2018 Poster Session

Assessment of the Interception Capacity of Curb Inlets with Channel-Extensions

The TxDOT PCO inlet consists of a main bay and two side extension chambers. Unlike a conventional curb inlet, flow intercepted through an extension does not fall directly into the main bay; instead the extension provides a horizontal channel directing the intercepted flow. The capacity of this horizontal channel may restrict the interception capacity of the inlet. This study uses a full-scale physical model to test the TxDOT PCO inlet with channel extension both on-grade and in a sag. Results showed that the 10-ft PCO inlet is equivalent to a 10-ft conventional inlet on-grade, but these inlets have previously been shown to have capacities less than predicted by FHWA guidelines (HEC-22) under most conditions. The interception of the channel extension in a sag is about 20% of the expected interception based on HEC-22. Therefore, the 10-ft and 15-ft PCO inlets operate at about 58% and 47% of the expected capacity of a conventional inlet of the same length. Designers should be aware that in either on-grade or sag, the PCO-type inlets will not perform as predicted by HEC-22 design equations. See TxDOT Research Project 0-6842 for more information.
Download PDF of poster.

Presenter: Muhammad Ashraf

 

Benefit-Cost Estimate for Skid Resistance Improvements at The Network Level Using Markov Chains

Safety studies has proven that low values of skid resistance increase crash risk. For this reason, transportation agencies have established minimum skid thresholds to screen projects for further testing or skid resistance improvements. However, Benefit-Cost Ratio (BCR) analyses are not conducted to estimate the potential benefit of such minimum thresholds at the network level. The objective of this project is to provide a framework that estimates the BCR at the network level for defined minimum skid thresholds. Three main issues are addressed. First, a skid resistance deterioration model at the network level is proposed. Second, the maintenance costs required to keep skid resistance above a defined skid threshold in the network are estimated. Third, the expected economic benefits of crash reduction at the network level are estimated. Using the proposed methodological framework, a sample of highway sections that comprise 564 lane-miles pf the Austin District is evaluated to demonstrate its applicability, and a curve between the BRC and the minimum skid threshold was established.

Presenter(s): Oscar Galvis, Zhe Han

Comprehensive Indicator Framework for Statewide Automated Vehicle Readiness in Texas

To date, TxDOT discussions on automated vehicle (AV) readiness with the Texas Technology Task Force have centered on physical and digital infrastructure readiness. Because Texas localities€™ social, economic, and system characteristics vary tremendously, the additional notion of community readiness grounds the statewide AV planning conversation in terms of impacts across Texas, ensuring that investment decisions yield observable benefits that sustain growing acceptance of such technologies. The proposed framework utilizes the three complementary pillars of physical infrastructure, digital infrastructure, and community AV readiness. This identifies potential TxDOT investments that simultaneously advance AVs in Texas, leverage synergies with other technologies and solutions, and suit unique communities€™ needs. Though this project demonstrates the framework by making programmatic recommendations regarding a statewide model deployment program, this context-sensitive and analytical framework is applicable to state DOTs for planning for all emerging technologies, not just AVs. See TxDOT Research Project 0-6902 for more information.

Presenter(s): Amy Fong, Kristie Chin, Andrea Gold

Emerging Visualization Technologies: 360 Degree Media and Virtual Reality

3D and 4D visualizations have proven exceptionally valuable for communicating and analyzing complex engineering designs in 3D as well as communicating and analyzing construction sequencing in 4D. There are now several emerging visualization technologies that could prove even more valuable as a way of comprehending complex engineering information: 360 degree media and Virtual Reality. Traditional photos and videos capture only a small portion of the world around them. New lenses, cameras, and special software now allow for modeled and real life 360 degree images and videos that capture everything around them. Virtual Reality (VR) is an emerging technology that allows users to experience 3D models at human scale through a head-mounted display. Users can have varying degrees of control over their movements inside the 3D model in a VR environment. The technology has become robust enough that the mind accepts, to a certain degree, that what a user is seeing is real. (Research sponsored through TxDOT Dallas District IAC.)

Presenter(s): Cameron Schmeits

Estimating Construction Time of a Large Portfolio of Highway Projects During Planning Phases

Time-cost regression modeling provides an alternative approach and quick solution when construction time estimates are required for a large portfolio of diverse projects in various project planning and development phases. Using data from 623 Texas Department of Transportation projects completed between 2003 and 2017 by its Dallas District Office, a time-cost regression model was developed and validated. The developed model was found statistically significant with better quality and prediction power than the widely known Bromilow’s time-cost (BTC) model. The model provides a quick method to estimate construction durations that can be used for state transportation agencies (STAs) in planning and managing a portfolio of diverse projects.

Presenter(s): Junghye Son

Evaluating Long-Term Durability and Performance of Pre-Stressed Concrete Beams with Extensive Surface Cracking

Thumbnail of Savitha Srinivasan posterVolumetric changes in concrete can lead to cracks. Over the last 14 years, unexplained microcracks have been observed very early in the service life of pre-stressed concrete girders throughout the state of Texas. Their presence has led to concerns about the future integrity of the girders, with one of the major concerns being corrosion of pre-stressing strands. A comprehensive study aimed at understanding the effects that these microcracks have on the service life of the girders has been initiated. See TxDOT Research Project 0-6922 for more information.
Download PDF of poster.

Presenter(s): Savitha Srinivasan

First Transparent Noise Barrier in Texas – IH-30 in Dallas

The Texas Department of Transportation commissioned a study to analyze the feasibility and effectiveness of a lightweight transparent noise barrier on Interstate Highway 30, near downtown Dallas, which became the first noise barrier of its kind in the State of Texas. The highway segment in question, an elevated structure next to a creek, had presented noise problems for the adjacent neighborhood ever since its expansion in the early 2000s. The highway carries substantial commuter traffic as well as heavy trucks. The material for the noise barrier needed to be lightweight in order to be supported by the existing bridge structures without having to retrofit them. CTR designed a 10-ft tall transparent acrylic noise barrier to be installed on top of the existing 8-ft concrete wall. Residential sound pressure level tests were performed at various locations before and after the wall was completed. The success of the project, both from the acoustic and aesthetic standpoints, made it the recipient of the TxDOT Environmental Award. See TxDOT Research Project 0-6804 for more information.

Presenter(s): Manuel Trevino, Rob Harrison

Improving Megaregion (MR) Freight Mobility: Impact of Truck Technologies

Megaregions (MRs) will raise freight mileage (FM) as goods are produced, consumed, distributed and exported over the next thirty years. Engines power the modes which move this freight and diesel fuel dominate motive choice, especially in trucking which carries about 70 percent of the freight ton-miles of Texas and the U.S. Diesel exhaust unless treated is extremely unhealthy and U.S Environmental Protection Agency (EPA) rules in 2002, 2007 and 2010 have succeeded in reducing the levels of pollution on a truck ton-mile basis. However, further reductions are required to meet the higher levels of truck vehicle miles of travel (VMT) on MR highway systems. This research will evaluate both the operator and societal costs and benefits from a range of truck design and equipment specifications. A case study of a truck logistical system In Texas will be used to identify changes in freight patterns mitigating higher VMT levels.

Presenter(s): Rob Harrison

Research sponsored through the Cooperative Mobility for Competitive Megaregions (CM2) UTC.

Multimodal Level of Service (MMLOS) Methodologies: Evaluation of the Multimodal Performance of Arterial Corridors

The principal objective of this research is to evaluate the multimodal performance of arterial corridors using currently available Multimodal Level of Service (MMLOS) methodologies. Eight different MMLOS approaches are applied to a case study using an arterial corridor section in Austin, Texas. The methods applied are (1) Highway Capacity Manual, (2) Transit Capacity and Quality of Service Manual, (3) Charlotte’s Urban Streets Design Guide, (4) Pedestrian and Bicycle Environmental Quality indices, (5) Level of Traffic Stress, (6) Bicycle Compatibility Index, (7) Deficiency Index, and (8) Walk Score®, Bike Score®, and Transit Score®. The analysis is focused on the pedestrian, bicycle, and transit assessment. The methodologies are evaluated and contrasted. The paper provides a compressive review of the current state of practice of multimodal evaluation, and recommendations about the most appropriate approaches to assess multimodal performance of arterial corridors. (Research sponsored through HDR Engineering.)

Presenter(s): Natalia Zuniga-Garcia, Randy Machemehl, Heidi Ross

Object Tracking with Low-Res Lidar and Single Camera

Many cars already have safety and convenience functions based on cheap, reliable, and task-specific object detection. Examples include forward warning with dashboard cameras and radar, and parking assistance with ultra-wideband signals. On the other hand, prototype self-driving vehicles rely on expensive and sometimes fragile instrumentation in order to gather broader and more precise information. Software that can maximize the information out of simpler sensors will narrow the gap between demonstration and mass adoption. We are designing object detection and warning applications with medium-resolution LIDAR and single wide-view cameras. Aspects include shape approximation, inferring distance, and handling objects that block your field of view.  See TxDOT Research Project 0-6877 for more information.

Presenter(s): Michael Motro

Optimal Locations of U.S. Charging Stations for Long-Distance Trips by BEVs

Thumbail of Kenneth Perrine's posterDue to environmental and energy challenges, battery electric vehicles (BEVs) are a relevant policy to reduce fuel consumption and emissions. However, a lack of fast recharging infrastructure and limitations on BEV range limit their popularity. There is a need for well-designed charging station network; this paper uses U.S. long-distance travel data to place charging stations to maximize long-distance trip completions. Each scenario assumes a certain number of charging stations from 50 to 250 and an all-electric-range (AER) from 60 to 250 miles (97 to 402 km). The problem is formulated as a mixed integer program, and a modified flow-refueling location model (FRLM) is solved via a branch-and-bound algorithm. Results reveal that the 60-mile-AER percentage varies between 31% and 65%, as one increases station count from 50 stations to 250 stations. At least 100-mile (161 km) range BEVs may be needed, to avoid long-distance-trip issues for the great majority of U.S. households. (Research sponsored through Beijing Institute of Technology International Graduate Exchange Program.)

Presenter(s): Kenneth Perrine

Processing Large-Scale Video Data to Support Transportation Safety, Planning, and Operations: A Flexible Approach to Data Storage and Integration

This research presents a methodology to automatically process the data streams generated by traffic cameras in order to create data sets that can be queried and integrated with other data sources. Artificial intelligence libraries are used to recognize and detect moving objects from traffic videos, and the information is stored into a structured queryable format that enables multiple analyses. We demonstrate the potential of the proposed framework by using automatically processed data in two distinct applications: traffic flow estimation and identification of pedestrian-vehicle conflicts. The vehicular counts produced by the analysis are over 90% accurate, and the technique is capable of identifying turning movements and close encounters between pedestrians and vehicles. (Research sponsored through City of Austin.)

Presenter(s): Venktesh Pandey

Quantifying the Contribution of Various Factors to Household Vehicle Miles of Travel

Household vehicle miles of travel (VMT) is exhibiting a steady growth in post-recession years in the United States and is poised to reach record levels in 2017. With transportation accounting for 27 percent of greenhouse gas emissions, planning professionals are seeking ways to curb vehicular travel to advance sustainable communities. This paper presents a holistic analysis to identify the relative contribution of socio-economic and demographic characteristics, built environment attributes, residential self-selection effects, and social and spatial dependency effects in explaining household VMT production. The modeling framework employs a simultaneous equations model of residential location (density) choice and household VMT production. The analysis is performed using household travel survey data from the New York metropolitan region. Model results showed insignificant spatial dependency effects, with socio-demographic variables explaining 38%, built environment attributes explaining 8.5%, and self-selection effects explaining 5.9% of the total variance in household VMT. (Research sponsored through NYMTC.)

Presenter(s): Abhilash Singh

TNC Trip Types: What They Mean for You and Your Agency

Symposium poster from Robert EvansPrivate transit in the US has evolved over the last decade to include car-sharing services like car2go and Zipcar to ride-hailing services offered by Uber, Lyft, and RideAustin. As these services become more convenient and cost-effective for users, they continue to increase in popularity. However, despite initial studies, there is not yet consensus on why people choose to use TNCs or what their effects on existing transit systems or society at large will be. RideAustin, a non-profit ride-hailing company started in May 2016, represented 50 percent of the market share for the year that Uber and Lyft left the city. This study aims to answer the questions raised by the emergence of TNCs by analyzing trips in the RideAustin dataset to impute trip purposes. Trip purposes, commonly used by traditional transit planners, will facilitate direct comparisons between TNC and traditional transit trips and facilitate planning in the face of uncertainty. (Sponsored through TxDOT IAC 15512.)
Download PDF of poster.

Presenter(s): Robert Evans

Using National Performance Management Research Data Set (NPMRDS) for Corridor Performance Measures: A US 281N Corridor Case Study

The National Performance Management Research Data Set (NPMRDS), made available by Federal Highway Administration in 2013, provides fine-resolution travel time data, which has been used in numerous network performance management and operations applications. This research discusses corridor-level performance measures computed using the NPMRDS. We analyze three measures on a 20.2-mile long corridor in San Antonio, Texas, including corridor travel time, corridor travel-time reliability, and day-to-day variation in travel time. The primary contributions of this research are the analysis of the impact of using two different approaches for travel-time aggregation across segments’ instantaneous and time-dependent approaches and defining a mean absolute error (MAE) based method to identify days when travel times significantly deviate from typical traffic conditions. (Research sponsored through TxDOT.)

Presenter(s): Venktesh Pandey

Poster session 2018 symposium