Venkata R Duddu

Traffic analysis zone level crash estimation models based on land use characteristics

The objective of this paper is to develop crash estimation models at traffic analysis zone (TAZ) level as a function of land use characteristics. Crash data and land use data for the City of Charlotte, Mecklenburg County, North Carolina were used to illustrate the development of TAZ level crash estimation models. Negative binomial count models (with log-link) were developed as data was observed to be over-dispersed. Demographic/socio-economic characteristics such as population, the number of household units and employment, traffic indicators such as trip productions and attractions, and, on-network characteristics such as center-lane miles by speed limit were observed to be correlated to land use characteristics, and, hence were not considered in the development of TAZ level crash estimation models. Urban residential commercial, rural district and mixed use district land use variables were observed to be correlated to other land use variables and were also not considered in the development of the models. Results obtained indicate that land use characteristics such as mixed use development, urban residential, single-family residential, multi-family residential, business and, office district are strongly associated and play a statistically significant role in estimating TAZ level crashes. The coefficient for single-family residential area was observed to be negative, indicating a decrease in the number of crashes with an increase in single-family residential area. Models were also developed to estimate these crashes by severity (injury and property damage only crashes). The outcomes can be used in safety conscious planning, land use decisions, long range transportation plans, and, to proactively apply safety treatments in high risk TAZs.

Principle of Demographic Gravitation to Estimate Annual Average Daily Traffic: Comparison of Statistical and Neural Network Models

This paper focuses on the application of the principle of demographic gravitation to estimate link-level annual average daily traffic (AADT) based on land-use characteristics. According to the principle, the effect of a variable on AADT of a link decreases with an increase in distance from the link. The spatial variations in land-use characteristics were captured and integrated for each study link using the principle of demographic gravitation. The captured land-use characteristics and on-network characteristics were used as independent variables. Traffic count data available from the permanent count stations in the city of Charlotte, North Carolina, were used as the dependent variable to develop statistical and neural network models. Negative binomial count statistical models (with log-link) were developed as data were observed to be over-dispersed while neural network models were developed based on a multilayered, feed-forward, back-propagation design for supervised learning. The results obtained indicate that statistical and neural network models ensured significantly lower errors when compared to outputs from traditional four-step method used by regional modelers. Overall, the neural network model yielded better results in estimating AADT than any other approach considered in this research. The neural network approach can be particularly suitable for their better predictive capability, whereas the statistical models could be used for mathematical formulation or understanding the role of explanatory variables in estimating AADT.

Identifying Spatial Gaps in Transit Accessibility to Maximize Market Potential

The focus of this paper is (1) to explore features available in commercial Geographic Information Systems (GIS) software and estimate accessibility index as a function of potential captive riders for each transit stop, and, (2) identify spatial gaps based on accessibility index to provide improved public transportation systems that maximizes market potential. Potential captive riders are identified within a pre-defined accessible walking distance or walking time (0.25 miles or 5 minutes) from each transit stop in the City of Charlotte, North Carolina. These riders comprise unemployed, household population with 0 or 1 automobiles, population by age group, low income population (<

Examining Injury Severity of Not-At-Fault Drivers in Two-Vehicle Crashes

25,000), and ethnicity. Results from statistical analysis conducted considering transit ridership and estimated accessibility index show that market potential can be maximized by selecting transit stop locations with high accessibility index or in locations with high accessibility index. Therefore, the methodology and estimated accessibility index to identify spatial gaps helps expand transit area coverage, identify new routes and transit stops.

Buses as Probe Vehicles for Travel Time Data Collection on Urban Arterials

The focus of this paper is to examine the injury severity of not-at-fault drivers in two-vehicle crashes. North Carolina crash data collected from 2009 to 2013 were used for the analysis. Ordered probit model was initially chosen because of the ordinal nature of the dependent variable (injury severity of the driver not at fault). However, the data failed to obey the proportional odds assumption accompanied with the ordered probit model. Therefore, a partial proportional model was fitted for two-vehicle crashes. Compared with the physical condition of at-fault drivers, the physical condition of not-at-fault drivers had a greater effect on the severity of injury to the not-at-fault drivers. Exceeding the speed limit, aggressive or reckless driving, and going the wrong way are the three traffic rule violations of at-fault drivers that are more likely to result in severe injuries to not-at-fault drivers than disregarding traffic signs, signals, and markings. Similarly, a crash involving an at-fault driver with violations of two and three traffic rules is 1.68 and 2.86 times likely to result in severe injuries to not-at-fault drivers compared with a crash involving an at-fault driver with only one traffic rule violation. Motorcyclists are observed to be at highest risk with the odds of severe injury to motorcyclists who are not at fault. Crashes with female at-fault drivers are less likely to result in severe injury to the not-at-fault drivers. Female drivers are also more likely to be severely injured when they are not at fault.

Illustrating the Monetary Impact of Transportation Projects/Alternatives using the Values of Travel Time and Travel Time Reliability

Floating car method technologies such as global positioning system (GPS) units or data from private sources such as INRIX are used for travel time data collection on urban streets. Time, man-power, and cost deter (limit) collection and purchase of such data for the entire transportation network. An alternate source of the travel time data is using buses as probe vehicles. This is practically feasible and inexpensive as most buses operating in urban areas are equipped with automatic vehicle location (AVL) units. However, the travel time of buses is generally greater than the travel time of a typical vehicle (car). The use or applicability could only be justified if there is strong correlation between car and bus travel times. This paper, therefore, examines the relationship between car and bus travel time. The role of key influential factors (such as the number of signalized intersections, the number of unsignalized intersections, the number of driveways, the number of bus-stops, traffic volume, the number of lanes and the number of turns made by the bus) on the ratio between the two travel times is also evaluated and examined to assess the use of buses as probe vehicles. Results indicate a moderately strong relationship between car and bus travel time. Variables other than the number of signalized intersections per unit distance, the number of lanes, and traffic volume do not seem to play a statistically significant role on the ratio of car to bus travel time irrespective of time-of-the-day. Models by time-of-the-day, developed to estimate car travel time, could be used if bus travel time, the number of signalized intersections per unit distance, the number of lanes, and traffic volume are known.

Cost of Independent Bicycle and Pedestrian Projects

State agencies, regional agencies, cities, towns, and local municipalities design and maintain transportation systems for the benefit of users by improving mobility, reducing travel time, and enhancing safety. Cost–benefit analysis based on travel time savings and the value of reliability helps these agencies in prioritizing transportation projects or when evaluating transportation alternatives. This paper illustrates the use of monetary values of travel time savings and travel time reliability, computed for the state of North Carolina, to help assess the impact of transportation projects or alternatives. The results obtained indicate that, based on the illustration of the effect and impact of various transportation projects or alternatives, both improved travel time and reliability on roads yield significant monetary benefits. However, from cost–benefit analysis, it is observed that greater benefits can be achieved through improved reliability compared with benefits from a decrease in travel time for a given section of road.

Modeling Link-Level Crash Frequency Using Integrated Geospatial Land Use Data and On-Network Characteristics

State, regional, and local agencies need an established cost estimation method to improve the accuracy of programmed project funds. In particular, accurately estimating the cost of independent bicycle and pedestrian facilities helps improve prioritization, decision making, and the efficient allocation of funds for bicycle and pedestrian projects. The cost estimates vary by category as well as by the construction cost element. Obtaining cost data for an adequate number of projects of each facility type, although important, is challenging because of either the lack of available information or a reluctance in the sharing of information. This paper (a) outlines methods to achieve a statistically significant sampling of cost data for bicycle and pedestrian facilities, (b) addresses challenges associated with collecting the data from various agencies, and (c) examines variations to better understand the estimates of individual construction cost elements. Recommendations pertaining to cost categories and cost elements that can help planners and engineers estimate the costs of independent bicycle and pedestrian projects are discussed.

Assessment of Transportation System Reliability at Link-, Corridor- and Area-level

AbstractThe primary focus of this paper is to develop models to estimate link-level crash frequency using land use data extracted and integrated through the use of a distance gradient method. The o...

Identifying Inaccessible Areas with Potential to Enhance Transit Market

There has been a paradigm shift in focus from intersection-level to corridor-and area-level analysis and performance measures in recent years. The possibility of capturing dynamic and continuous travel time and/or speed data from private sources such as INRIX opens many pragmatic avenues to predict reliability of transportation systems. Travel time reliability (or index or variability) is considered the most viable performance measure for corridor-level analysis though it is not being widely used for transportation planning, project prioritization, and allocation of resources. The definition of reliability as a performance measure and associated thresholds to understand or assess transportation system performance could vary for a link, corridor or an area. These definitions and thresholds to assess reliability need to be clearly established prior to its large scale application. This research aims to fill this gap by computing, comparing, and assessing link-, corridor- and area-level reliability measures. Data for the city of Charlotte, North Carolina was used to compute reliability measures, examine temporal and spatial variations, and illustrate how reliability can be used for transportation planning, prioritization and allocation of resources.