The Reliability and Effectiveness of a Radar-Based Animal Detection System

This document contains data on the reliability and effectiveness of an animal detection system along U.S. Hwy 95 near Bonners Ferry, Idaho. The system uses a Doppler radar to detect large mammals (e.g., deer and elk) when they approach the highway. The system met most of the suggested minimum norms for reliability. The total time the warning signs were activated was at most 90 seconds per hour, and likely substantially less. Animal detection systems are designed to detect an approaching animal. After an animal has been detected, warning signs are activated which allow drivers to respond. Results showed that 58.1–67.9% of deer were detected sufficiently early for northbound drivers, and 70.4–85% of deer were detected sufficiently early for southbound drivers. The effect of the activated warning signs on vehicle speed was greatest when road conditions were challenging (e.g., freezing temperatures and snow- and ice-covered road surface) and when visibility was low (night). In summer, there was no measurable benefit of activated warning signs, at least not as far as vehicle speed is concerned. Depending on the conditions in autumn and winter, the activated warning signs resulted in a speed reduction of 0.69 to 4.43 miles per hour. The report includes practical recommendations for operation and maintenance of the system and suggestions for potential future research

Using Operations Data for Planning the the Delaware Valley: First Steps

Real-time traffic operations data has been gathered for several years on an increasing number of roads throughout the Delaware Valley. The archives of this data are a tremendous potential resource for transportation planning. Use of the data, however, has posed significant technical challenges. This report summarizes how the data can be used, the state of operations data for planning in the Delaware Valley, and the results of two case studies. The first case study used data from the Pennsylvania Department of Transportation's Dynac system about speed and travel time on a section of I-76. The second case study used data provided by the I-95 Corridor Coalition Vehicle Probe Project (VPP) from INRIX, a private-sector traffic data company. The second case study analyzed duration of congestion on weekdays in 2009 for freeways in the Delaware Valley. This analysis was used in the region's 2011 Congestion Management Process

Performance Measures to Assess Resiliency and Efficiency of Transit Systems

Transit agencies are interested in assessing the short-, mid-, and long-term performance of infrastructure with the objective of enhancing resiliency and efficiency. This report addresses three distinct aspects of New Jersey’s Transit System: 1) resiliency of bridge infrastructure, 2) resiliency of public transit systems, and 3) efficiency of transit systems with an emphasis on paratransit service. This project proposed a conceptual framework to assess the performance and resiliency for bridge structures in a transit network before and after disasters utilizing structural health monitoring (SHM), finite element (FE) modeling and remote sensing using Interferometric Synthetic Aperture Radar (InSAR). The public transit systems in NY/NJ were analyzed based on their vulnerability, resiliency, and efficiency in recovery following a major natural disaster

Value of Reliability: High Occupancy Toll Lanes, General Purpose Lanes, and Arterials

In the Minneapolis-St. Paul region (Twin Cities), the Minnesota Department of Transportation (MnDOT) converted the Interstate 394 High Occupancy Vehicle (HOV) lanes to High Occupancy Toll (HOT) lanes (or MnPASS Express Lanes). These lanes allow single occupancy vehicles (SOV) to access the HOV lanes by paying a fee. This fee is adjusted according to a dynamic pricing system that varies with the current demand. This paper estimates the value placed by the travelers on the HOT lanes because of improvements in travel time reliability. This value depends on how the travelers regard a route with predictable travel times (or small travel time variability) in comparison to another with unpredictable travel times (or high travel time variability). For this purpose, commuters are recruited and equipped with Global Positioning System (GPS) devices and instructed to commute for two weeks on each of three plausible alternatives between their home in the western suburbs of Minneapolis eastbound to work in downtown or the University of Minnesota: I-394 HOT lanes, I-394 General Purpose lanes (untolled), and signalized arterials close to the I-394 corridor. They are then given the opportunity to travel on their preferred route after experiencing each alternative. This revealed preference data is then analyzed using mixed logit route choice models. Three measures of reliability are explored and incorporated in the estimation of the models: standard deviation (a classical measure in the research literature); shortened right range (typically found in departure time choice models); and interquartile range (75th - 25th percentile). Each of these measures represents distinct ways about how travelers deal with different sections of reliability. In all the models, it was found that reliability was valued highly (and statistically significantly), but differently according to how it was defined. The estimated value of reliability in each of the models indicates that commuters are willing to pay a fee for a reliable route depending on how they value their reliability savings.time reliability, GPS, route choice, random utility, I-394 HOT, MnPass, mixed logit

How Effective are Toll Roads in Improving Operational Performance?

The main focus of this research is to develop a systematic analytical framework and evaluate the effect of a toll road on region’s traffic using travel time and travel time reliability measures. The travel time data for the Triangle Expressway in Raleigh, North Carolina, United States was employed for the assessment process. The spatial and temporal variations in the travel time distributions on the toll road, parallel alternate route, and near-vicinity cross-streets were analyzed using various travel time reliability measures. The results indicate that the Triangle Expressway showed a positive trend in reliability over the years of its operation. The parallel route reliability decreased significantly during the analysis period, whereas the travel time reliability of cross-streets showed a consistent trend. The stabilization of travel time distributions and the reliability measures over different years of toll road operation are good indicators, suggesting that further reduction in performance measures may not be seen on the near vicinity corridors. The findings from link-level and corridor-level analysis may help with transportation system management, assessing the influence of travel demand patterns, and evaluating the effect of planned implementation of similar projects

Efficient detection of contagious outbreaks in massive metropolitan encounter networks

Physical contact remains difficult to trace in large metropolitan networks, though it is a key vehicle for the transmission of contagious outbreaks. Co-presence encounters during daily transit use provide us with a city-scale time-resolved physical contact network, consisting of 1 billion contacts among 3 million transit users. Here, we study the advantage that knowledge of such co-presence structures may provide for early detection of contagious outbreaks. We first examine the "friend sensor" scheme --- a simple, but universal strategy requiring only local information --- and demonstrate that it provides significant early detection of simulated outbreaks. Taking advantage of the full network structure, we then identify advanced "global sensor sets", obtaining substantial early warning times savings over the friends sensor scheme. Individuals with highest number of encounters are the most efficient sensors, with performance comparable to individuals with the highest travel frequency, exploratory behavior and structural centrality. An efficiency balance emerges when testing the dependency on sensor size and evaluating sensor reliability; we find that substantial and reliable lead-time could be attained by monitoring only 0.01% of the population with the highest degree.Comment: 4 figure

A method to assess demand growth vulnerability of travel times on road network links

Many national governments around the world have turned their recent focus to monitoring the actual reliability of their road networks. In parallel there have been major research efforts aimed at developing modelling approaches for predicting the potential vulnerability of such networks, and in forecasting the future impact of any mitigating actions. In practice-whether monitoring the past or planning for the future-a confounding factor may arise, namely the potential for systematic growth in demand over a period of years. As this growth occurs the networks will operate in a regime closer to capacity, in which they are more sensitive to any variation in flow or capacity. Such growth will be partially an explanation for trends observed in historic data, and it will have an impact in forecasting too, where we can interpret this as implying that the networks are vulnerable to demand growth. This fact is not reflected in current vulnerability methods which focus almost exclusively on vulnerability to loss in capacity. In the paper, a simple, moment-based method is developed to separate out this effect of demand growth on the distribution of travel times on a network link, the aim being to develop a simple, tractable, analytic method for medium-term planning applications. Thus the impact of demand growth on the mean, variance and skewness in travel times may be isolated. For given critical changes in these summary measures, we are thus able to identify what (location-specific) level of demand growth would cause these critical values to be exceeded, and this level is referred to as Demand Growth Reliability Vulnerability (DGRV). Computing the DGRV index for each link of a network also allows the planner to identify the most vulnerable locations, in terms of their ability to accommodate growth in demand. Numerical examples are used to illustrate the principles and computation of the DGRV measure

Transit Performance Measures in California

This research is the result of a California Department of Transportation (Caltrans) request to assess the most commonly available transit performance measures in California. Caltrans wanted to understand performance measures and data used by Metropolitan Planning Organizations (MPOs) and transit agencies to help it develop statewide measures. This report serves as a summary reference guide to help Caltrans understand the numerous and diverse performance measures used by MPOs and transit agencies in California. First, investigators review the available literature to identify a complete transit performance framework for the purposes of organizing agency measures, metrics, and data sources. Next, they review the latest transit performance measures documented in planning reports for the four largest MPOs in California (San Francisco Bay Area, Los Angeles, San Diego, and Sacramento). Researchers pay special attention to the transit performance measures used by these MPOs, because these measures are available for the majority of California’s population. Finally, investigators summarize 231 performance measures used by a total 26 local transit agencies in the State of California, based on transit planning documents available on the internet

Estimating Uncertainty of Bus Arrival Times and Passenger Occupancies

Travel time reliability and the availability of seating and boarding space are important indicators of bus service quality and strongly influence users’ satisfaction and attitudes towards bus transit systems. With Automated Vehicle Location (AVL) and Automated Passenger Counter (APC) units becoming common on buses, some agencies have begun to provide real-time bus location and passenger occupancy information as a means to improve perceived transit reliability. Travel time prediction models have also been established based on AVL and APC data. However, existing travel time prediction models fail to provide an indication of the uncertainty associated with these estimates. This can cause a false sense of precision, which can lead to experiences associated with unreliable service. Furthermore, no existing models are available to predict individual bus occupancies at downstream stops to help travelers understand if there will be space available to board. The purpose of this project was to develop modeling frameworks to predict travel times (and associated uncertainties) as well as individual bus passenger occupancies. For travel times, accelerated failure-time survival models were used to predict the entire distribution of travel times expected. The survival models were found to be just as accurate as models developed using traditional linear regression techniques. However, the survival models were found to have smaller variances associated with predictions. For passenger occupancies, linear and count regression models were compared. The linear regression models were found to outperform count regression models, perhaps due to the additive nature of the passenger boarding process. Various modeling frameworks were tested and the best frameworks were identified for predictions at near stops (within five stops downstream) and far stops (further than eight stops). Overall, these results can be integrated into existing real-time transit information systems to improve the quality of information provided to passengers

Social Equity Impacts of Congestion Management Strategies

This white paper examines the social equity impacts of various congestion management strategies. The paper includes a comprehensive list of 30 congestion management strategies and a discussion of equity implications related to each strategy. The authors analyze existing literature and incorporate findings from 12 expert interviews from academic, non-governmental organization (NGO), public, and private sector respondents to strengthen results and fill gaps in understanding. The literature review applies the Spatial – Temporal – Economic – Physiological – Social (STEPS) Equity Framework (Shaheen et al., 2017) to identify impacts and classify whether social equity barriers are reduced, exacerbated, or both by a particular congestion mitigation measure. The congestion management strategies discussed are grouped into six main categories, including: 1) pricing, 2) parking and curb policies, 3) operational strategies, 4) infrastructure changes, 5) transportation services and strategies, and 6) conventional taxation. The findings show that the social equity impacts of certain congestion management strategies are not well understood, at present, and further empirical research is needed. Congestion mitigation measures have the potential to affect travel costs, commute times, housing, and accessibility in ways that are distinctly positive or negative for different populations. For these reasons, social equity implications of congestion management strategies should be understood and mitigated for in planning and implementation of these strategies