become more refined as more data becomes available.

The methodology adopted for safety analysis uses SPFs for various types of facilities and CMFs for various safety improvements. Several research studies have been conducted in the past for developing safety performance functions and crash reduction factors.

3

CONCEPT OF RESEARCH APPROACH

This chapter discusses the concept of the research approach to develop and implement the tool. The essence of the concept is the use of existing safety performance functions (SPF) and crash modification factors (CMFs) to predict crashes. The research approach adopted for addressing the problem objectives is presented in this chapter.

As mentioned earlier in Chapter 2, there exist lacunae in the current procedures adopted for safety analysis of corridor solutions. One of the greatest problems is the potential for a large number of safety solutions. It is not expedient to develop one comprehensive predictive model from regression analysis including an infinite number of variables. It would be impractical from both the user and the research development points of view. The transportation analyst would have to collect and prepare a large amount of data, including some that may possibly be irrelevant to the proposed improvements. As past experience indicates, in spite of having a large amount and wide scope of data, the effects of many road improvements would not be included in the predictive equation because the resources that constrain the amount of data that can be collected are always limited while the need for data grows in proportion to the number of variables included in the equation. To avoid these methodological complications, a more effective method of developing a crash predictive equation that meets the requirements of corridor studies for long-range planning is proposed.

Instead of trying to develop a set of equations with many variables, we propose to use SPFs existing in Indiana supplemented from existing models developed by other states to predict safety for segments and intersections. The results from these developed equations will be then aggregated for corridors, counties, towns, regions, etc. A safety analysis tool for corridor studies will be developed. This task will develop the components of the method for a corridor study, including its manual. It will also test the method by a comparison to real data. This will be then facilitated with TransCAD-based planning tools presently used in Indiana. Since these models have also been calibrated, we therefore need crash data as we also bring crashes to

TransCAD. These crashes will be then assigned to segments and nodes or intersections in TransCAD using the crash data. In this way the planner will be able to compute the number of crashes by dividing the corridor into functional components: road sections (segments) and nodes or intersections for planning perspective. These models then require calibration and validation by using method of calibration for the user defined set of network partitions. The models developed are based on data from different regions. Therefore the differences in regions and the changes in safety over a period of time call for calibration of the SPFs. For example, different parts of the region may experience different weather conditions (e.g., northern and southern California) or topographical conditions (e.g., northern and southern Indiana). In such cases, the planner may want to use calibration factors to consider these differences when predicting future safety in road networks.

Once the base model is processed, then the calibration process will start, as we will be adding calibration in the planning tool.

Finally, the corridor safety analysis tool and TransCAD will be applied to an example corridor project to illustrate the methodology and to further test it. The method will be applied to a recently developed project so all of the needed data are available for testing. This example will be evidence that the developed method is practical. A description of the developed method with its manual, and an example application of the method to an existing Indiana corridor will be provided.

The INDOT 2000-2025 Long-Range Plan (INDOT, 2002) defines the plan development process where a Technical Planning Analysis is the core component that feeds the Indiana long-range plan with engineering-based inputs. Development of a GIS-based method of predicting safety in transportation networks for long and short-term planning is underway in Indiana. As emphasized by Washington et al. (2004), safety should be introduced in all steps of the planning process, starting with incorporating safety into the vision, goals, and objectives, through technical analysis, development of programs, and monitoring of the system. The objective is to integrate safety consideration into the transportation planning process at all

Figure 3.1 Flow Diagram Illustrating Proposed Safety Conscious Technical Planning

levels starting with the Statewide Transportation Improvement Plans (STIP) and followed by consideration of safety objectives in long-range planning (FHWA, 2003). This long range plan of Indiana will be supplemented with the proposed safety-conscious technical planning components as shown in the flow diagram.

Calibrating Safety Performance Functions (SPF) Predicting Future Safety Recent Crash Data

Future Safety Calibrating Travel Demand Model (TDM) Future Alternative Network Predicting Future Volumes Evaluating the Planning Alternative Recent Volumes Current Network Future Volumes

4

REVIEW OF EXISTING SAFETY PERFORMANCE