1,082 research outputs found

    Multidisciplinary accident investigations

    Get PDF
    Issued as Monthly progress report [1-5], Quarterly progress report [1-7], Flow diagram network, and Final report, Phase 4-5, Project no. E-20-606 (formerly B-617)Final reports have title: Multidisciplinary accident investigation

    New Orleans Claiborne Avenue Redevelopment Study: A University of New Orleans Analysis of Best Practices and Public Opinion

    Get PDF
    The purpose of this study is to examine the potential implications of the removal of the Claiborne Expressway segment of Interstate 10 (I-10), a proposal that has gained traction since Hurricane Katrina. This study complements previous analyses of the impacts of removing the elevated expressway. It considers case studies of best practices in highway removal, the history of the study area, and the proposal in terms of its local and regional context -- in particular the transportation system, land-use patterns, the economy, and the community of the affected area. Stakeholder interviews and surveys were conducted to assist with drawing conclusions and recommendations about the proposed removal of the I-10 highway segment and redevelopment of the Claiborne corridor

    Development and evaluation of a NFWEAV simulation model for weaving areas under non-freeway condition

    Get PDF
    The development of a microscopic digital computer simulation model representing vehicle interaction at a weaving area under non-freeway condition is presented. Weaving areas are classified into two categories: 1. Weaving caused by merging and diverging of a ramp with an arterial, 2. On/off ramps connecting an arterial with a highway. The principal characteristics of the simulation model are the following: 1) a car following and lane changing model were used to represent vehicle movements; 2) an anti-collision check algorithm was developed for all vehicle movements; 3) driver merging urgency and follower courtesy model were developed for weaving vehicles. The simulation model was validated through field observation using video taping and photogrammetry techniques Comparative analyses between field observations and model predictions are carried out for non-weaving and weaving speed, as well as non-weaving and weaving acceleration. The results indicate that there is no statistically significant difference between the field data and simulation output

    Analyzing data in the Internet of Things

    Get PDF
    The Internet of Things (IoT) is growing fast. According to the International Data Corporation (IDC), more than 28 billion things will be connected to the Internet by 2020—from smartwatches and other wearables to smart cities, smart homes, and smart cars. This O’Reilly report dives into the IoT industry through a series of illuminating talks and case studies presented at 2015 Strata + Hadoop World Conferences in San Jose, New York, and Singapore. Among the topics in this report, you’ll explore the use of sensors to generate predictions, using data to create predictive maintenance applications, and modeling the smart and connected city of the future with Kafka and Spark. Case studies include: Using Spark Streaming for proactive maintenance and accident prevention in railway equipment Monitoring subway and expressway traffic in Singapore using telco data Managing emergency vehicles through situation awareness of traffic and weather in the smart city pilot in Oulu, Finland Capturing and routing device-based health data to reduce cardiovascular disease Using data analytics to reduce human space flight risk in NASA’s Orion program This report concludes with a discussion of ethics related to algorithms that control things in the IoT. You’ll explore decisions related to IoT data, as well as opportunities to influence the moral implications involved in using the IoT

    Assessing the Safety and Operational Benefits of Connected and Automated Vehicles: Application on Different Roadways, Weather, and Traffic Conditions

    Get PDF
    Connected and automated vehicle (CAV) technologies have recently drawn an increasing attention from governments, vehicle manufacturers, and researchers. Connected vehicle (CV) technologies provide real-time information about the surrounding traffic condition (i.e., position, speed, acceleration) and the traffic management center\u27s decisions. The CV technologies improve the safety by increasing driver situational awareness and reducing crashes through vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I). Vehicle platooning with CV technologies is another key element of the future transportation systems which helps to simultaneously enhance traffic operations and safety. CV technologies can also further increase the efficiency and reliability of automated vehicles (AV) by collecting real-time traffic information through V2V and V2I. However, the market penetration rate (MPR) of CAVs and the higher level of automation might not be fully available in the foreseeable future. Hence, it is worthwhile to study the safety benefits of CAV technologies under different MPRs and lower level of automation. None of the studies focused on both traffic safety and operational benefits for these technologies including different roadway, traffic, and weather conditions. In this study, the effectiveness of CAV technologies (i.e., CV /AV/CAV/CV platooning) were evaluated in different roadway, traffic, and weather conditions. To be more specific, the impact of CVs in reduced visibility condition, longitudinal safety evaluation of CV platooning in the managed lane, lower level of AVs in arterial roadway, and the optimal MPRs of CAVs for both peak and off-peak period are analyzed using simulation techniques. Currently, CAV fleet data are not easily obtainable which is one of the primary reasons to deploy the simulation techniques in this study to evaluate the impacts of CAVs in the roadway. The car following, lane changing, and the platooning behavior of the CAV technologies were modeled in the C++ programming language by considering realistic car following and lane changing models in PTV VISSIM. Surrogate safety assessment techniques were considered to evaluate the safety effectiveness of these CAV technologies, while the average travel time, average speed, and average delay were evaluated as traffic operational measures. Several statistical tests (i.e., Two sample t-test, ANOVA) and the modelling techniques (Tobit, Negative binomial, and Logistic regression) were conducted to evaluate the CAV effectiveness with different MPRs over the baseline scenario. The statistical tests and modeling results suggested that the higher the MPR of CAVs implemented, the higher were the safety and mobility benefits achieved for different roadways (i.e., freeway, expressway, arterials, managed lane), weather (i.e., clear, foggy), and traffic conditions (i.e., peak and off-peak period). Interestingly, from the safety and operation perspective, at least 30% and 20% MPR were needed to achieve both the safety and operational benefits of peak and off-peak period, respectively. This dissertation has major implications for improving transportation infrastructure by recommending optimal MPR of CAVs to achieve balanced mobility and safety benefits considering varying roadway, traffic, and weather condition

    Calibration of Traffic Simulation Models using SPSA

    Get PDF
    Εθνικό Μετσόβιο Πολυτεχνείο--Μεταπτυχιακή Εργασία. Διεπιστημονικό-Διατμηματικό Πρόγραμμα Μεταπτυχιακών Σπουδών (Δ.Π.Μ.Σ.) “Γεωπληροφορική

    Remaking Downtown Toronto: Politics, Development, and Public Space on Yonge Street, 1950-1980

    Get PDF
    This study explores the history of Torontos iconic downtown Yonge Street and the people who contested its future, spanning a period from the 1950s through to 1980 when the street was seldom out of the news. Through detailed analysis of a range of primary sources, it explores how the uses and public meanings of this densely-built commercial strip changed over time, in interaction with the city transforming around it. What emerges is a street that, despite fears for its future, remained at the heart of urban life in Toronto, creating economic value as a retail centre; pushing the boundaries of taste and the law as a mass-entertainment destination; and drawing crowds as a meeting place, pedestrian corridor, and public space. Variously understood as an historic urban landscape and an embarrassing relic, a transportation route and a people place, a bastion of Main Street values and a haven for big-city crime and sleaze, from the 1950s through the 1970s Yonge was at the centre of efforts to improve or reinvent the central city in ways that would keep pace with, or even lead, urban change. This thesis traces the history of three interventionsa pedestrian mall, a clean-up campaign aimed at the sex industry, and a major redevelopment schemetheir successes and failures, and the larger debates they triggered. The result is a narrative that ranges widely in theme: planning, automobility, and youth culture; vice, moral regulation, and citizen activism; capitalism, corporate power, and urban renewal. Engaging with the North American and international historiographies of these topics, it places the politics of downtown in Toronto in larger historical context. It offers an account of urban transformation that emphasizes complexity in the interaction between ideas, structures of power, and the often idiosyncratic decisions of a range of downtown actors. An increasingly interventionist local state, dynamic capital investment in retail and real estate, and diverse citizen mobilizations all contributed to transforming Yonge Street, helping to create the modern, globalized downtown shopping street and public space we know today

    Improving Traffic Safety And Drivers\u27 Behavior In Reduced Visibility Conditions

    Get PDF
    This study is concerned with the safety risk of reduced visibility on roadways. Inclement weather events such as fog/smoke (FS), heavy rain (HR), high winds, etc, do affect every road by impacting pavement conditions, vehicle performance, visibility distance, and drivers’ behavior. Moreover, they affect travel demand, traffic safety, and traffic flow characteristics. Visibility in particular is critical to the task of driving and reduction in visibility due FS or other weather events such as HR is a major factor that affects safety and proper traffic operation. A real-time measurement of visibility and understanding drivers’ responses, when the visibility falls below certain acceptable level, may be helpful in reducing the chances of visibility-related crashes. In this regard, one way to improve safety under reduced visibility conditions (i.e., reduce the risk of visibility related crashes) is to improve drivers’ behavior under such adverse weather conditions. Therefore, one of objectives of this research was to investigate the factors affecting drivers’ stated behavior in adverse visibility conditions, and examine whether drivers rely on and follow advisory or warning messages displayed on portable changeable message signs (CMS) and/or variable speed limit (VSL) signs in different visibility, traffic conditions, and on two types of roadways; freeways and two-lane roads. The data used for the analyses were obtained from a self-reported questionnaire survey carried out among 566 drivers in Central Florida, USA. Several categorical data analysis techniques such as conditional distribution, odds’ ratio, and Chi-Square tests were applied. In addition, two modeling approaches; bivariate and multivariate probit models were estimated. The results revealed that gender, age, road type, visibility condition, and familiarity with VSL signs were the significant factors affecting the likelihood of reducing speed following CMS/VSL instructions in reduced visibility conditions. Other objectives of this survey study were to determine the content of messages that iv would achieve the best perceived safety and drivers’ compliance and to examine the best way to improve safety during these adverse visibility conditions. The results indicated that Caution-fog ahead-reduce speed was the best message and using CMS and VSL signs together was the best way to improve safety during such inclement weather situations. In addition, this research aimed to thoroughly examine drivers’ responses under low visibility conditions and quantify the impacts and values of various factors found to be related to drivers’ compliance and drivers’ satisfaction with VSL and CMS instructions in different visibility and traffic conditions. To achieve these goals, Explanatory Factor Analysis (EFA) and Structural Equation Modeling (SEM) approaches were adopted. The results revealed that drivers’ satisfaction with VSL/CMS was the most significant factor that positively affected drivers’ compliance with advice or warning messages displayed on VSL/CMS signs under different fog conditions followed by driver factors. Moreover, it was found that roadway type affected drivers’ compliance to VSL instructions under medium and heavy fog conditions. Furthermore, drivers’ familiarity with VSL signs and driver factors were the significant factors affecting drivers’ satisfaction with VSL/CMS advice under reduced visibility conditions. Based on the findings of the survey-based study, several recommendations are suggested as guidelines to improve drivers’ behavior in such reduced visibility conditions by enhancing drivers’ compliance with VSL/CMS instructions. Underground loop detectors (LDs) are the most common freeway traffic surveillance technologies used for various intelligent transportation system (ITS) applications such as travel time estimation and crash detection. Recently, the emphasis in freeway management has been shifting towards using LDs data to develop real-time crash-risk assessment models. Numerous v studies have established statistical links between freeway crash risk and traffic flow characteristics. However, there is a lack of good understanding of the relationship between traffic flow variables (i.e. speed, volume and occupancy) and crashes that occur under reduced visibility (VR crashes). Thus, another objective of this research was to explore the occurrence of reduced visibility related (VR) crashes on freeways using real-time traffic surveillance data collected from loop detectors (LDs) and radar sensors. In addition, it examines the difference between VR crashes to those occurring at clear visibility conditions (CV crashes). To achieve these objectives, Random Forests (RF) and matched case-control logistic regression model were estimated. The results indicated that traffic flow variables leading to VR crashes are slightly different from those variables leading to CV crashes. It was found that, higher occupancy observed about half a mile between the nearest upstream and downstream stations increases the risk for both VR and CV crashes. Moreover, an increase of the average speed observed on the same half a mile increases the probability of VR crash. On the other hand, high speed variation coupled with lower average speed observed on the same half a mile increase the likelihood of CV crashes. Moreover, two issues that have not explicitly been addressed in prior studies are; (1) the possibility of predicting VR crashes using traffic data collected from the Automatic Vehicle Identification (AVI) sensors installed on Expressways and (2) which traffic data is advantageous for predicting VR crashes; LDs or AVIs. Thus, this research attempts to examine the relationships between VR crash risk and real-time traffic data collected from LDs installed on two Freeways in Central Florida (I-4 and I-95) and from AVI sensors installed on two vi Expressways (SR 408 and SR 417). Also, it investigates which data is better for predicting VR crashes. The approach adopted here involves developing Bayesian matched case-control logistic regression using the historical VR crashes, LDs and AVI data. Regarding models estimated based on LDs data, the average speed observed at the nearest downstream station along with the coefficient of variation in speed observed at the nearest upstream station, all at 5-10 minute prior to the crash time, were found to have significant effect on VR crash risk. However, for the model developed based on AVI data, the coefficient of variation in speed observed at the crash segment, at 5-10 minute prior to the crash time, affected the likelihood of VR crash occurrence. Argument concerning which traffic data (LDs or AVI) is better for predicting VR crashes is also provided and discussed

    Shifting urban priorities : the removal of inner city freeways in the United States

    Get PDF
    Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 2007.Includes bibliographical references (p. 132-136).The United States Interstate Highway System transformed the nation's cities and countryside, accelerating suburbanization and leading to unprecedented levels of motorized mobility. While the interstate highways brought undeniable benefits, they also imparted social, environmental and aesthetic costs. Growing opposition to the paving of cities in the name of improved mobility resulted in a "freeway revolt" movement. Much of the original interstate infrastructure built in the 1950s and 1960s is reaching or is past the end of its useful life - requiring large investments for rehabilitation. At the same time, the freeway revolt has evolved into a more widespread movement, underlined by values such as sustainability. Thus, the vigorous debate over the future of urban highways and mobility continues. This thesis examines this future from the perspective of a fairly recent phenomenon: urban freeway removal. By examining three different cases where urban freeway removal was a seriously considered option - two where the freeway was removed and replaced with a lower capacity at-grade boulevard (Park East Freeway, Milwaukee and Central Freeway, San Francisco) and one where the freeway ultimately was not removed (Whitehurst Freeway, Washington D.C.) this thesis works toward a theory of highway removal.(cont.) The analysis suggests that freeway removal will only take place when: (1) the one precondition is met: the condition of the freeway must be such, that there is concern over its integrity and structural safety, (2) a window of opportunity exists; the window may the precondition itself or another event that enables a freeway removal alternative to gain serious consideration and legitimacy, (3) the value of mobility must be lower than other objectives such as economic development, quality of life, etc., and (4) those in power must value other benefits more than they value the benefits associated with freeway infrastructure for the alternative of freeway removal to be selected over other alternatives.by Francesca Napolitan.M.C.P
    corecore