Sandeep Mudigonda

Derivation and Validation of New Simulation-Based Surrogate Safety Measure

Traffic safety evaluation is one of the most important processes in analyzing transportation systems performance. Traditional methods like statistical models and before-after comparisons have many drawbacks, such as limited time periods, sample size problems, and reporting errors. The advancement of traffic conflict techniques combined with microsimulation offers a potentially innovative way for conducting safety assessment of traffic systems even before safety improvements are implemented. In this paper, simulation-based safety studies are reviewed, and a modified simulation-based surrogate safety measure and a new simulation-based surrogate safety measure that can capture the probability of collisions, as well as the severity of these potential collisions, are proposed. Conceptual and computational logic of the proposed surrogate safety indicators are described in detail. These surrogate safety indices are initially proposed for link-based analysis and should not be used for other purposes, such as intersection safety assessment, without further enhancements, and the use of these indices should be limited to the analysis of linear conflicts. In addition, these link-based indices are extended to be able to conduct aggregate networkwide safety assessments. The proposed indices are validated by means of a well-calibrated traffic simulation model of a section of the New Jersey Turnpike and real accident data from the same section. Preliminary results indicate a strong relationship between the proposed surrogate safety measures and real accident data. Further research is needed to investigate these new surrogate safety indices under different locations and traffic conditions.

Impact of Electronic Toll Collection on Air Pollution Levels: Estimation Using Microscopic Simulation Model of Large-Scale Transportation Network

This paper presents a microscopic simulation-based estimation of the spatiotemporal change in air pollution levels as a result of electronic toll collection (ETC) deployment on the New Jersey Turnpike (NJTPK), a large-scale traffic network. The study includes (a) the disaggregate spatial estimation and analysis of the emissions instead of aggregate systemwide estimations, (b) the use of a vehicle-based and well-calibrated traffic simulation model of NJTPK network in Paramics microscopic simulation software to perform this disaggregate emission estimation, (c) the use of a unique and realistic toll plaza model with a complete mainline model to capture complex mainline–toll plaza interactions, and (d) estimation of short- and long-term impacts of ETC systems. The simulation model is loaded with a recent network-specific data set, which includes origin–destination demand data for 1999 (before ETC deployment) and for 2005 (6 years after ETC deployment) and toll plaza service times obtained from toll plaza videotapes. The MOBILE6.2 mobile source emission model developed by the Environmental Protection Agency is integrated in Paramics. At each time step of the simulation, air pollution levels—namely, CO, HC, NOx, and PM10 emissions—are calculated for each vehicle type on the basis of its speed. The simulation network is used to estimate not only the change in systemwide air pollution levels but also the spatial changes throughout the system. Results show that ETC deployment reduces the overall network air pollution level in the short term; however, in the long term its benefits are not sufficient to compensate for the air pollution increase on the mainline because of annual traffic growth.

Enabling vehicular networking in the MobilityFirst future internet architecture

Vehicular networking, both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I), is an increasingly important usage scenario for future mobile Internet services. Radio technologies such as 3G/4G and WAVE/802.11p now enable vehicles to communicate with each other and connect to the Internet, but there is still the lack of a unifying network protocol architecture for delivery of services across both V2V and V2I modes. The MobilityFirst future Internet architecture, discussed in this paper, is a clean-slate protocol design in which the requirements of untethered nodes and dynamically formed networks are considered from the ground-up, making it particularly suitable for vehicular applications. Here we describe the vehicular networking specific features and protocol design details of the architecture and present evaluation results on performance and scalability.

Development and calibration of an integrated freeway and toll plaza model for New Jersey Turnpike using paramics microscopic simulation tool

The paper describes the development and calibration efforts of an integrated freeway and toll plaza model of the New Jersey Turnpike (NJTPK) using paramics microscopic simulation software. The model is calibrated using the detailed E-ZPass data of individual vehicles. The efficiency of the NJTPK is highly related to the toll plaza operations. However, paramics cannot model toll plazas by default. It is also demonstrated in this paper that the application programming interface (API) of paramics is required to model the complex vehicle movements and decisions at toll plazas. The developed simulation model is an invaluable tool in many analyses such as evaluation of traveler information systems, incident management strategies, the effect of infrastructural changes, and the impact of congestion pricing.

Evaluation of a Methodology for Scalable Dynamic Vehicular Ad Hoc Networks in a Well-Calibrated Test Bed for Vehicular Mobility

Vehicles that communicate with one another (connected vehicles) are becoming more ubiquitous each year, and the increase in mobile computing is allowing the proliferation of possible applications for connected vehicles. Many of these applications require vehicles to be connected continuously to the communication infrastructure. This connection could result in congestion of the communication network. This study evaluates a novel dynamic grouping methodology that combines vehicle-to-vehicle and vehicle-to-infrastructure communication schemes for optimal use of the communication infrastructure. The methodology for dynamic grouping of instrumented vehicles was implemented in a realistic and well-calibrated microscopic traffic simulation for application to the collection of sensor data. A 66% to 91% reduction in the load on the communication infrastructure was achieved by dynamic grouping for systematic aggregation of vehicular information. Use of the maximum bandwidth showed that name–address mapping was scalable. The dynamic grouping methodology is thus scalable and achieves a negligible loss of data quality compared with that in a scenario in which each vehicle connects to the communication infrastructure independently. The scalability was shown by the generation of response surfaces for the load on communication channels for different market penetration and communication ranges. The quality of the data was validated by use of the reported speed and estimated travel times over the network. On average, the error in speed was 5.5% to 8%, with far less bandwidth used with the dynamic grouping approach. The travel time along different paths was shown to be within 5% under regular conditions and within 10% under conditions of nonrecurrent congestion.

ASSIST-ME: Postprocessing Tool for Transportation Planning Model Output

This paper presents Advanced Software for Statewide Integrated Sustainable Transportation System Monitoring and Evaluation (ASSIST-ME), an application for visualizing and analyzing the output of transportation planning models in a geographic information system environment. ASSIST-ME was developed on a customized version of the ArcGIS 9.2 Developer Engine in the Microsoft .NET Framework. The tool is built on a flexible framework that allows for adoption of any traditional transportation planning model, as demonstrated with the output of two major transportation planning models on different software platforms: the New York Best Practice Model, running in TransCAD, and the North Jersey Regional Transportation Model–Enhanced, running in CUBE. ASSIST-ME allows agencies and planners to easily work with transportation planning model output, analysis of which is often time-consuming and requires extensive training. It offers four key functionalities: data visualization, demand analysis, path analysis, and benefit–cost analysis. Data visualization and demand analysis enable the user to work easily with direct model output; the custom path and cost analysis tools support analyses beyond those possible with other software packages. The benefit–cost analysis functions utilize the latest quantification–monetization approaches employed in research and by government agencies and require no external applications or procedures. This process can be used for any planning scenario, but ASSIST-ME also allows for customization to modify input data or analysis procedures according to the users needs. ASSIST-ME incorporates data visualization, data analysis, and output reporting functionalities in a single user-friendly setting that requires minimal training or knowledge of the models themselves.

Simple Approach to Estimating Changes in Toll Plaza Delays

Toll plazas are important components of the road infrastructure, especially on urban highways. They can have adverse capacity and safety impacts on traffic. However, the plazas serve an important purpose, namely, revenue generation for highway agencies. Various traffic management and electronic toll collection strategies, including regular and high-speed E-ZPass and time-of-day pricing, are also implemented as part of toll plaza operations to change traffic supply and demand characteristics and improve networkwide level of service. In recent years, because of the increasing need to better assess the impact of toll plazas combined with these various traffic management strategies, customized or off-the-shelf microsimulation and macrosimulation models of toll plazas have been developed. This study reviews the literature on both approaches. Then a customized microscopic toll plaza model developed as an integrated part of PARAMICS microsimulation is compared with a relatively simple macroscopic model. This kind of macroscopic model, which can estimate toll plaza delays, is needed because it is extremely difficult and expensive to calibrate and implement microsimulation models when projects have severe budget and time constraints. Several New Jersey Turnpike toll plazas that were well validated and calibrated are used in the comparison. A sensitivity analysis is conducted with various other toll plazas to ensure the validity of the macroscopic model, especially for cases in which demand is reduced because of a real-time traffic management strategy. Results indicate that the macroscopic method is comparable (within average error 2.6% to 6.4%) with the PARAMICS model when sufficient care is taken in selecting macroscopic and microscopic model parameters consistently.

Evaluating highway capacity investments using a geographic information systems-based tool: Trip-based full marginal cost approach

This paper presents an interactive computer tool based on geographic information systems (GIS) and developed for the evaluation and analysis of full marginal costs (FMC) of highway transportation in New Jersey. The first part of the paper is concerned with the implementation of a trip-based FMC estimation methodology in the GIS environment. A constrained k-shortest-path algorithm is proposed to estimate the trip-based FMC of a trip along not only the shortest travel time path but also a set of feasible paths between each origin-destination (O-D) pair that can be attractive to the travelers. The second part of the paper deals with estimation of various transportation cost categories, including vehicle operation, congestion, accident, air pollution, noise, and maintenance. This estimation uses New Jersey-specific data. The methodology is then implemented in ArcGIS, with the use of Visual Basic and C-programming language. The developed GIS-based tool not only estimates FMC between a selected O-D pair but also compares complete and partial networks to assess short-term impacts of infrastructure investments on the FMC. The proposed tool will help planners to calculate true trip costs between different O-D pairs for various user-defined scenarios of various demand and supply changes.

Incident Detection Through Twitter

Traffic incident information is disseminated via Twitter from various types of accounts. It is more common to find active or transitive verbs and adverbs in tweets from personal accounts because individuals report personal experiences (e.g., “just saw an accident”). Tweets from an organization or agency [e.g., 511 (a telephone hotline for transportation information widely used in the United States and Canada), departments of transportation] are more structured and commonly include nouns and past participles (e.g., “one lane blocked”). Organization accounts mostly provide incident location, type, severity, and so on, whereas personal tweets do not usually provide such details. However, an agency tweets about an incident usually after the incident management (IM) officials have already been notified. Because of this timing, a personal tweet is more likely to carry useful “new” information for IM purposes. This study investigated the detection of traffic incidents through Twitter feeds by using these differences in structure and information content found in organization and personal social media accounts. Tweets collected via the Twitter public application programming interface were manually coded and treated separately as either personal or organizational, and the “dictionaries” used to perform relevancy classification were derived separately. Combinations of dictionaries (i.e., personal only, organizational only, personal and organizational) were used for “term frequency–inverse document frequency” and naïve Bayesian analysis. It was shown that analysis specific to account types helped achieve better accuracy in classification for targeting relevant tweets. Therefore, account-specific analysis should be considered for more efficient and effective event detection for IM purposes.

Quantifying Transportation Benefits of Transit-Oriented Development in New Jersey

The cost of transportation plays an important role in residential location choice. Reducing transportation costs not only benefits the user but also improves the performance of the system as a whole. A direct impact of transit-oriented development (TOD) is the change in out-of-pocket costs for users, as well as the changes in costs of externalities and agency benefits. The prime mover for these changes is the shift in population when a TOD is built near train stations and the induced mode shifts from driving to transit. In this study several sites throughout New Jersey were evaluated to determine the cost of driving versus the cost of using rail transit to major employment destinations in New Jersey and New York City. Driving costs were composed of vehicle operating costs (including fuel, wear and tear, and depreciation), value of time based on the highway travel time from origin to destination, parking cost, and cost of externalities such as air and noise pollution, road maintenance, and accidents. Transit costs were composed of fares, parking costs, and values of travel time, waiting time, and transfer time. The likely changes in population resulting from the TOD were used to estimate changes in highway and transit trips. The costs were compared to derive the net benefit for transportation system users as a result of the TOD. Generally, TOD results in financial benefits to the user and the transportation system.