84 research outputs found
Statewide Heavy-Truck Crash Assessment -- tech transfer summary
In 2010, 16.5 percent of all fatal vehicle crashes in Iowa involved large trucks compared to the national average of 7.8 percent. Only about 16 percent of these fatalities involved the occupants of the heavy vehicles, meaning that a majority of the fatalities in fatal crashes involve non-heavy-truck occupants. These statistics demonstrate the severe nature of heavy-truck crashes and underscore the serious impact that these crashes can have on the traveling public. These statistics also indicate Iowa may have a disproportionately higher safety risk compared to the nation with respect to heavy-truck safety. Several national studies, and a few statewide studies, have investigated large-truck crashes; however, no rigorous analysis of heavy-truck crashes has been conducted for Iowa. The objective of this study was to investigate and identify the causes, locations, and other factors related to heavy-truck crashes in Iowa with the goal of reducing crashes and promoting safety. To achieve this objective, this study used the most current statewide data of heavy-truck crashes in Iowa. This study also attempted to assess crash experience with respect to length of commercial driver’s license (CDL) licensure using the most recent five years of CDL data linked to the before mentioned crash data. In addition, this study used inspection and citation data from the Iowa Department of Transportation (DOT) Motor Vehicle Division and Iowa State Patrol to investigate the relationship between enforcement activities and crash experience
Safety Ramifications of A Change in Pedestrian Crosswalk Law: A Case Study of Oregon, USA
Pedestrians are some of the most vulnerable road users as they are not protected by safety devices, and must also share the road with vehicles traveling at dangerous speeds, particularly during road crossings. In 2011, the state of Oregon changed their traffic laws to be more accommodating to pedestrians by giving right of way to pedestrians using a crosswalk, regardless if whether the crosswalk is marked or unmarked. This paper estimates a panel logit model to evaluate the efficacy of the law in preventing pedestrian fatalities. Pedestrian fatalities are shown to decrease over time, with smaller likelihood of a fatality outcome in the years following the change in pedestrian crossing laws. To the authors’ knowledge, it is the first time panel logit models have been used in evaluating pedestrian safety. Results indicate that panel logit models are an alternative to using Box-Tiao intervention models to analyze the long term effects of policy changes, as they allow for the consideration of crash exposure factors as well as temporal effects
Ridesharing, Active Travel Behavior, and Personal Health: Implications for Shared Autonomous Vehicles
An Assessment of Traffic Safety in Urban Deer Herd Management Zones in Iowa
Many states are striving to keep their deer population to a sustainable and controllable level while maximizing public safety. In Iowa, measures to control the deer population include annual deer hunts and special deer herd management plans in urban areas. While these plans may reduce the deer population, traffic safety in these areas has not been fully assessed. Using deer population data from the Iowa Department of Natural Resources and data on deer-vehicle crashes and deer carcass removals from the Iowa Department of Transportation, the authors examined the relationship between deer-vehicle collisions, deer density, and land use in three urban areas in Iowa that have deer management plans in place (Cedar Rapids, Dubuque, and Iowa City) over the period 2002 to 2007. First, a comparison of deer-vehicle crash counts and deer carcass removal counts was conducted at the county level. Further, the authors estimated econometric models to investigate the factors that influence the frequency and severity of deer-vehicle crashes in these zones. Overall, the number of deer carcasses removed on the primary roads in these counties was greater than the number of reported deervehicle crashes on those roads. These differences can be attributed to a number of reasons, including variability in data reporting and data collection practices. In addition, high rates of underreporting of crashes were found on major routes that carry high volumes of traffic. This study also showed that multiple factors affect deer-vehicle crashes and corresponding injury outcomes in urban management zones. The identified roadway and non-roadway factors could be useful for identifying locations on the transportation system that significantly impact deer species and safety and for determining appropriate countermeasures for mitigation. Efforts to reduce deer density adjacent to roads and developed land and to provide wider shoulders on undivided roads are recommended. Improving the consistency and accuracy of deer carcass and deer-vehicle collision data collection methods and practices is also desirable
Estimating Elasticities for Multi-Modal Public Transport Demand: A Time Series Approach
Research on the demand side of public transportation systems with the use of time series data frequently shows conflicting results with respect to fare elasticities and the factors affecting it. In this analysis we complement prior research by developing seemingly unrelated regression equation models with monthly data for a city served by three different modes of public transportation. The results indicate that, as expected, urban public transport demand in Athens, Greece, is inelastic with respect to fares but, surprisingly, highly inelastic with respect to automobile fuel cost. Further, different transit modes have significantly different fare elasticities, a finding with important practical implications
Forecasting transportation infrastructure impacts of renewable energy industry using neural networks
Iowa is a state rich in renewable energy resources, especially biomass. The successful development of renewable energy industry in Iowa is concomitant with increase in freight traffic and is likely to have significant impacts on transportation infrastructure condition and increased maintenance expenses for the state and local governments. The primary goal of this paper is to investigate the feasibility of employing the Neural Networks (NN) methodology to forecast the impacts of Iowa's biofuels and wind power industries on Iowa's secondary and local road condition and maintenance-related costs in a panel data framework. The data for this study were obtained from a number of sources and for a total of 24 counties in clusters in Northern, Western, and Southern Iowa over a period of ten years. Back-Propagation NN (BPNN) using a Quasi-Newton secondorder training algorithm was chosen for this study owing to its very fast convergence properties. Since the size of the training set is relatively small, ensembles of well-trained NNs were formed to achieve significant improvements in generalization performance. The developed NN forecasting models could identify the presence of biofuel plants and wind farms as well as large-truck traffic as the most sensitive inputs influencing pavement condition and granular and blading maintenance costs. Pavement deterioration resulting from traffic loads was found to be associated with the presence of both biofuel plants and wind farms. The developed NN forecasting models can be useful in identifying and properly evaluating future transportation infrastructure impacts resulting from the renewable energy industry development and thus help Iowa maintain its competitive edge in the rapidly developing bioeconomy
Motorcycle conspicuity: what factors have the greatest impact
The objective of this project was to determine the effect of headlight configuration (daytime running lights, high beam, modulating) and rider color (bright yellow, blue denim, and black torso and helmet) on the conspicuity of a motorcycle to a driver of a passenger vehicle in a simulated environment. To achieve this, 36 participants completed three drives on a National Advanced Driving Simulator (NADS)-2 driving simulator. During two of the drives, participants were presented with six oncoming motorcycles and three leading parked motorcycles, each with a different combination of rider color and headlight configuration. Each of the nine motorcycles was present in either the urban or rural driving environment. Participants indicated when each motorcycle was first visible to them by pressing a button on the steering wheel of the driving simulator. The detection distances from the motorcycles to the participant vehicles were then recorded. Participants were within one of two groups: younger drivers (25 to 55) or older drivers (65 and older). This research applied repeated measures analysis of variance to investigate the impact of headlight configurations and rider color on motorcycle conspicuity in urban and rural environments. The researchers found that oncoming motorcycles with modulating headlights were detected at the greatest distance compared to motorcycles with high beam or daytime running lights. Participant ability to detect an oncoming motorcycle was also significantly influenced by the combination of headlight configurations with black or bright yellow rider colors. Leading motorcycles in urban environments were detected at a greater distance compared to those in rural environments. Leading motorcycles with riders having bright yellow clothing and helmet were detected at the greatest distance, followed by motorcycles with riders having blue denim and black rider colors. A significant interaction effect among the driving environment, rider color, and age group was also found for the detection distance of leading motorcycles
Public Acceptance of INDOT’s Traffic Engineering Treatments and Services
As a public agency, interacting with and understanding the public’s perspective regarding agency activities is an important endeavor for the Indiana Department of Transportation (INDOT). Although INDOT conducts a biennial customer satisfaction survey, it is occasionally necessary to capture public perception regarding more specific aspects of INDOT’s activities. In particular, INDOT needs an effective way to measure and track public opinions and awareness or understanding of a select set of its traffic engineering practices. To evaluate public acceptance of specific INDOT traffic engineering activities, a survey consisting of 1,000 adults residing within the State of Indiana was conducted. The survey population was representative in terms of age and gender of the state as of the 2010 U.S. Census. The survey was administered during the months of July and August 2020. Public awareness regarding emerging treatments not currently implemented in Indiana is low and opposition to the same new technologies is prominent. Older or female drivers are less likely to be aware of emerging treatments, and older drivers are more likely to oppose potential implementation of these treatments. Although roundabouts are commonplace in Indiana, multi-lane roundabouts remain controversial among the public. Regarding maintenance and protection of traffic during work zones and considering full or partial roadway closure, public preference is for partial closure; this preference is stronger in rural areas. The public equally agrees and disagrees that INDOT minimizes construction related traffic delays. Approximately 76% of Indiana drivers believe themselves to above average drivers, while an additional 23% believe themselves to be average. Driver perceptions of average highway speeds speed are not aligned with posted speed limit as the perceived average speed on Indiana’s urban freeways and rural and urban state highways is considerably higher than the actual speed limit
Best Practices for Maximizing Driver Attention to Work Zone Warning Signs
Studies have shown that rear-end crashes in the advance warning area for a work zone are the most common type of work zone crashes. Driver inattention (or distraction) is reported as the most common issue and a major contributing factor to those types of crashes. As such, there is a need to identify the technologies that are successful in alerting drivers when approaching work zones
Economic Development Impact of Corridor Improvements
In recent years, the Indiana Department of Transportation (DOT) and other state transportation agencies have increasingly implemented non-capacity expansion projects or strategies due to their benefits in improving flow, safety, and reducing delay in the transportation network at low capital, operations, and maintenance costs. The quantification of the benefits of these strategies has also become very important due to increasingly challenging local and regional fiscal conditions. With this in mind, this project developed a framework and a tool for the evaluation of economic development impacts of corridor improvements at the sketch-level of planning. The resulting framework and tool, called “Tool for Operations – Economic Impact Analysis” (TOPS-EIA), is based on a framework and tool from the Federal Highway Administration (FHWA) called Tool for Operations Benefit Cost Analysis (TOPS-BC). TOPS-EIA takes the expected impacts of each strategy on corridor performance and translates them into business cost savings and economic development impacts through a set of statewide economic multipliers. TOPS-EIA is subdivided into 4 modules: arterial signal coordination (ASC) strategies, traffic incident management (TIM) strategies, work zone management (WZM) strategies, and access management (AM) strategies. Additionally, a qualitative tool for road diet (RD) strategies was developed. To demonstrate TOPS-EIA, two case studies of ASC strategies were conducted. The results showed that this type of strategies could provide not only significant user cost savings, but also economic development impacts, expressed as gross regional product, job-years, and real personal income. The proposed methodology and tool can assist DOTs, Metropolitan and Rural Planning Organizations (MPOs and RPOs) in assessing the benefits of non-capacity expansion projects at the early and middle stage planning processes and, therefore, contribute to better-informed decisions
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