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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
    <docs>http://blogs.law.harvard.edu/tech/rss</docs>
    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Transport Research International Documentation (TRID)</title>
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      <title>Eco-driving advisory strategies for a platoon of mixed gasoline and electric vehicles in a connected vehicle system</title>
      <link>https://trid.trb.org/View/1531016</link>
      <description><![CDATA[As electric vehicles (EVs) have gained an increasing market penetration rate, the traffic on urban roads will tend to be a mix of traditional gasoline vehicles (GVs) and EVs. These two types of vehicles have different energy consumption characteristics, especially the high energy efficiency and energy recuperation system of EVs. When GVs and EVs form a platoon that is recognized as an energy-friendly traffic pattern, it is critical to holistically consider the energy consumption characteristics of all vehicles to maximize the energy efficiency benefit of platooning. To tackle this issue, this paper develops an optimal control model as a foundation to provide eco-driving suggestions to the mixed-traffic platoon. The proposed model leverages the promising connected vehicle technology assuming that the speed advisory system can obtain the information on the characteristics of all platoon vehicles. To enhance the model applicability, the study proposes two eco-driving advisory strategies based on the developed optimal control model. One strategy provides the lead vehicle an acceleration profile, while the other provides a set of targeted cruising speeds. The acceleration-based eco-driving advisory strategy is suitable for platoons with an automated leader, and the speed-based advisory strategy is more friendly for platoons with a human-operated leader. Results of numerical experiments demonstrate the significance when the eco-driving advisory system holistically considers energy consumption characteristics of platoon vehicles.]]></description>
      <pubDate>Fri, 31 Aug 2018 10:07:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/1531016</guid>
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    <item>
      <title>Should drivers be informed about the equipment of drivers with green light optimal speed advisory (GLOSA)?</title>
      <link>https://trid.trb.org/View/1523935</link>
      <description><![CDATA[Previous research demonstrated that green light optimal speed advisory (GLOSA) affects driving behavior at signalized intersections: On the one hand, drivers assisted with GLOSA show more energy-efficient and eco-friendly driving. Following unequipped vehicles’ drivers (UVDs) also adapt their driving behavior to the assisted one. On the other hand, safety issues can be found in encounters with UVDs who also perceive assisted driving behavior negatively. Therefore, in a multi-driver simulator study (N = 60 participants sorted in groups of n = 2 UVDs), the authors tested whether informing UVDs about the GLOSA of an assisted driver results in more behavioral adaptation of UVDs to the assisted driving behavior, less safety issues, and less frustration of UVDs. Two UVDs followed a lead vehicle driven by a confederate. The confederate was equipped with GLOSA and knew when traffic lights switched from green to red and, consequently, slowed down when approaching a green traffic light. The degree of information UVDs received was manipulated: The group “no information” did not receive any information. The group “information” knew about the equipment of the assisted confederate with GLOSA and the group “detailed information” received additional information about its functionality and benefit. Results show that UVDs of the group “detailed information” adapted their driving behavior to the assisted driver. However, these UVDs also showed smaller minimum time-to-collision (TTC) values indicating safety issues. Results are discussed and implications made with regard to providing information to UVDs and to further investigate these challenges in the context of autonomous vehicles.]]></description>
      <pubDate>Thu, 26 Jul 2018 10:36:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/1523935</guid>
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    <item>
      <title>Band Finder: Vehicular Trajectory-Driven Method for Signalized Corridor Control Under Connected and Automated Vehicles (C/AV) Environment</title>
      <link>https://trid.trb.org/View/1439263</link>
      <description><![CDATA[This research presents a signal control strategy utilizing vehicular trajectory-driven optimization method. Band Finder provides individual drivers equipped with opt-in device (i.e. smartphone or tablet) with advisory speed information enabling to minimize overall travel time of the vehicle while negotiating signalized corridor. Signal status parameters such as cycle length and remaining green/red time are continuously captured. At the same time in-vehicle unit provides vehicle position information through cell-phone global positioning system (GPS) receiver. Both inputs are then used by optimization algorithm to provide optimal vehicle speed that will achieve minimal vehicle delay along the signalized corridor. To calculate the most optimal advisory speed for individual vehicles a non-linear optimization algorithm was utilized. The concept was evaluated using microsimulation in PTV VISSIM. The results for selected signalized corridor in Woodbridge, New Jersey indicate 1.2% to 5.4 % reduction in overall corridor travel time depending on different market penetration and traffic volume conditions.]]></description>
      <pubDate>Fri, 10 Mar 2017 14:38:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/1439263</guid>
    </item>
    <item>
      <title>In-car usage-based insurance feedback strategies. A comparative driving simulator study</title>
      <link>https://trid.trb.org/View/1424860</link>
      <description><![CDATA[Usage-Based Insurances (UBI) enable policyholders to actively reduce the impact of vehicle insurance costs by adopting a safer and more eco-friendly driving style. UBI is especially relevant for younger drivers, who are a high-risk population. The effectiveness of UBI should be enhanced by providing in-car feedback optimised for individual drivers. Thirty young novice drivers were therefore invited to complete six experimental drives with an in-car interface that provided real-time information on rewards gained, their driving behaviour and the speed limit. Reward size was either displayed directly in euro, indirectly as a relatively large amount of credits, or as a percentage of the maximum available bonus. Also, interfaces were investigated that provided partial information to reduce the potential for driver distraction. Compared to a control no-UBI condition, behaviour improved similarly across interfaces, suggesting that interface personalisation after an initial familiarisation period could be feasible without compromising feedback effectiveness.  Practitioner Summary: User experiences and effects on driving behaviour of six in-car interfaces were compared. The interface provided information on driving behaviour and rewards in a UBI setting. Results suggest that some personalisation of interfaces may be an option after an initial familiarisation period as driving behaviour improved similarly across interfaces.]]></description>
      <pubDate>Fri, 21 Oct 2016 16:32:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/1424860</guid>
    </item>
    <item>
      <title>Vehicular-Communications-Based Speed Advisory System for Electric Bicycles</title>
      <link>https://trid.trb.org/View/1412624</link>
      <description><![CDATA[Smart transportation, which is an important dimension of smart cities, includes both intelligent and “green” transportation solutions. Cycling, as one of the most sustainable forms of transportation, is and should be an important component of smart cities. Electric bicycles, which are the most popular electric vehicles, subscribe to this type of transportation. They have several advantages when compared with traditional bicycles but have issues that relate to battery-limited capacity and long periods of charging as well. Consequently, energy-efficient solutions for electric bicycles are of very high research interest. Research on vehicular-communications-based energy-efficient solutions for electric vehicles is still in the early stages. Among electric vehicles, electric bicycles distinguish themselves as a special class as they have different characteristics and road-related requirements. This paper proposes a novel vehicular-communications-based speed advisory system for electric bicycles. The solution recommends strategic riding (i.e., the appropriate speed) when bicycles are approaching a signaled intersection to avoid high-power-consumption scenarios. The proposed approach includes a fuzzy-logic-based wind-aware speed adaptation policy, as, among all the other vehicles, bicycles are mostly affected by wind. Experimental results based on a real testbed and extensive simulation-based testing demonstrate that, by using the proposed solution, significant energy savings are recorded. In addition, an analysis on comfort-related metrics shows that the proposed solution can also contribute to improving the cycling experience.]]></description>
      <pubDate>Wed, 29 Jun 2016 13:23:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/1412624</guid>
    </item>
    <item>
      <title>Smart roadside system for driver assistance and safety warnings: framework and applications</title>
      <link>https://trid.trb.org/View/1140801</link>
      <description><![CDATA[Newly emerging sensor technologies in traditional roadway systems can provide real-time traffic services to  drivers through Telematics and Intelligent Transport Systems (ITSs). The authors of this paper introduce a smart roadside system that utilizes various sensors for driver assistance and traffic safety warnings. Two road application models for a smart roadside system and sensors are shown: a red-light violation warning system for signalized intersections, and a speed advisory system for highways. Evaluation results for the two services are then shown using a micro-simulation method. In the given real-time applications for drivers, the framework and certain algorithms produce a very efficient solution with respect to the roadway type features and sensor type use.]]></description>
      <pubDate>Fri, 15 Jun 2012 16:03:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/1140801</guid>
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    <item>
      <title>Establishing Advisory Speeds on Freeway Exit Ramps</title>
      <link>https://trid.trb.org/View/909494</link>
      <description><![CDATA[Guidance on exit ramp advisory speeds is limited and based primarily on horizontal curvature.  The generality of the guidance provides an engineer with flexibility, but likely also results in inconsistent exit ramp advisory speed signing practices.  In addition, non-direct connectors (i.e., regular slip ramps) where there are no obvious speed-restricting alignment features, but where a speed transition is needed or desired, is not clearly addressed.  The research documented in this paper includes a survey of state department of transportation (DOT) exit ramp advisory speed signing practice as well as speed studies on exit ramps in Texas.  A range of horizontal and vertical curvatures, freeway-to-frontage-road speed differentials and distances between ramp locations and the nearest downstream cross street intersection were represented in the data.  Speed profiles were developed for each location and qualitatively examined to assess cases with good and poor agreement between ramp advisory speeds and operating speeds and to also identify speed-influencing ramp features.  A predictive model of exit ramp speeds was also estimated using the degree of horizontal curvature and the distance to the nearest downstream intersection as predictors.  Model predictions for mean truck speeds were used as inputs to a recommended procedure for determining exit ramp advisory speeds.]]></description>
      <pubDate>Thu, 18 Mar 2010 10:29:31 GMT</pubDate>
      <guid>https://trid.trb.org/View/909494</guid>
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    <item>
      <title>ENGINEERING AND TECHNOLOGY MEASURES TO IMPROVE LARGE TRUCK SAFETY: STATE OF THE PRACTICE IN VIRGINIA</title>
      <link>https://trid.trb.org/View/643241</link>
      <description><![CDATA[In response to a request by Frank S. Wolf and Jo Ann Davis of the U.S. House of Representatives, Governor Mark Warner formed a Special Task Force on Truck Safety in the fall of 2002.  The objective of the task force was to examine ways to reduce the number of crashes involving large trucks on Virginia's roads. One of the goals of this task force was to identify engineering and technology measures that have the potential to improve large truck safety.  The task force charged the Virginia Transportation Research Council with identifying engineering and technology measures that offer the potential to improve large truck safety.  A literature review of these areas was conducted, and a survey of personnel in the Virginia Department of Transportation (VDOT) was also carried out (1) to determine what measures have been implemented in Virginia, and (2) to solicit ideas for additional improvements.  Traffic control improvements, geometric design changes, and intelligent transportation systems that improve truck safety are summarized in this report, and survey respondents' recommendations for potential initiatives in engineering, enforcement, and education are also presented.  The research showed that VDOT has already taken many actions to improve large truck safety issues and that further action could be taken in several areas:  (1) VDOT's Mobility Management Division (MMD) should consider encouraging the use of dynamic truck speed advisory systems on freeway ramps where there are large numbers of rollover crashes; (2) VDOT's Location & Design Division should examine whether current design standards are adequate for the current truck fleet; (3) The MMD should consider developing guidelines for providing advance warning of the start of the red phase at intersections with limited sight distance; and (4) The MMD should reexamine whether the truck lane restrictions are producing safety improvements. In addition to these measures, VDOT should continue to pursue the initiatives that are already underway, for example, the rumble strip program and measures to improve traveler information.]]></description>
      <pubDate>Fri, 23 May 2003 00:00:00 GMT</pubDate>
      <guid>https://trid.trb.org/View/643241</guid>
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