Intelligent Transportation Systems Strategic Plan (Phase I Report)

This interim report on an Intelligent Transportation Systems Strategic (ITS) Plan has been developed as documentation of the process of offering a vision for ITS and recommending an outline for organizational structure, infrastructure, and long-term planning for ITS in Kentucky. This plan provides an overview of the broad scope of ITS and relationships between various Intelligent Vehicle Highway Systems (IVHS) functional areas and ITS user service areas. Three of the functional areas of ITS have been addressed in this interim report with sections devoted to mission, vision, goals, and potential technology applications. Within each of the three areas, recommendations have been made for applications and technologies for deployment. A more formalized business plan for will be developed to recommend specific projects for implementation. Those three functional areas are 1) Advanced Rural Transportation Systems (ARTS), 2) Advanced Traveler Information Systems (ATIS), and 3) Commercial Vehicle Operations (CVO). A survey of other states was conducted to determine the status of the development of ITS strategic plans. Information received from the 11 states that had completed strategic plans was used to determine the overall approach taken in development of the plans and to evaluate the essential contents of the reports for application in Kentucky. Kentucky\u27s ITS Strategic Plan evolved from an early decision by representatives of the Kentucky Transportation Cabinet (KyTC) to formalize the procedure by requesting the Kentucky Transportation Center to prepare a work plan outlining the proposed tasks. Following several introductory meetings of the Study Advisory Committee, additional focus group meetings were held with various transportation representatives to identify ITS issues of importance. Results from these meetings were compiled and used as input to the planning process for development of the Strategic Plan components of ARTS and ATIS. The development of a strategic plan for Commercial Vehicle Operations originated from a different procedure than did the other functional areas of ITS. As part of well-developed commercial vehicle activities through the ITS-related programs of Advantage I-75 and CVISN, Kentucky has become a national leader in this area and has developed a strategic plan of advanced technology applications to commercial vehicles. The strategic plan for Commercial Vehicle Operations was developed out of the convergence of several parallel processes in Kentucky. Empower Kentucky work teams had met over a two-year period to develop improved and more efficient processes for CVO in Kentucky. Their conclusions and recommendations encouraged the further activities of the Kentucky ITS/CVO working group that first convened in the summer of 1996. In an effort to conceptually organize the various ITS/CVO activities in Kentucky, and as a commitment to the CVISN Mainstreaming plan, an inclusive visioning exercise was held in early 1997. Out of this exercise emerged the six critical vision elements that guided the CVO strategic plan. The remaining functional areas to be included in the ITS Strategic Plan will be addressed in the second phase of this study. Those areas are Advanced Traffic Management Systems (ATMS), Advanced Vehicle Control Systems (AVCS), and Advanced Public Transportation Systems (APTS). It is anticipated that a process similar to that developed for the first phase of this study will continue

DEVELOPING A SOUTH CAROLINA TRAFFIC INCIDENT MANAGEMENT PLAN ALONG THE I-26 CORRIDOR BETWEEN COLUMBIA AND CHARLESTON

Traffic Incident Management (TIM) programs are used in many states across the nation to efficiently clear interstate incidents and alleviate congestion in response to incidents. The overarching goal of this research is to maintain safety of the motoring public and incident responders while reducing congestion, secondary collisions, and traffic delays from incidents that occur on South Carolina highways. To reduce incident clearance times along the I-26 corridor between Columbia and Charleston through the implementation of a Traffic Incident Management (TIM) Program, several objectives for this thesis were established to move toward the goal, including; defining gaps between national TIM best-practices and SC TIM practices recommending programmatic changes to address gaps based on best-practices literature, developing training materials to address programmatic changes as needed, and assessing existing performance measurement metrics and suggest improvements to better evaluate changes in program effectiveness. The nationally recommended best practices were compared to the current South Carolina practices. Gaps were observed and SCDOT expressed interest in developing towing, coroner, HAZMAT, and crash investigation procedures. Successful programs involving these groups of responders were evaluated, including implementation costs and challenges. Several successful national programs, as well as those in Florida, Georgia, and numerous other states were included in this step. This specifically included incentive based towing programs, fatality removal programs, HAZMAT training procedures, and crash investigation technologies. It is recommended that these programs be considered and investigated further when implementing a SC TIM plan. It was however noted that while basic HAZMAT training is necessary, a large or full-scale program may not be cost effective. After analyzing the data, areas where data collection could be improved were determined. It is recommended that responders more consistently collect on-scene arrival time for all agencies. Additionally, due to the high number of incidents that seem to be timing out and recording recovery times that are too long, it is recommended that improvements to the data collection process be made

A two-level identification model for selecting the coordination strategy for the urban arterial road based on fuzzy logic

A novel model for identifying the traffic condition of urban arterial roadways is proposed in this paper to improve the operational efficiency and safety of the urban traffic arterial road system. During the identification process, fuzzy analytic hierarchy process and fuzzy integrated evaluation are employed to identify the traffic condition on the arterial road; according to the fuzzy logic scheme, a proper coordination strategy is then generated based on the resulting identification of each way of the artery. To verify the effectiveness of the proposed method, a numerical experiment is carried out by using the microscopic traffic simulation software VISSIM, where a traffic flow simulation system is generated according to the real-time traffic data. The comparison results show that the proposed model works well to fit with the actual operating condition of the arterial traffic and the proposed coordination strategy can provide a better performance for the traffic management

Advisory Safety System for Autonomous Vehicles under Sun-glare

Autonomous Vehicles (AVs) are expected to provide a large number of benefits such as improving comfort, vehicle safety and traffic flow. AVs use various sensors and control systems to empower driver’s decision-making under uncertainties as well as, assist the driving task under adverse conditions such as vision impairment. Excessive sunlight has been recognized as the primary source of the reduction in vision performance during daytime. Sun glare oftentimes leads to an impaired visibility for drivers and has been studied from different aspects on roadways. However, there is a lack of knowledge regarding the potential detrimental effects of natural light brightness differential, particularly sun glare on driving behavior and its possible risks. This dissertation addresses this issue by developing an integrated vehicle safety methodology as an advisory system for safe driving under sun glare. The main contribution of this research is to establish a real-time detection of the vision impairment area on roadways. This study also proposes a Collision Avoidance System Under Sun-glare (CASUS) in which upcoming possible vision impairment is detected, a warning message is sent, and the speed of vehicle is adjusted accordingly. In this context, real-world data is used to calibrate a psychophysical car-following model within VISSIM, a traffic microscopic simulation tool. Traffic safety impacts are explored through the number of conflicts extracted from the microsimulation tool and assessed by the time-to-collision indicator. Conventional/human-driven vehicles and different type of AVs are modeled for a straight segment of the TransCanada highway under various AVs penetration rates. The findings revealed a significant reduction in potential collisions due to adjustment of travel speed of AVs under the sun glare. The results also indicated that applying CASUS to the AVs with a failing sensory system improves traffic safety by providing optimal-safe speeds. Furthermore, the CASUS algorithm has the potential to be integrated into driving simulators or real vehicles to further evaluate and examine its benefits under different vision impairment scenarios

Incident Traffic Management Respone

The North Carolina State Highway Patrol (NCSHP) and the North Carolina Department of Transportation (NCDOT) are often called upon to assist in traffic incidents. Yet little systematic research has examined the extent to which these two agencies collaborate. This gap in understanding is problematic, as a lack of collaboration may result in significant delays in the clearing of traffic incidents. The purpose of this correlational study was to investigate circumstances when the two agencies collaborated in clearing major traffic incidents, and the efficiency of the clearance of the incidents, through the measurement of normal traffic flow. The theory of the convergence of resources from divergent organizations framed the study. The research questions addressed the extent of collaboration between the NCSHP and the NCDOT, the conditions under which this collaboration took place, and the efficiency of the clearance of these incidents. Data were obtained from the NCSHP and the NCDOT on characteristics of 1,580 traffic incidents that occurred on the North Carolina portion of Interstate 95 during the year 2014. The data were analyzed using chi-square tests, analyses of variance, and Z-tests for proportions. Collaboration between the two agencies occurred in 7.2% of all of the incidents and in 21.6% of incidents of major severity (p \u3c .001), which indicated a low level of interagency collaboration. The mean clearance time for incidents in which collaboration took place was 115.92 minutes compared to a national goal of 90 minutes. It is hoped that these results can contribute to policy dialogue relevant to the state\u27s Strategic Plan, leading to safer highways and less financial loss due to congestion caused by traffic incidents

Mobility Platform: Organizing and Visualizing Traffic Data in the Santa Fe Metropolitan Area

Transportation organizations in Santa Fe, New Mexico do not currently have a centralized location for all of the traffic data they collected in the Santa Fe metropolitan area. To alleviate this problem, the team created a database to store the data from each organization. Visualizations representing the data were also created, and this process was also made automatic through Microsoft Excel. Then, a transportation platform was created to provide the organizations with easy access to the database and visualizations

Corridor-Wide Surveillance Using Unmanned Aircraft Systems Phase II: Freeway Incident Detection Using Unmanned Aircraft Systems (Part A)

69A3551947136, 79075-00-SUB ADuring the second phase of this study, the team collected field data with unmanned aerial vehicles (UAVs) at different elevations and distances from the road to analyze the performance of a background subtraction algorithm for vehicle detection. Validation analyses were carried out and their results indicated that a detection rate with an accuracy of up to 92% can be reached using the background subtraction algorithm. The results of the ANOVA test confirmed that the drone\u2019s distance from the road was the only main factor associated with vehicle detection percentage (at the 95% confidence level). It was also determined that, depending on drone type, elevation can affect the detection rate based on the interaction plots created. The experiences from the field activities that took place during this phase of the project were incorporated into the previously developed protocol for the use of UAVs in corridor surveillance. The protocol was also updated with the steps that must be followed for several scenarios and these can be incorporated in future studies on the use of drones in transportation applications

Situational Awareness for Transportation Management: Automated Video Incident Detection and Other Machine Learning Technologies for the Traffic Management Center

IA 65A0541This report provides a synthesis of Automated Video Incident Detection (AVID) systems as well as a range of other technologies available for Automated Incident Detection (AID) and more general traffic system monitoring. In this synthesis, the authors consider the impacts of big data and machine learning techniques being introduced due to the accelerating pace of ubiquitous computing in general and Connected and Automated Vehicle (CAV) development in particular. They begin with a general background on the history of traffic management. This is followed by a more detailed review of the incident management process to introduce the importance of incident detection and general situational awareness in the Traffic Management Center (TMC). The authors then turn their attention to AID in general and AVID in particular before discussing the implications of more recent data sources for AID that have seen limited deployment in production systems but offer significant potential. Finally, they consider the changing role of the TMC and how new data can be integrated into traffic management processes most effectively