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    <title>Transport Research International Documentation (TRID)</title>
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    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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    <language>en-us</language>
    <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>
    <image>
      <title>Transport Research International Documentation (TRID)</title>
      <url>https://trid.trb.org/Images/PageHeader-wTitle.jpg</url>
      <link>https://trid.trb.org/</link>
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    <item>
      <title>An Overview and Testing of Pedal Misapplication Systems</title>
      <link>https://trid.trb.org/View/2558336</link>
      <description><![CDATA[Performance testing was conducted to assess the effectiveness of five different pedal misapplication mitigation (PMM) systems in a simulated PMM scenario. These systems are components of advanced driver-assistance systems (ADAS), which are designed to detect and mitigate inadvertent sudden accelerator pedal misapplications by drivers. A 2023 BMW iX, 2020 Tesla Model 3, 2014 Subaru Forester, 2020 Subaru Outback, and a 2023 Subaru Ascent were tested in a simulated pedal misapplication scenario, whereby the test vehicle's accelerator was quickly depressed with a stationary pedestrian and vehicle target in front of the test vehicle. The testing involved measuring the performance of the respective vehicles' pedal misapplication mitigation systems, including when or if engine/motor output or throttle was limited or reduced, whether a forward collision warning was provided, or if the vehicle automatically engaged braking and/or braked to a stop before contact with the soft targets. Results of the five vehicles tested will be presented and compared.]]></description>
      <pubDate>Thu, 05 Jun 2025 11:59:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2558336</guid>
    </item>
    <item>
      <title>Analysis of the Impact of Traffic Environment on Driving Behavior under Real-world Driving Conditions</title>
      <link>https://trid.trb.org/View/2364726</link>
      <description><![CDATA[Automobile exhaust emission has a serious impact on the environment. Driver models are currently used to predict the amount of CO₂ emitted from vehicles, but the current models are inadequate as they do not capture the real road traffic environment. So, it is necessary to clarify the effects of traffic environments on driving operation under real-world driving conditions. In this study, how the driver’s accelerator operation, which has a large impact on CO₂ emission behavior, was analyzed. Actual driving experiments using hybrid vehicles on multiple routes on public roads and highways were conducted in the Tokyo metropolitan area, and various data on traffic environments were collected and analyzed. To conduct the analysis, a driving model of a hybrid vehicle were created and which information about the traffic environment influences the driver’s driving operation were examined. Then, a multiple regression model to predict the amount of accelerator operation by the driver was created based on this information. In order to improve the accuracy of the model, a modified version of the model that takes into account the driver’s reaction time and the decision to accelerate off was developed. Finally, the created models were fitted to test data on general roads and highways to verify their accuracy and to analyze the magnitude of the influence of each traffic environment.]]></description>
      <pubDate>Wed, 17 Apr 2024 11:29:44 GMT</pubDate>
      <guid>https://trid.trb.org/View/2364726</guid>
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    <item>
      <title>Evaluating the Effectiveness of “Smart Pedal” Systems for Vehicle Fleets</title>
      <link>https://trid.trb.org/View/2186016</link>
      <description><![CDATA[In recent years, a number of “Smart Pedal” systems have emerged, both as automotive Original Equipment Manufacturer (OEM) equipment and as third-party hardware. These “Smart Pedal” systems can be installed in vehicles with the potential to reduce fuel consumption and greenhouse gas (GHG) emissions by smoothing a driver’s acceleration patterns, with little effect on travel time or safety. This research evaluates the potential effectiveness of a select “Smart Pedal” system for improving fuel economy and reducing GHG emissions in the California Department of Transportation (Caltrans) vehicle fleet. Following a literature review, the SmartPedal™ throttle controller, currently a $299 device that effortlessly attaches to the accelerator pedal, was selected for evaluation. The SmartPedal™ device corrects the accelerator pedal signal for micro accelerations caused by the influence of artifacts in the roadway on the driver’s foot and the accelerator pedal. The SmartPedal™ technology was evaluated using six Caltrans vehicles instrumented with Global Positioning Systems (GPS) enabled Engine Control Unit (ECU) data loggers. ECU and GPS data was collected for a baseline period of vehicle operation without the SmartPedal™ device installed, followed by a period of operation with the SmartPedal™ device installed. For each test vehicle, the two datasets provided comparison data to evaluate the “Smart Pedal” technology. The amount of data in each collection period, in terms of distance, ranged from 548 miles to roughly 2,800 miles. An average fuel economy increase of up to 6.29% was observed for a vehicle with the "Smart Pedal" technology installed. The payback period for that scenario was evaluated based on the vehicle’s average monthly mileage during the study period and was about 15.76 months. Two of the six vehicles showed a small fuel economy decrease (-0.52% and -1.72%), which suggests that the effect of uncontrolled parameters is significant. This study consisted of real-world operation and the contribution of factors such as changes in payload, number of passengers, driver, accessory usage, etc., is unknown. Despite the limitations of this study, results were largely in-line with larger case studies based on fleet fuel consumption data that showed fuel economy savings in the range of 1.5% to 16.8%.]]></description>
      <pubDate>Fri, 26 May 2023 08:51:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/2186016</guid>
    </item>
    <item>
      <title>Development of Accelerator–by–wire System for Variable Valve Lift and Timing Mechanism with Three Dimensional Cam</title>
      <link>https://trid.trb.org/View/1816413</link>
      <description><![CDATA[Although various types of engines with a variable valve lift mechanism have been developed and introduced, the authors have developed a Three Dimensional Cam for Variable Valve Lift and Timing mechanism (3D Cam VVLT) as a technology to simultaneously improve fuel consumption and power. In 3D Cam VVLT, the position of 3D Cam slide decides valve lift and timing simultaneously. The 3D Cam VVLT is composed of a mechanical section including 3D Cam, an accelerator motor to drive the mechanical section, and an accelerator controller to control the cam position. The target slide position of the cam is calculated from engine speed and accelerator grip opening ratio. And the position of the cam is sifted by the accelerator motor. The cam position control requires quick response time, stability, and smoothness.]]></description>
      <pubDate>Wed, 01 Jun 2022 15:49:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/1816413</guid>
    </item>
    <item>
      <title>Development of Road Safety Information System for Active Accelerator Pedal at Curves</title>
      <link>https://trid.trb.org/View/1813347</link>
      <description><![CDATA[The “Road Safety Information System (RSIS)” addressed in this paper differs from those active and real time systems in that it controls an artificial counter force at the active accelerator pedal before the vehicle actually enters the curve to limit the cornering speed. This study aims at detecting the dangerous section on the road and warning of entering the curve. To determine dangerous section, the quality and accuracy of Digital Road Map (DRM) is very important to calculate the curve fitting on the road. The curve detection algorithm and software, which were suggested by in this paper, with effective determination were designed and developed. As a result of the research, when this method were used to find curve section it showed similar results and performances between a highway and national road.]]></description>
      <pubDate>Mon, 16 May 2022 09:34:38 GMT</pubDate>
      <guid>https://trid.trb.org/View/1813347</guid>
    </item>
    <item>
      <title>Vehicle Accelerator and Brake Pedal On-Off State Judgment by Using Speed Recognition</title>
      <link>https://trid.trb.org/View/1850164</link>
      <description><![CDATA[The development of intelligent transportation improves road efficiency, reduces automobile energy consumption, and improves driving safety. The core of intelligent transportation is the two-way information interaction between vehicles and the road environment. At present, road environmental information can flow to the vehicle, while the vehicle’s information rarely flows to the outside world. The electronic throttle and electronic braking systems of some vehicles use sensors to get the state of the accelerator and brake pedal, which can be transmitted to the outside environment through technologies such as the Internet of Vehicles. But the Internet of Vehicles technology has not been widely used, and it relies on signal sources, which is a passive way of information acquisition. In this paper, an active identification method is proposed to get the vehicle pedal on-off state as well as the driver’s operation behavior through existing traffic facilities. The research object is the commercial vehicles driving on expressways. Vehicle speed is acquired by the camera, and specific vehicle models are identified by the camera to get the relevant vehicle parameters from the vehicle model database. Combined with road environment data, the pedal on-off state will be calculated by the vehicle dynamics model. The research results show that the judgment accuracy of the pedal opening and closing state is high, and the errors are generated at the time of the pedal opening and closing state transition, and the maximum error is 0.4 s. This study provides a new method for the outside access to vehicle longitudinal operation information in the intelligent transportation system and provides a backup scheme for the information interaction of the Internet of Vehicles, which can provide a reference for the determination of traffic accident liability.]]></description>
      <pubDate>Wed, 09 Jun 2021 17:21:13 GMT</pubDate>
      <guid>https://trid.trb.org/View/1850164</guid>
    </item>
    <item>
      <title>Understanding the Trigger of Breakdown at Tunnel Sag Section and Exploring the Cause with an Improved Car-Following Model</title>
      <link>https://trid.trb.org/View/1756827</link>
      <description><![CDATA[Sag is a road section with significant vertical gradient change from downhill to uphill, which is a capacity bottleneck that easily causes traffic flow breakdown. To understand the trigger of breakdown, a typical sag section in Xiangyin Tunnel, Shanghai, is investigated using loop detector data in this paper. The empirical analysis indicates that the breakdown is mainly caused by the car-following behavior. Thus, an improved car-following model is proposed to explore the cause of breakdown by incorporating the gravity factor and several human factors (perception error and the asymmetry between acceleration and deceleration process). Combining a simple but effective lane-changing model, numerical simulations are conducted to analyze the influence of these car-following factors on traffic capacity. The results show that the proposed car-following model can describe the traffic flow characteristics of sag section, and the asymmetry is found as the critical internal cause of sag breakdown.]]></description>
      <pubDate>Fri, 26 Mar 2021 17:47:45 GMT</pubDate>
      <guid>https://trid.trb.org/View/1756827</guid>
    </item>
    <item>
      <title>Evaluation of Traffic Collision Risk and CO₂ Emission Reduction under Providing Accelerator-off Indication to Multiple Vehicles</title>
      <link>https://trid.trb.org/View/1682198</link>
      <description><![CDATA[Reduction of CO₂ emissions from vehicles becomes an urgent social issue for preventing global warming. In this study, the information provision system to provide accelerator-off indication to a driver is constructed for reducing the amount of CO₂ emissions from vehicles approaching a signalized intersection, which can be applied to multiple car-following situations. A driver could pass through the upcoming intersection at green signal or shorten the idling time during red by following the information. The information system is evaluated by driving experiments with two participants and a recorded driver by a driving simulator. From results of the experiments, although the information provision only to the lead vehicle raised a risk of traffic collision, it was clarified the information provision to the following vehicle contributed to reduce the collision risk even under multiple car-following situations. Furthermore, the information provision reduced the amount of CO₂ emissions effectively from the last following vehicle.]]></description>
      <pubDate>Wed, 22 Apr 2020 12:28:43 GMT</pubDate>
      <guid>https://trid.trb.org/View/1682198</guid>
    </item>
    <item>
      <title>A new approach to identifying the effect of diabetic peripheral neuropathy on the ability to drive safely</title>
      <link>https://trid.trb.org/View/1688919</link>
      <description><![CDATA[The purpose of this study was to estimate the potential for impaired driving performance in current drivers with diabetic peripheral neuropathy compared to healthy controls. The authors analysed, using a driving simulator, three important aspects of driving - use of the accelerator pedal, steering wheel and eye-steering coordination - to test for any differences, and then to integrate these findings to identify a unique pattern of changes in people driving with diabetic peripheral neuropathy. Patients with diabetic peripheral neuropathy displayed differences in use of the accelerator pedal compared to healthy control drivers (p < 0.05) which could be a direct consequence of their sensorimotor impairment due to diabetic peripheral neuropathy. Drivers with DPN used the more extreme high and low positions of the pedal to a greater extent than the Control group who exhibited a more graded use of the accelerator pedal over the mid-range. Eye-steering coordination was also different in drivers with diabetic peripheral neuropathy (p < 0.05) and, as it improved during the second drive, becoming closer to healthy drivers’ values, the occasional loss of control experienced during driving reduced. These insights demonstrate that diabetic peripheral neuropathy affects multiple aspects of driving performance suggesting the need for an integrated approach to evaluate the potential for driving safely in this population.]]></description>
      <pubDate>Mon, 13 Apr 2020 17:39:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/1688919</guid>
    </item>
    <item>
      <title>Functional Safety Assessment of a Generic Accelerator Control System With Electronic Throttle Control in Electric Vehicles</title>
      <link>https://trid.trb.org/View/1694893</link>
      <description><![CDATA[This report describes research assessing the functional safety of accelerator control systems with electronic faults such as errant electronic throttle control signals,  following an industry process standard. This study focuses specifically on errant signals in motor vehicles with electric propulsion. This study follows   the concept phase process in the ISO 26262 standard and applies a hazard and operability study, functional failure mode and effects analysis, and systems theoretic process analysis methods. In total, this study identifies 7 vehicle-level safety goals and 202 ACS/ETC system safety requirements (an output of the ISO 26262 and STPA processes). This study uses the results of the analysis to identify potential opportunities to improve the risk assessment approach in the ISO 26262 standard.]]></description>
      <pubDate>Fri, 27 Mar 2020 09:01:50 GMT</pubDate>
      <guid>https://trid.trb.org/View/1694893</guid>
    </item>
    <item>
      <title>Functional Safety Assessment of a Generic Accelerator Control System with Electronic Throttle Control in Hybrid Electric Vehicles with a Gasoline Internal Combustion Engine</title>
      <link>https://trid.trb.org/View/1662854</link>
      <description><![CDATA[This report describes the research effort to assess the functional safety of accelerator control systems with electronic faults, such as errant electronic throttle control signals, following an industry process standard. This study focuses specifically on errant signals in hybrid electric vehicles (HEVs) that combine an electric powertrain subsystem with a gasoline internal combustion engine. Three common HEV architectures are considered, the series HEV, parallel HEV, and series-parallel HEV. This study follows the concept phase process in the ISO 26262 standard and applies a hazard and operability study, functional failure modes and effects analysis, and systems theoretic process analysis methods. In total, this study derives 8 vehicle-level safety goals and 260 safety requirements (an output of the ISO 26262 and STPA processes). This study uses the results of the analysis to identify potential opportunities to improve the risk assessment approach in the ISO 26262 standard.]]></description>
      <pubDate>Fri, 15 Nov 2019 13:45:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/1662854</guid>
    </item>
    <item>
      <title>High Performance Motor and Inverter System for a Newly Developed Electric Vehicle</title>
      <link>https://trid.trb.org/View/1560869</link>
      <description><![CDATA[This paper describes a newly developed motor and inverter system with maximum torque of 320 Nm and maximum power of 110 kW for a 2018 model year EV. The system achieves this performance with no increase in size from the previous 2013 model year system with maximum torque of 254 Nm and maximum power of 80 kW.         The specific features of the new system described in this paper are summarized below.         A new inverter power module that adopts a direct cooling structure produces higher current density than the previous model. The designs of components experiencing structural and electrical variation that affects heat generation by the power semiconductors were confirmed. Furthermore, the motor temperature is estimated for thermal protection. These features allow for control logic that can optimally manage the temperatures of the power semiconductors and the motor to facilitate the high torque performance of the system.         The motor voltage management has also been optimized in order to reduce the current level and thereby contributes to the system’s high power performance and high efficiency. The motor also adopts magnets with reduced heavy rare earth elements. This improves heat resistance and obtains resource savings.         In addition, one of the novel features of the new EV is e-Pedal that provides not only deceleration but also stopping by operating only the accelerator pedal. This is achieved by motor control logic of the motor and inverter system that generates the optimum motor torque in response to each road grade.       ]]></description>
      <pubDate>Tue, 22 Oct 2019 14:38:58 GMT</pubDate>
      <guid>https://trid.trb.org/View/1560869</guid>
    </item>
    <item>
      <title>Functional Safety Assessment of a Generic Accelerator Control System With Electronic Throttle Control in Fuel Cell Hybrid Electric Vehicles</title>
      <link>https://trid.trb.org/View/1592131</link>
      <description><![CDATA[This report describes research assessing the functional safety of accelerator control systems with electronic faults, such as errant electronic throttle control signals, following an industry process standard. This study focuses specifically on errant signals in motor vehicles with fuel cell hybrid electric propulsion. This study follows the concept phase process in the ISO 26262 standard and applies a hazard and operability study, functional failure mode and effects analysis, and systems theoretic process analysis methods. In total, this study identifies 7 vehicle-level safety goals and 202 ACS/ETC system safety requirements (an output of the ISO 26262 and STPA processes). This study uses the results of the analysis to identify potential opportunities to improve the risk assessment approach in ISO 26262.]]></description>
      <pubDate>Mon, 25 Mar 2019 09:54:30 GMT</pubDate>
      <guid>https://trid.trb.org/View/1592131</guid>
    </item>
    <item>
      <title>Relationship Between Brain Activity and Real-Road Driving Behavior: A Vector-Based Whole-Brain Functional Near-Infrared Spectroscopy Study</title>
      <link>https://trid.trb.org/View/1505475</link>
      <description><![CDATA[Automobile driving requires multiple brain functions. However, the brain regions related to driving behavior are unknown. Therefore, the authors measured activity of the frontal, parietal and occipital lobes during driving using functional near-infrared spectroscopy (fNIRS). Cortical activation patterns were examined in relation to driving behaviors, such as steering motion, accelerator pedal motion, and speed control. Six healthy adults participated in the experiment. Cerebral oxygen exchange (COE) was calculated based on the oxyhemoglobin and deoxyhemoglobin concentrations measured by fNIRS. The COE and driving behavior data were collected every 1 m and averaged for all subjects. Functional NIRS data for all 98 channels were extracted using principal component analysis. Similarity between extracted components and driving behaviors were confirmed by |cosine similarity|>0.3. Among the factors with confirmed similarity, the authors identified brain regions with high principal component loading (|PCL|>0.4). Among the 16 COE factors extracted, COE factor 1 and factor 5 exhibited similarity with steering motion (cosine similarity: factor 1, -0.538; factor 5, 0.551). The PCLs of COE factor 1 and factor 5 were high in the frontal lobe (Brodmann areas [BAs] 9, 8, and 4/3) (PCL>0.8). COE factor 6 exhibited a similarity with accelerator pedal motion (cosine similarity: 0.369), and the PCL of COE factor 6 was highest in the parietal lobe (BA7) (PCL= -0.62). Speed control did not exhibit similarity with any COE factor. These findings will contribute to the selection of brain measurement areas when fNIRS is used for vehicle driving assessment.]]></description>
      <pubDate>Mon, 26 Mar 2018 09:19:21 GMT</pubDate>
      <guid>https://trid.trb.org/View/1505475</guid>
    </item>
    <item>
      <title>Development and Evaluation of a Distance Control Assist System with an Active Accelerator Pedal</title>
      <link>https://trid.trb.org/View/1430373</link>
      <description><![CDATA[A Distance Control Assist System (DCA) aiming at facilitating the driver maintaining a following distance to a lead vehicle in congested traffic was developed. The DCA imposes active force to the driver’s foot to urge him or her to release the accelerator pedal as well as decelerates automatically when the host vehicle comes too close to a lead vehicle. This paper introduces the system description and a field test conducted to evaluate effectiveness of the DCA. As a result of the field test, comparison of the driver performances between with and without the DCA showed that numbers of braking by the drivers were decreased, and comparison of NASA-TLX scores showed subjective workload was reduced by the DCA. These results suggested that the DCA can contribute to mitigation of the driver’s workload while following situations.       ]]></description>
      <pubDate>Thu, 30 Nov 2017 17:17:24 GMT</pubDate>
      <guid>https://trid.trb.org/View/1430373</guid>
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