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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
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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>
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      <link>https://trid.trb.org/</link>
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    <item>
      <title>A new pilot jet lag risk assessment scale (JLRAS) and its application</title>
      <link>https://trid.trb.org/View/2728052</link>
      <description><![CDATA[Few subjective survey scales or questionnaires are available for assessing jet lag risk in pilots. The Pilot Jet Lag Risk Assessment Scale (JLRAS) was administered to a cohort of Chinese airline pilots flying across multiple time zones. Its validity was assessed against data from an actigraphy bracelet, the Karolinska Sleepiness Scale (KSS), and the Samn-Perelli (SP) scale. The JLRAS demonstrated excellent discriminative ability. It comprises four dimensions - sleep, psychological fatigue perception, self-assessment of competence, and jet lag perception - that collectively capture the combined risk of jet lag symptoms in pilots from a psychological perspective after completing a trans-meridian flight. Concurrent validity was established using external measures: the KSS and SP scales corroborated the psychological fatigue dimension, while actigraphy-based sleep metrics validated the sleep dimension. This study presents and validates a new scale for evaluating jet lag risk in pilots, offering a standardized and well - validated tool that can be widely adopted by the pilot community operating across time zones.]]></description>
      <pubDate>Fri, 14 Aug 2026 15:04:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2728052</guid>
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    <item>
      <title>Differential sensitivity of self-reported driving and collision measures to aspects of shiftwork, sleep, and fatigue</title>
      <link>https://trid.trb.org/View/2720827</link>
      <description><![CDATA[Sleepiness, fatigue, and shiftwork are three aspects of daily life that might affect individuals’ safety when driving. Driving behaviors are commonly assessed via self-report measures. In this study, different self-reported measures of driving behaviors are compared to test their sensitivity to measures of sleepiness, fatigue, and night shiftwork. Police shiftworkers from English forces completed a survey that included questions about shiftwork, sleep, fatigue, and included three measures of driving behavior: The Driver Behavior Questionnaire (DBQ − Lawton et al., 1997; Reason et al., 1990), Smith’s (2016) measures of poor and fatigued driving, and self-reported collision frequencies. Hierarchical regressions confirmed that the driving behavior measures were differentially sensitive to aspects of sleepiness, fatigue, and shiftwork. Responses to Smith’s components of driver fatigue and risk taking, and questions on collision frequencies, but not responses to the DBQ, could be predicted from the proportion of night shifts a person worked. Conversely, only the DBQ was sensitive to fatigue as a predictor of poor driving. All measures were sensitive to aspects of sleepiness and the extent to which it predicted driving outcomes (Adj. R2) differed between scales. Self-reported collision data was least sensitive to contexts of shiftwork, sleepiness and fatigue and such data should be used cautiously to explore effects of sleep and shiftwork on driving behavior. The present findings highlight the importance of using scales that are sensitive to the context of investigations (e.g., shiftwork). Relying on inappropriate scales could lead to the underreporting of poor driving behaviors in sleepy and shiftworking drivers.]]></description>
      <pubDate>Tue, 21 Jul 2026 09:49:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2720827</guid>
    </item>
    <item>
      <title>Creating the London night-worker geodemographic classification</title>
      <link>https://trid.trb.org/View/2646122</link>
      <description><![CDATA[This paper aims to provide a more comprehensive understanding of the geography of night working in London (United Kingdom). Around a quarter of London’s workforce is employed in the evening and night-time economy, working between the hours of 6 pm and 6 am. Compared to daytime workers, there is limited public information on where these workers are located, how they travel, and what amenities they rely on during work hours. To address this gap, we combine official employment statistics with mobile phone footfall data to develop the London Night-Worker Classification. This new small-area geodemographic classification captures key characteristics of night-working patterns, offering a spatial perspective on night-time employment to support more informed decisions in transport, planning, and worker wellbeing.]]></description>
      <pubDate>Wed, 22 Apr 2026 16:15:35 GMT</pubDate>
      <guid>https://trid.trb.org/View/2646122</guid>
    </item>
    <item>
      <title>Mixed Methods Case Study of Bus Operator Work Preferences at the Chicago Transit Authority</title>
      <link>https://trid.trb.org/View/2684225</link>
      <description><![CDATA[Transit agencies in the U.S. have faced significant challenges in recruiting and retaining bus operators, both before and after the COVID-19 pandemic. Bus driving often involves working long hours and performing physically demanding tasks involved with operating a large commercial vehicle, while constantly interacting with the public. The physically and mentally demanding nature of the job, coupled with increased personal safety concerns, further exacerbates retention issues. Additionally, a restrictive working environment and a lack of scheduling flexibility, coupled with competitive opportunities in ride-hailing and delivery services, contribute to high turnover rates. Existing research has not sufficiently addressed the role of work scheduling in affecting bus operators’ quality of life and retention rates. In this study, we conducted focus group studies with 213 Chicago Transit Authority bus drivers and analyzed their stated preferences about work schedule characteristics, combining this analysis with revealed preference data on duty selection to gain comprehensive insights into shift desirability. Overall, drivers’ top priorities include getting enough pay hours, reducing the incidence of split shifts, having sufficient recovery time built into the schedule, avoiding relief points outside of garages, and getting weekends off. Relief points, often called reliefs, are the points where operators start or end their shifts. These findings are translated into a series of scheduling recommendations to improve bus operators’ quality of life. Specifically, the recommendations focus on increasing the use of 4-day work weeks and rostering to allow for greater consistency, more days off, and longer duties for operators.]]></description>
      <pubDate>Thu, 26 Mar 2026 13:38:05 GMT</pubDate>
      <guid>https://trid.trb.org/View/2684225</guid>
    </item>
    <item>
      <title>Dynamic evolution of high-speed railway driver fatigue across scheduling shifts – a simulator study in China</title>
      <link>https://trid.trb.org/View/2613683</link>
      <description><![CDATA[Scheduling significantly contributes to fatigue among high-speed rail (HSR) drivers, impacting both driving performance and safety. This study aims to analyse distinctiveness and evolutionary patterns of driver fatigue across different scheduling shifts, leveraging an HSR simulator and wearable devices. Through an extensive statistical examination, differences in most heart rate variability features were identified across shifts. The evolution of self-reported fatigue and physiological fatigue was investigated using a Markov chain and a hidden Markov model (HMM) that is extended using softmax regression, respectively. Results indicated a similarity in the initial fatigue state distribution and evolution trends across shifts, albeit with varying degrees of fluctuation. Morning shifts exhibited a higher likelihood of fatigue accumulation. The study revealed that even adequate pre-rest did not entirely counterbalance the impact of circadian rhythms. These findings may contribute to comprehending the temporal dynamics of driver fatigue evolution and offer insights for optimizing driver scheduling practices.]]></description>
      <pubDate>Mon, 26 Jan 2026 14:44:19 GMT</pubDate>
      <guid>https://trid.trb.org/View/2613683</guid>
    </item>
    <item>
      <title>Work Schedules, Fatigue and Regeneration in Modern Aviation</title>
      <link>https://trid.trb.org/View/2572692</link>
      <description><![CDATA[The discussion on fatigue, long working hours and shift systems focused on single operator workload and stress up to now. Options based on modern technologies with semi-automated work have not been fully elaborated. Especially the combination of double-operator task sharing with semiautomated work options call for new solutions, especially with respect to task and break sharing. In addition, psychological concepts have been restricted to fatigue, biological rhythms, and workload. Regeneration and the role of breaks has received only marginal attention. This is in contrast to the fact, that stress-strain, work schedules, breaks and regeneration should always be viewed jointly. Thirty years of experience with the recovery-stress-concept are discussed with respect to work design and problems of regeneration, and recovery for operators in aviation. Under-recovery and the problem of efficient breaks as well as solutions based on the recovery-stress balance will be discussed. Concepts like detachment from work, coping and debriefing, as well as under-recovery and skills from mental training will be mentioned and elaborated with respect to requirements for new work designs in aviation. The SCS-Tool (subjective scaling of critical situations) will be proposed as an easy monitoring and debriefing option for new technologies at the workplace.]]></description>
      <pubDate>Mon, 08 Dec 2025 15:19:03 GMT</pubDate>
      <guid>https://trid.trb.org/View/2572692</guid>
    </item>
    <item>
      <title>Work performance measurement of visual inspectors in the automotive industry by considering ergonomic factors</title>
      <link>https://trid.trb.org/View/2611435</link>
      <description><![CDATA[Background:Visual inspection workers are always performing under various ergonomic factors and are more vulnerable to the effects of physical and organizational aspects, since their work deals highly with cognitive functions and the impact of ergonomic factors has to be identified in automotive industries to improve work performance.Objective:To study the combined effect of ergonomic factors that may have an impact on the performance of visual inspection workers in the automotive industry.Methods:In this experimental study combined factors such as postures (standing, sitting, Sit-stand) and work shifts (A shift, B shift, C Shift) have been studied at three levels. The study was conducted among selected employes (n?=?10) in the automotive manufacturing industry in 2023. During the study, the visual inspectors’ work performance was measured using the error study, and the cognitive functions of visual inspectors’ were evaluated by taking the Digit Symbol Substitution Test (DSST).Results:The study established that postures significantly impact work performance at 40.08% and cognitive functions at 36.25%. Work shifts significantly impact work performance with 18.18% and cognitive functions with 26.62% of visual inspectors’ in the automotive industry. The combined effect of postures and work shifts has significantly impacted the visual inspectors’ performance with 13.29% on work performance and 10.12% on cognitive functions.Conclusions:This study draws the inference that individual and combined factors (Posture and Work shift) both possess a significant impact on the work performance and cognitive functions of visual inspectors’ in the automotive manufacturing industry.]]></description>
      <pubDate>Fri, 24 Oct 2025 08:47:17 GMT</pubDate>
      <guid>https://trid.trb.org/View/2611435</guid>
    </item>
    <item>
      <title>The Association Between Shift Work and Lipid Health in Chinese Railway Workers: A Longitudinal Analysis of 6 Years</title>
      <link>https://trid.trb.org/View/2563839</link>
      <description><![CDATA[This article reports on a study undertaken to evaluate the longitudinal association between shift work and lipid health among railway workers (n = 1,126).  Data was analyzed from at least two physical examinations (between 2016 and 2021) and included triglycerides, total cholesterol, low-density, and high-density lipoprotein cholesterol.  Dylipidemia was based on Chinese definitions and the authors identified the trajectory of lipid health, establishing three categories:  persistently low (40.8%), persistently moderate (34.3%), and persistently high (24.9%).  Their analyses showed that those railway workers on dedicated/pooled charter shifts were more likely to be in the persistently low dyslipidemia category.  They conclude that nonregular day shift work is associated with lower levels of lipid profile and lower risk of lipid abnormalities.  The authors include a brief discussion of how their results differ from previous studies on dyslipidemia in other occupational groups in China.]]></description>
      <pubDate>Fri, 11 Jul 2025 10:00:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2563839</guid>
    </item>
    <item>
      <title>Multi-shift drayage planning for batches of containers: A branch-and-benders-and-price algorithm</title>
      <link>https://trid.trb.org/View/2544435</link>
      <description><![CDATA[This paper investigates a multi-shift drayage planning problem arising from container truck transportation across multiple terminals within a port area. The authors consider it at the tactical planning level and determine the optimal truck workload for each shift. The main distinction between their problem and others is the incorporation of multiple shift planning, handling container transportation requests—each consisting of a batch of containers with the same origin and destination—and accounting for their completion times. A mixed integer programming model is proposed to minimize total transportation completion time. And to solve large-scale instances, they develop a Branch-and-Benders-and-Price algorithm. This approach not only decomposes the problem into a series of manageable sub-problems but also divides the workload determination into two tractable steps: one for assigning workloads to shifts and another for verifying the feasibility of these assignments. Unlike the common Branch and Price, their approach maintains a subset of variables as integers while allowing the remaining variables to be continuous, significantly improving the lower bound and enabling obtaining optimal solutions efficiently. They validate the proposed approach via random instances and real-world cases. The results demonstrate that their approach outperforms a solver and a Branch and Price. They also apply their method to a real-world case involving Roll-On/Roll-Off terminal cargo transfer, which shares key similarities with the problem at hand, thereby further broadening the scope of their approach’s applicability. And, sensitivity tests are conducted to demonstrate the robustness of their approach against variations in problem settings.]]></description>
      <pubDate>Thu, 15 May 2025 10:12:18 GMT</pubDate>
      <guid>https://trid.trb.org/View/2544435</guid>
    </item>
    <item>
      <title>Rethinking ‘discretionary’ travel: The impact of night and evening shift work on social exclusion and mobilities of care</title>
      <link>https://trid.trb.org/View/2527128</link>
      <description><![CDATA[Night and evening shift workers play critical roles in the modern economy, yet the mobility implications of working at these times is understudied. Shift workers’ schedules are mis-aligned with the schedules of their families and most of society, complicating their contribution to household-serving travel and their participation in social activities. This study models the effects of working nights and evenings on household-serving and social trips, including social trips with other householders. The author applies binary logistic and Poisson regression with block bootstrapping to the 2017 U.S. National Household Travel Survey, which contains records for over 160,000 travelers recruited through stratified random sampling of U.S. addresses. Night and evening shift workers are less likely to make a trip for recreation, visiting others, or eating out, on days that they work. Shift workers are also less likely to conduct household-serving trips on days that they work, and this effect is amplified for women with regards to errands and shopping. When people work impacts what activities they can participate in, including whether they join in social activities with other household members. These results demonstrate the limitations of understanding social trips as ‘discretionary,’ in that these activities are still subject to coupling constraints that make it difficult for some groups of people to participate. These impacts hold negative implications for the mental health and wellbeing of shift workers.]]></description>
      <pubDate>Thu, 17 Apr 2025 16:55:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/2527128</guid>
    </item>
    <item>
      <title>Promoting healthy and safe driving: Physiological and psychological evaluation of truck drivers for individualized shift and route planning</title>
      <link>https://trid.trb.org/View/2531121</link>
      <description><![CDATA[There is a worldwide shortage of truck drivers, and the situation will likely worsen in the coming years. Truck driver health and safety must be improved to counteract this shortage, as this could increase driver availability. A structured literature review was first conducted to identify individual and psychological factors in various vehicle-related application areas that influence drivers’ performance, health, and safety. It encompassed aspects such as the prevailing chronotype, stress levels, and the associated psychological factors of attention and concentration performance. Then, a complementary field study involving professional truck drivers was conducted to measure both physiological and psychological indicators during their daily routines. It found differences in both attentional performance and perceived stress that varied by the type of shift. The further inclusion of truck drivers’ chronotypes showed that these individual differences impact attention and concentration performance, which influence stress. These results enable personnel management or distribution planners to account for individual factors when preparing truck drivers’ work schedules. Shift and route plans considering individual factors could improve truck drivers’ health and safety, positively influencing their availability.]]></description>
      <pubDate>Mon, 14 Apr 2025 17:08:46 GMT</pubDate>
      <guid>https://trid.trb.org/View/2531121</guid>
    </item>
    <item>
      <title>Mixed integer linear programming model for a multi-depot arc routing problem with different arc types and flexible assignment of end depot</title>
      <link>https://trid.trb.org/View/2493215</link>
      <description><![CDATA[This article addresses a street sweeping problem that extends the class of multi-depot arc routing problem by integrating a flexible assignment of end depot for each working shift. A unique team of specialized vehicles starts each shift from a depot, visits the required arcs and returns at the end of each shift to a depot. The service in the next shift should start from the end depot of the previous one. An additional new constraint imposes that the highway arcs must be serviced during a night shift while all others arcs (boulevard, street, etc.) can be swept during both day and night. The aim of this arc routing problem is to find optimal shifts that satisfy these two practical aspects, along with other constraints such as maximum shift duration. The problem is motivated by a real-world application that has not been previously studied in the literature. A mixed integer linear programming model is formulated with the objective of minimizing the total travel time and tested on newly generated instances based on Cordeau's multi-depot vehicle routing problem instances. The results show a generation of total travel time savings up to 12 % compared to the single depot arc routing problem.]]></description>
      <pubDate>Mon, 10 Feb 2025 09:30:52 GMT</pubDate>
      <guid>https://trid.trb.org/View/2493215</guid>
    </item>
    <item>
      <title>Improving attractiveness of working shifts for train dispatchers</title>
      <link>https://trid.trb.org/View/2459170</link>
      <description><![CDATA[The authors consider the problem of scheduling shifts for train dispatchers: given legal and operational constraints, the dispatching work in geographical areas should be assigned to dispatchers. In previous work, the authors presented an integer-programming framework for scheduling one-day shifts, aiming to minimize the number of dispatchers needed. Here, the authors present a stronger formulation for this problem. Moreover, the authors handle several quality aspects of the resulting shifts: the authors exclude undesirable start times and too short shifts; and the authors present four approaches to handle unnecessary changes in the dispatcher-area assignments. With an experimental performance-evaluation, the authors show that the stronger model significantly reduces the runtime in all but one instance, with an average decrease of 82.2 percent. The authors can solve all real-world-sized instances in less than 10 seconds. Moreover, the authors compare the four handover-approaches on instances with different temporal and geographical resolutions, and show that the two promising approaches allow us to solve a real-world-sized instance.]]></description>
      <pubDate>Mon, 27 Jan 2025 15:39:53 GMT</pubDate>
      <guid>https://trid.trb.org/View/2459170</guid>
    </item>
    <item>
      <title>Spatiotemporal Analysis of Electric Taxi Service Mode Based on Gaussian Mixture Model</title>
      <link>https://trid.trb.org/View/2475456</link>
      <description><![CDATA[Vehicle electrification is important for promoting green transportation. Using a large-scale Electric Taxi (ET) operation data set in Shenzhen, the study explored the spatiotemporal distribution of ETs’ service mode considering different shift modes. Specifically, segmenting the time sequence of ET orders into different work slices (WSs), Gaussian mixture models were used to cluster these WSs of single-shift and double-shift ETs into 9 and 12 spatiotemporal feature-based clusters, respectively. Subsequent analysis was conducted on the service modes combined by different clusters for both shifts. Results show the following: (1) ETs operated in central core areas often receive higher fares. (2) Implementing service mode combining 2 or 3 clusters could help increase the fare for ET drivers. (3) Double-shift drivers in core areas may experience fare imbalance and potential charging peak at shift hours. The outcome offers insights for customizing ET operation strategies, such as subsidy design and order matching algorithms.]]></description>
      <pubDate>Tue, 24 Dec 2024 16:44:42 GMT</pubDate>
      <guid>https://trid.trb.org/View/2475456</guid>
    </item>
    <item>
      <title>Railway security personnel scheduling problem considering personnel preferences</title>
      <link>https://trid.trb.org/View/2431608</link>
      <description><![CDATA[This study discusses the shift scheduling problem of security personnel, considering personnel preferences for 43 stations on four lines of the Ankara metro, which carries more than 10 million passengers monthly. Firstly, 751 security personnel have been distributed to four lines of the Ankara metro according to personnel needs. A survey is conducted among the personnel at the stations on each line, and they are asked to rank the stations they want to work at according to their preferences. The station preferences of the personnel are listed with increasing scoring in parallel with the order of preference. A goal programming model has been used to assign personnel to stations, considering personnel needs, operating rules, and personnel preference scoring at the stations. The main objective of the model is to minimize the personnel-preferred station scoring. As a result of the solution of the mathematical model solved separately for four lines, 24.23% of the personnel for the M1 (Kızılay-Batıkent) line, 27.94% of the personnel for the M2 (Kızılay-Koru) line, 23.32% of the personnel for the M3 (Batıkent-Sincan) line, and 35.85% of the personnel for the M4 (Keçiören-Şehitler) line, are assigned to their first three preferences. Moreover, an important balance is achieved between personnel preferences. Few studies are in the literature on railway security personnel scheduling, and no studies that consider personnel preferences have been found in this field. This study, which considers personnel preferences, contributes to the literature.]]></description>
      <pubDate>Mon, 07 Oct 2024 16:55:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/2431608</guid>
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