Andrea R. Bill

Modeling Reservation-Based Autonomous Intersection Control in VISSIM

The use of autonomous vehicles is attracting more and more attention as a promising approach to improving both highway safety and efficiency. Most previous studies on autonomous intersection management relied heavily on custom-built simulation tools to implement and evaluate their control algorithms, but the use of nonstandard simulation platforms makes the comparison of systems almost impossible. Furthermore, without support from standard simulation platforms, reliable and trustworthy simulation results are hard to obtain. In this context, this paper explores a way to model autonomous intersections through the use of VISSIM, a standard microscopic simulation platform. A reservation-based intersection control system named autonomous control of urban traffic (ACUTA) was introduced and implemented in VISSIM through the use of VISSIMs external driver model. The operational and safety performance characteristics of ACUTA were evaluated with VISSIMs easy-to-use evaluation tools. In comparison with the results obtained with optimized signalized control, significantly reduced delays, along with a higher intersection capacity and lower volume-to-capacity ratios under various traffic demand conditions, resulted from the use of ACUTA. The safety performance of ACUTA was evaluated by use of the surrogate safety measure model, and few conflicts between vehicles within the intersection were detected. Moreover, the key steps and elements for implementation of ACUTA in VISSIM were introduced. These steps and elements can be useful for other researchers and practitioners implementing their autonomous intersection control algorithms in a standard simulation platform. By use of a standard simulation platform, the performance characteristics of autonomous intersection control algorithms can eventually be compared.

Automated Identification and Extraction of Horizontal Curve Information from Geographic Information System Roadway Maps

Roadway horizontal alignment has long been recognized as one of the most significant contributing factors to lane departure crashes. Knowledge of the location and geometric information of horizontal curves can greatly facilitate the development of appropriate countermeasures. When curve information is unavailable, obtaining curve data in a cost-effective way is of great interest to practitioners and researchers. To date, many approaches have been developed to extract curve information from commercial satellite imagery, Global Positioning System survey data, laser-scanning data, and AutoCAD digital maps. As geographic information system (GIS) roadway maps become more accessible and more widely used, they become another cost-effective source for extraction of curve data. This paper presents a fully automated method for the extraction of horizontal curve data from GIS roadway maps. A specific curve data–extraction algorithm was developed and implemented as a customized add-in tool in ArcMap. With this tool, horizontal curves could be automatically identified from GIS roadway maps. The length, radius, and central angle of the curves were also computed automatically. The only input parameter of the proposed algorithm was calibrated to have the least curve identification errors. Finally, algorithm validation was conducted through a comparison of the algorithm-extracted curve data with the ground truth curve data for 76 curves that were obtained from Bing aerial maps. The validation results indicated that the proposed algorithm was very effective and that it identified completely 96.7% of curves and computed accurately their geometric information.

Development of Knowledge Tables and Learning Outcomes for an Introductory Course in Transportation Engineering

Many decisions about the content of an introductory transportation engineering course are complicated by a wide range of topics and skills to be presented in a limited amount of time. The information presented in this paper was compiled by a working group of educators who represented universities of varying sizes and geographic areas. This working group was charged with developing core concepts and associated knowledge tables for the introductory transportation course for the following core concept areas: traffic operations, transportation planning, geometric design, transportation finance, transportation economics, traffic safety, and transit and nonmotorized transport. Instructors can weave the knowledge tables together by explaining the ways of being of a transportation professional and the course learning outcomes. A key focus of the working groups efforts was to provide more guidance to instructors on core content versus optional content. The intent of the working group was not to dictate what exactly should be taught in a course. The group therefore created more content than could fit into a typical semester-long course so that instructors would have flexibility. Some content should be viewed as more critical to the transportation profession than other material, and the working group will prioritize it accordingly. The objective of this paper is to demonstrate the work that has been completed and to get feedback from industry partners and other academic professionals about the curriculum. The efforts of the pilot studies over the next year will help determine the amount of time needed to cover the information in the knowledge tables.

Safety Evaluation of Horizontal Curves on Rural Undivided Roads

The objective of this research was to develop prediction models for total crashes and fatal or injury crashes for rural horizontal curves on undivided roads, with a focus on three distinct aspects. The first was an emphasis on assembling a large, high-quality data set. Crash prediction models were developed by using a data set of 11,427 rural horizontal curves on Wisconsin state trunk network roads with more than 13 parameters and four distinct types of crash data sets. The second focus area was to use regression tree analysis in creating a simple model of horizontal curve safety aimed at practitioners of systemic road safety management and creating subsets of data that warranted further analysis. Regression tree results identified the curve radius of approximately 2,500 ft as a significant point below which there is a marked increase in crashes on horizontal curves. The third focus area was to research the effect on horizontal curve crash prediction models of different selection criteria to assemble the crash data set. Models (total and fatal or injury) based on a crash data set with and without crashes in the proximity of intersections were compared. The results show that when crashes on horizontal curves are selected where crash report forms indicate the presence of a horizontal curve, crashes that occur in the proximity of intersections do not affect model results significantly; therefore, the inclusion of such crashes would increase the size of the data set and benefit model development.

Comprehensive Safety Evaluation of Roundabouts in Wisconsin

The modern roundabouts are proliferating rapidly in the United States and Wisconsin is no exception to this trend. The growing number of U.S.-specific research has played an important role in their acceptance in the United States. However, as new data become available, there is a need to continue the research to better understand roundabout safety in the United States. Moreover, the growing data sets also warrant the creation of localized models to better reflect ground conditions. The objectives of this research were to continue and enhance research efforts on the roundabout safety using current data sets. The aim was to analyze roundabout crash trend and patterns to further evaluate their performance under varying situations and develop crash prediction models. The results showed interesting observations as far as crash patterns at roundabouts were concerned. Even though crash severity was reduced, it is not the same situation for crash frequencies. Further research is required to assess the safety effectiveness of roundabouts in Wisconsin. The crash prediction models from this research would help in quantifying roundabout safety, especially when selecting which locations to be converted to roundabouts.

Injury outcomes and costs for cross-median and median barrier crashes

INTRODUCTION The objective of this research was to quantify the injury outcomes and develop reliable and comprehensive injury costs for cross-median crashes (CMC) and median barrier crashes (MBC). METHOD A three-step methodology was developed to quantify the crash costs for each crash severity and type. All CMC and MBC between 2001 and 2007 in Wisconsin were identified and used in this analysis. The Wisconsin CODES database provided comprehensive injury costs based on the injury types and severities suffered by participants in study crashes. RESULTS As expected, multi-vehicle CMC result in more total injuries and more severe injuries than single-vehicle CMC. Injury costs for the same injury level on KABCO scale are different for different crash types. Injury costs for concrete MBC are 33% to 50% less than those of multi-vehicle CMC, while the injury costs of concrete MBC for lower severities (B and C) are similar to those of single-vehicle CMC for the same severities; but for incapacitating injuries the costs are 30% less. As expected, concrete MBC result in lower severities than CMC. The costs, by crash severity, vary significantly between different crash types. Concrete median barrier injury crashes are roughly 20% of multi-vehicle CMC costs and 50% of single-vehicle CMC costs. CONCLUSIONS Results indicate that using one set of crash costs for all crash types biases any evaluation. Therefore, it is recommended that crash-type-specific costs be used in applications such as development of median barrier warrant where specific types of crashes are considered (CMC and MBC). IMPACT ON INDUSTRY Using crash specific costs can lead to a more realistic benefit-cost analysis and enable better decision-making.

Spatial effectiveness of speed feedback signs

Speed feedback signs (SFS), also known as dynamic speed displays, provide drivers with feedback about their speed in relationship to the posted speed limit. When appropriately complemented with police enforcement, SFS can be an effective method for reducing speeds at a desired location. However, as reported in the literature, effectiveness of SFS is limited not only in regard to time after the deployment but also for distance. Therefore, a need exists to understand how far upstream and downstream of the SFS speed reductions are maintained. Through a unique data collection methodology, researchers obtained trajectories of free-flowing vehicles that approached an SFS, as well as trajectories of vehicles receding from the SFS. Trajectory data were used by researchers to determine the locations at which drivers willing to reduce their speed when approaching the SFS actually started the reduction. Downstream of the SFS, the distance at which drivers started increasing their speed after complying with the sign was also determined. Results showed the feasibility of determining the spatial effectiveness of SFS. By using the methods as presented, speed enforcement personnel can understand how drivers in an area of interest react to SFS and therefore can determine the best locations for SFS as well as the number of SFS that need to be deployed to achieve a speed reduction over a segment of road.

Sustainability effects of next-generation intersection control for autonomous vehicles

AbstractTransportation sustainability is adversely affected by recurring traffic congestions, especially at urban intersections. Frequent vehicle deceleration and acceleration caused by stop-and-go behaviours at intersections due to congestion adversely impacts energy consumption and ambient air quality. Availability of the maturing vehicle technologies such as autonomous vehicles and Vehicle-To-Vehicle (V2V) / Vehicle-To-Infrastructure (V2I) communications provides technical feasibility to develop solutions that can reduce vehicle stops at intersections, hence enhance the sustainability of intersections. This paper presents a next-generation intersection control system for autonomous vehicles, which is named ACUTA. ACUTA employs an enhanced reservation-based control algorithm that controls autonomous vehicles’ passing sequence at an intersection. Particularly, the intersection is divided into n-by-n tiles. An intersection controller reserves certain time-space for each vehicle, and assures no conflict ex...

Automated extraction of horizontal curve information for low-volume roads

Rates of fatal and injury crashes on low-volume roads are much higher than those on higher-volume roads. A large proportion of crashes on low-volume roads are roadway departure crashes. Research has shown that roadway departure crashes are 1.5 to 4 times more likely at curves than on tangent sections. Therefore, knowledge of where horizontal curves are located and their geometric characteristics is key to addressing safety issues for low-volume roads. In the United States, although many states have a horizontal curve database for their state routes and Interstate highways, most states do not have such a database for non-state-owned roads, especially for low-volume rural roads, because of the lack of funds for additional data collection. A novel approach is presented that can extract curve data for both state and local roads in an accurate, cost-effective, and time-efficient manner without additional data collection. An ArcGIS add-in tool, CurveFinder, was developed by the authors previously to automatically identify horizontal curves from a selected roadway layer, classify curves, compute curve geometrics, and, finally, create a geographic information system for curve layers. CurveFinder was updated to incorporate compatibility with curve elements of FHWAs Model Inventory of Roadway Elements. Case studies are used to demonstrate the application of the updated CurveFinder on rural low-volume roads in different states and the lessons learned. Results show that none of the control curves were 100% missed by CurveFinder. False identification rates were also low. Both results validate CurveFinder. Causes of the few errors in the extracted curve data are identified, and potential solutions are explored.

Evaluation of Roundabout-Related Single-Vehicle Crashes

Roundabouts reduce fatal and injury crashes at intersections when converted from other intersection control types. In Wisconsin, roundabouts have been linked to a 38% decrease in fatal and injury crashes. Part of this reduction can be attributed to crash types that result in the mitigation of more serious injuries. However, the reduction comes at a cost because other crash types, such as single-vehicle collisions, may increase. Six years of crash data on 53 roundabouts in Wisconsin were examined for crash causes and geometric characteristics that affected single-vehicle crashes. Weather and impaired driving, particularly by younger drivers, were primary causes for more than half of all single-vehicle crashes at the study roundabouts. Younger drivers (18 to 24 years of age) were involved in a significantly higher proportion of single-vehicle crashes than the total proportion of licensed drivers in that age group. Younger drivers were involved in approximately one-third of all crashes that involved impaired driving and in two-thirds of all speed-related single-vehicle crashes. A negative binomial model was constructed to estimate run-off-road crashes at approaches. It was found that roundabouts with higher approach speeds and higher traffic volumes experienced more run-off-road crashes. Landscaped central islands experienced significantly lower frequencies of run-off-road crashes.