Browsing by Author "Alden, Andrew S."

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    An Assessment of Quiet Vehicles and Pedestrian and Bicyclist Safety
    Alden, Andrew S. (National Surface Transportation Safety Center for Excellence, 2014-07-28)
    The primary intent of this report is to provide a comprehensive and concise overview of the apparent safety issues presented to pedestrians and pedalcyclists by the operation of quiet vehicles on roadways. The report provides background information to establish how this issue became the focus of safety research in the United States and elsewhere. It presents the findings of a literature review of notable major research and a review of related pending and established regulations. The report also describes implemented and proposed countermeasure methods in addition to opportunities for future potential research to address knowledge gaps and improve overall understanding of the issues.
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    Enhanced Camera/Video Imaging Systems (E-C/VISs) for Heavy Vehicles
    Wierwille, Walter W.; Bowman, Darrell Scott; Alden, Andrew S.; Gibbons, Ronald B.; Hanowski, Richard J.; Blanco, Myra; Leeson, B.; Hickman, Jeffrey S. (United States. National Highway Traffic Safety Administration, 2011-06)
    Tests were performed to determine the feasibility of developing an Enhanced Camera/Video Imaging System (Enhanced C/VIS or E-C/VIS) to provide heavy-vehicle drivers with better situation awareness to the sides and rear of their vehicles. It is well known that large blind spots currently exist in these areas and that sideswipe crashes can occur as a result. An additional goal was to extend the operating envelope of conventional video to nighttime and to inclement weather. A three-channel system was envisioned in which there would be a camera at each (front) fender of the tractor looking backward along the sides of the rig. The third channel would be aimed rearward from the back of the trailer. The current document describes the project results. Indoor tests involved selection of components having the best capabilities, while early outdoor tests used the selected components in a single-channel side mounted system. Subjects evaluated rain and dark conditions. Results were satisfactory. Once developed, the three-channel system was tested and found to work well in the nighttime and inclement weather environments. Street lighting was also included in the testing.
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    Evaluation of a Buried Cable Roadside Animal Detection System
    Druta, Cristian; Alden, Andrew S. (Virginia Transportation Research Council, 2015-06)
    Animal-vehicle collisions (AVC) are a concern for departments of transportation as they translate into hundreds of human fatalities and billions of dollars in property damage each year. A recently published report states that the Virginia Department of Transportation (VDOT) currently spends over $4 million yearly to remove about 55,000 deer carcasses from its roadways. Currently, one of the most effective existing methods to reduce AVCs is the use of animal detection systems, which can detect animals near the roadway and alert approaching drivers accordingly. In order to reduce AVCs in Virginia, VDOT, in collaboration with the Virginia Tech Transportation Institute, proposed the evaluation of an innovative roadside animal detection system in naturalistic and controlled conditions. This type of system offers numerous apparent advantages over above-ground animal detection technologies when environmental interferences, such as precipitation and vegetation, and site-specific characteristics, such as topology, subsidence, and road curvature, are considered. The subject animal detection system (ADS), a 300-m-long buried dual-cable sensor, detects the crossing of large and medium-sized animals and provides data on their location along the length of the cable. The system has a central processor unit for control and communication and generates an invisible electromagnetic detection field around buried cables. When the detection field is perturbed, an alarm is declared and the location of the intrusion is determined. Target animals are detected based on their conductivity, size, and movement, with multiple simultaneous intrusions being detected during a crossing event. The system was installed and tested at a highly suitable site on the Virginia Smart Road where large wild animals, including deer and bear, are often observed in a roadside environment. This report describes the installation of the ADS, data collection and analysis methodology, evaluation of the system’s reliability and effectiveness, cost analysis, and implementation prospects. The system used continuous, all-weather and nighttime video surveillance to monitor animal movement and to gauge system detections, and potential non-detections of the ADS. Also, a communication link between the buried ADS and the Virginia Smart Road fiber optic network was established to allow operation and monitoring of the system from a dedicated server in the Virginia Smart Road Control Room. A performance verification of the network communication was successfully conducted through continuous data collection and transfer to a storage unit. Data were collected continuously for a period of 10 months that included winter, and then analyzed to determine overall detection performance of the system. Data analyses indicate that the ADS, if properly installed and calibrated, is capable of detecting animals such as deer and bear, and possibly smaller animals, such as fox and coyotes, with over 95% reliability. The ADS also performed well even when covered by 3 ft of snow. Moreover, the system was tested under various traffic conditions and no vehicle interferences were noted during the same monitoring period. The acquired data can be used to improve highway safety through driver warning systems installed along roadway sections where high wildlife activity has been observed. Additionally, this system may be integrated with the connected vehicle framework to provide advance, in-vehicle warnings to motorists approaching locations where animals have been detected in or near the roadway.
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    Feasibility Study for Animal Detection Driver Warning Systems on Corridor Q/Route 460
    Bell, Stephen; Crowder, Tarah; Alden, Andrew S. (2024-03)
    Corridor Q, as part of the Appalachian Development Highway System, is a 14-mile-long addition to US-460 in Buchanan County, Virginia that is currently under construction. The diverse large- and medium-sized wildlife in this area present risks for drivers, requiring an exploration of the different animal-vehicle crash (AVC) mitigation technologies available to state departments of transportation (DOTs). In addition to the wildlife typically found in the area, which already poses a threat to drivers (and vice versa), a local herd of elk was reintroduced to this area between 2012 and 2014 and are often seen along this new roadway. Elk pose additional dangers due to their large body size, herding behavior, and many other unique qualities that set them apart from other similar local species, like white-tailed deer. Elk primarily feed on low-growing vegetation such as the grasses typically used during construction to prevent roadside erosion. Soon after construction began, the elk were observed feeding on the grass along Corridor Q and tended to remain in the area. GPS collar data from tagged elk near Corridor Q reflect this observation. AVCs involving elk are costly, averaging around $73,196 in 2020 US dollars, with more recent estimates of $80,771. AVC mitigation efforts along Corridor Q must consider the unique challenges elk will present to drivers upon completion of the roadway. While many different AVC mitigation techniques are in use today, this project focuses on the feasibility of utilizing animal detection and driver warning systems (AD/DWS) as a cost-effective measure to reduce the risk of AVCs along Corridor Q. AD/DWS combine animal detection (AD) with driver warning (DW) systems to effectively alert drivers of animals near the roadway. ADS are electronic systems that use methods such as tracking motion via camera, thermal imagery, or radar, the breaking of an invisible beam, or perturbation of underground sensors, with the goal of detecting the presence of an animal near the roadway. DWS are signage systems, connected to ADS, that give drivers advanced alerts of animal detection locations. In this study, the Virginia Tech Transportation Institute researched the state of AD/DWS technologies to determine the feasibility for their use on Corridor Q, to review products that are currently available to state DOTs as off-the-shelf solutions, and to identify potential locations for a pilot study site. Interviews with subject matter experts were conducted to help guide this research. To ensure a cost-effective approach, an analysis of the partially completed portion of the roadway, and the activity of the local elk population, was conducted to observe the varying characteristics that could distinguish between areas of higher potential risk of elk-vehicle crashes (EVCs) versus areas of lower risk. In doing so, implementation of AD/DWS can be focused on the areas of higher apparent risk, keeping overall costs down while maximizing the effectiveness of these systems. AD/DWS were considered both as standalone options and in combination with other strategies to assess which method is better. As this is a new roadway, typical analysis methods used for assessing AVC mitigation strategies, such as historic crash data and traffic volume data, could not be applied. Some elk in the area were collared with GPS tracking devices, allowing for an analysis of their movement around and near the roadway. Additionally, the Virginia DOT (VDOT) provided as-built data of the new roadway, and georeferenced footage was recorded to assist with the analysis. Ultimately, the roadway was classified into distinct sections where conditions were indicative of a higher risk of EVCs based on an analysis of the data collected for this project. Details on these sections were provided to three vendors with different potential AD/DWS products that VDOT could readily purchase. These vendors provided their assessments and costs of implementing their solutions along Corridor Q.
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    Implementation and Evaluation of a Buried Cable Animal Detection System and Deer Warning Sign
    Druta, Cristian; Alden, Andrew S. (Virginia Transportation Research Council, 2019-05)
    Animal-vehicle collisions (AVC), and deer-vehicle collisions (DVC) in particular, are a major safety problem on Virginia roads. Mitigation measures such as improved fencing and location-specific driver alerts are being implemented and evaluated in Virginia and elsewhere. One of the most promising mitigation methods uses a buried cable animal detection system (BCADS) to provide roadside or in-vehicle warnings to approaching drivers based on the active presence of an animal on or near the roadway. BCADS may also be deployed in combination with exposure controls such as fencing to provide monitored, at- grade, animal crossing zones where conventional passages (e.g. culverts and bridges) are unavailable. In this study, the Virginia Department of Transportation (VDOT) in collaboration with the Virginia Tech Transportation Institute (VTTI) implemented and monitored the performance of a BCADS on a public road to provide a real-world assessment of system capabilities and possible operation issues. The BCADS has proved effective and reliable in a previous evaluation performed under more controlled and secure conditions at the Virginia Smart Road facility in Blacksburg, VA. A BCADS was installed on State Route 8 in the town of Christiansburg, VA on a road segment known to have a relatively high rate of DVCs. The system identified crossings of large- and medium-sized animals and provided data on their location along the length of the sensing cable. The BCADS and associated surveillance and communications equipment were powered by a solar photovoltaic system. A cellular modem provided for remote system monitoring and data collection. A flashing light “Deer Crossing” warning sign was installed at the site and was wirelessly linked with the BCADS to alert approaching drivers when an animal crossing was detected. Continuous BCADS and all-weather video surveillance data were collected during an 11-month period (November 2017–September 2018) to monitor animal movement, vehicle traffic, and system performance. Data on driver response to the activated warning sign during the dawn and dusk hours were collected in two separate daily sessions within a 3-month period. Study findings indicate that the BCADS is capable of detecting larger animals such as deer, and sometimes smaller animals such as coyotes, with approximately 99% reliability. The system also performed well when covered by approximately 60 cm (2 ft.) of snow. Moreover, the system was tested under various vehicle traffic conditions, and rare instances of relatively minor interferences were observed. Vehicle speed and brake light application data collected during warning sign activation showed that approximately 80% of drivers either braked or slowed in response, indicating that the sign was effective.
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    Reducing School Bus/Light-Vehicle Conflicts Through Connected Vehicle Communications
    Palframan, Kelly Donoghue; Alden, Andrew S. (Connected Vehicle/Infrastructure University Transportation Center (CVI-UTC), 2016-08-15)
    This project aimed to develop and test a concept for improving the safety of school bus transportation using connected vehicle technology. The project consisted of three key steps that led to a final road study: 1) conducting focus groups with light vehicle drivers and school bus drivers to determine what type of in-vehicle school-bus related information they would like to receive/send; 2) developing a concept of operations to accommodate driver desires; and 3) evaluating the effect of an in-vehicle message that warns of a stopped school bus ahead. In the road study, researchers evaluated each driver’s response through analysis of vehicle kinematics (speed, longitudinal acceleration, and jerk) when a bus was staged either beyond a “School Bus Stop Ahead” roadside sign or beyond the point at which a similar in-vehicle message was presented. Driver responses for each condition were compared to a baseline condition that described their driving behavior when no bus was present on the roadway. The results showed a nearly immediate response to in-vehicle messages, whereas the corresponding roadside sign messages provided little evidence of modifying driver behavior prior to visually observing a stopped school bus in the roadway.