The American Society for Testing and Materials (ASTM) is an independent organization devoted to the development of standards.

American Society for Testing and Materials

Highway Capacity Manual改訂の動向--テイラ-教授の講演より

Over the past decade, vision-based vehicle detection techniques for road safety improvement have gained an increasing amount of attention. Unfortunately, the techniques suffer from robustness due to huge variability in vehicle shape (particularly for motorcycles), cluttered environment, various illumination conditions, and driving behavior. In this paper, we provide a comprehensive survey in a systematic approach about the state-of-the-art on-road vision-based vehicle detection and tracking systems for collision avoidance systems (CASs). This paper is structured based on a vehicle detection processes starting from sensor selection to vehicle detection and tracking. Techniques in each process/step are reviewed and analyzed individually. Two main contributions in this paper are the following: survey on motorcycle detection techniques and the sensor comparison in terms of cost and range parameters. Finally, the survey provides an optimal choice with a low cost and reliable CAS design in vehicle industries.

Vehicle Detection Techniques for Collision Avoidance Systems: A Review

Rapid urbanization and the growing demand for faster transportation has led to heavy congestion in road traffic networks, necessitating the need for traffic-responsive intelligent signal control systems. The developed signal control system must be capable of determining the green time that minimizes the network-wide travel time delay based on limited information of the environment. This paper adopts a distributed multiagent-based approach to develop a traffic-responsive signal control system, i.e., the geometric fuzzy multiagent system (GFMAS), which is based on a geometric type-2 fuzzy inference system. GFMAS is capable of handling the various levels of uncertainty found in the inputs and rule base of the traffic signal controller. Simulation models of the agents designed in PARAMICS were tested on virtual road network replicating a section of the central business district in Singapore. A comprehensive analysis and comparison was performed against the existing traffic-control algorithms green link determining (GLIDE) and hierarchical multiagent system (HMS). The proposed GFMAS signal control outperformed both the benchmarks when tested for typical traffic-flow scenarios. Further tests show the superior performance of the proposed GFMAS in handling unplanned and planned incidents and obstructions. The promising results demonstrate the efficiency of the proposed multiagent architecture and scope for future development.

Distributed Geometric Fuzzy Multiagent Urban Traffic Signal Control

Improving a vehicle driver’s performance decreases the damage caused by, and chances of, road accidents. In recent decades, engineers and researchers have proposed several strategies to model and improve driving monitoring and assistance systems (DMAS). This work presents a comprehensive survey of the literature related to driving processes, the main reasons for road accidents, the methods of their early detection, and state-of-the-art strategies developed to assist drivers for a safe and comfortable driving experience. The studies focused on the three main elements of the driving process, viz. driver, vehicle, and driving environment are analytically reviewed in this work, and a comprehensive framework of DMAS, major research areas, and their interaction is explored. A well-designed DMAS improves the driving experience by continuously monitoring the critical parameters associated with the driver, vehicle, and surroundings by acquiring and processing the data obtained from multiple sensors. A discussion on the challenges associated with the current and future DMAS and their potential solutions is also presented.

/pdf/a-comprehensive-survey-of-driving-monitoring-and-assistance-4ftzretuvn.pdf

A Comprehensive Survey of Driving Monitoring and Assistance Systems.

Traffic engineers are often faced with operational and safety challenges at rural, high-speed signalized intersections. Vehicle-actuated control, combined with multiple advance detectors, is often used to improve operations and safety. However, this type of detection and control has not always eliminated rear-end or right-angle crashes. Crashes sometimes continue to occur at high-speed intersections, and delays to traffic movements can be unnecessarily long. This project developed and tested a detection-control system that is capable of minimizing both delay and crash frequency at rural intersections. This report documents the work performed, findings, and conclusions reached as a result of the two-year research project. During the first year, an intelligent detection-control system was developed and evaluated. The development consisted of defining the system's functionality and the hardware needed to implement it in the field. The evaluation consisted of using simulation software to exercise the algorithm for a range of traffic and geometric conditions. During the second year, the system was installed at two intersections and evaluated using field data. The results of this evaluation indicated that the system is able to provide equal or lower delays for a reasonable range of speeds, flow rates, and turn percentages. The results also indicate that the system will reduce the number of drivers running the red indication.

Intelligent detection-control system for rural signalized intersections

High-speed signalized intersections have both safety and efficiency problems. The safety problems traditionally have been overcome by using advance detectors. However, at relatively moderate flow rates, multiple advance detector systems tend to extend the green phase to its maximum allowable duration (i.e., max-out). At max-out, drivers on the intersection approach may be faced with the decision to proceed or stop. This creates the safety problem the system was intended to prevent. Also, extending phases to their maximums increases delays to other movements. A new approach to high-speed intersection control is outlined—a dynamic dilemma zone allocation system that uses measured vehicle speeds with a control algorithm to decide when to end the signal phases. The new system was evaluated by simulation and field installation. In both instances, the new system indicated it could improve safety and maintain efficient operations at high-speed intersections.

Improved Detection and Control System for Isolated High-Speed Signalized Intersections:

The objective of this research project was to produce a synthesis of available information to support specific areas related to pavements for the safe, economical development of the Trans Texas Corridor (TTC). This synthesis is divided into several sections, each of which deals with a specific topic or topics. These specific areas include (1) pavement design for heavy vehicles, (2) pavement design for light vehicles, (3) skid resistance issues on high-speed corridors, (4) issues related to traffic characterization, (5) smart pavements for high-speed corridors, (6) pavement material response to dynamic loads and performance prediction, (7) safety issues related to splash and spray, and (8) ride quality for high-speed corridors. Regarding these stated issues, this synthesis recommends state-of-the-art technology to the Texas Department of Transportation (TxDOT) for use during development of the TTC. It provides recommendations for future research to fill gaps in knowledge and to take emerging technology to the stage where it can be implemented during the design and construction of the TTC pavements. This is the first synthesis study to address issues related to the TTC. A secondary objective of this project was to determine if additional synthesis studies in other areas of transportation related to the TTC should be conducted and, if so, how the process might be improved. This synthesis recommends that future syntheses should be more focused on specific, maybe critical issues; the researcher should be instructed to present only those findings that are really new, innovative, and potentially implementable. One element of the study should pursue non-transportation related technology that might be adapted to transportation issues.

/pdf/synthesis-of-pavement-issues-related-to-high-speed-corridors-4hxqqpss55.pdf

Synthesis of Pavement Issues Related to High-Speed Corridors

Due to the well-documented problems associated with inductive loops, most jurisdictions have replaced many intersection loops with video image vehicle detection systems (VIVDS). While VIVDS have overcome some of the problems with loops such as traffic disruption and pavement degradation, they have not been as accurate as originally anticipated. The objective of this project is to conduct evaluations of alternative detector technologies for application into the state’s traffic signal systems. The research will include investigating the available detectors that could replace loops or VIVDS through a literature search and agency contacts, followed by field and/or laboratory investigations of promising technologies. Deliverables will include a research report, a project summary report, and a detector selection guide. Findings indicate that three detectors should be considered as alternatives to VIVDS for signalized intersections – one is a radar detector and the other two are magnetic detectors. The radar detector is only for dilemma zone detection and does not cover the stop line area. The other two are point detectors, so their basic function would be for loop replacements. One is an intrusive detector, requiring a short lane closure for installation and replacement. Field testing of performance for all three detectors indicated they are worth considering as inductive loop or VIVDS replacements.

/pdf/alternative-vehicle-detection-technologies-for-traffic-3w4qflfe7t.pdf

Alternative vehicle detection technologies for traffic signal systems: technical report

This research supplemented findings of previous research projects on the topic of vehicle detection. Because improvements in performance aspects and in functionality of non-intrusive vehicle detectors continue to occur at an ever increasing pace, there were reasons to continue testing of the most viable products and determine their interface potential with other components of the Texas Department of Transportation’s (TxDOT’s) existing system. Like previous vehicle detector research, this research tested the latest and most promising non-intrusive vehicle detector technologies. The ones included in this research were: video image vehicle detection systems (VIVDS), acoustic, magnetic, inductive loops, and microwave radar. Besides evaluating detectors, the research scope also included investigating an interface with TxDOT’s current Advanced Traffic Management System (ATMS) using contact closure inputs to current Local Control Units (LCUs) for collecting vehicle count, speed, and occupancy data. Findings of this research indicate that, of the detectors tested, the following technologies appear to be most promising for freeway applications based on cost, accuracy, and ease of setup: microwave radar and magnetometers. One of the VIVDS units tested was also accurate but its cost and ease of setup were inferior to the other two. Neither of the two technologies is affected by weather and they are capable of consistently achieving 95 percent count accuracy (or better) and can detect speeds to within 5 mph of true speeds.

Investigation of Vehicle Detector Performance and ATMS Interface

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Dan Middleton

Author Tools

Chat about Author