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    <title>Transport Research International Documentation (TRID)</title>
    <link>https://trid.trb.org/</link>
    <atom:link href="https://trid.trb.org/Record/RSS?s=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" rel="self" type="application/rss+xml" />
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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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    <item>
      <title>Study on the Stress Transfer Principle of Closed Cavity Thin-Walled Components in Assembled Underground Structures</title>
      <link>https://trid.trb.org/View/2019104</link>
      <description><![CDATA[For the first time in China, precast assembly technology was used to build the large underground stations and a new kind of closed cavity thin-walled component was developed to reduce the weight of the structure in Changchun Metro Line 2. This paper set up a numerical model for the typical straight closed cavity thin-walled component and conducted a parameter study to obtain the influence of the end plate on stress transfer of the component. The result shows that the best performance is achieved when the ratio of the end plate thickness to height is 0.43 and over-thick end plate does not improve the force performance significantly.]]></description>
      <pubDate>Fri, 30 Dec 2022 09:16:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/2019104</guid>
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    <item>
      <title>Predicting Passenger Volumes of Metro Stations Based on Random Forest Regression</title>
      <link>https://trid.trb.org/View/2019135</link>
      <description><![CDATA[Metro stations’ passenger volumes are important parameters for planning and design. In this paper, a random forest regression model is proposed to predict the inbound/outbound passenger volume and the total passenger volume of each station during the workday, based on the Metro AFC data and POI data of Shanghai, China. The dependent variables include the inbound/outbound and total passenger volumes of each metro station, and the independent variables include the relative proportion of 15 types of POI data. The results show that the R-square values of the inbound and total volumes is 0.94, and the outbound volume is 0.95. The average relative error of the model (≈20%) indicates that its prediction accuracy is good. Moreover, the variable importance method based on permutation was used to analyze the factors affecting the passenger volumes of stations. This study’s findings are useful for metro station planning and design, and metro operation organization.]]></description>
      <pubDate>Fri, 16 Dec 2022 09:41:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2019135</guid>
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    <item>
      <title>Phase Optimization Based Green Wave Coordination Control Method for Trunk Lines</title>
      <link>https://trid.trb.org/View/2019134</link>
      <description><![CDATA[In order to improve the effect of green wave coordination control on urban arterials, this paper proposes an arterial green wave coordination control method based on signal phase optimization at intersections. The method uses Webster’s signal cycle algorithm to increase the adjustment zone of phase difference between adjacent intersections on the arterial by optimizing the signal phase composition of each intersection on the arterial; and uses the number solution method to determine the phase difference between adjacent intersections, and then determines the arterial coordination control scheme. The case analysis shows that the optimization scheme effectively improves the vehicle delay time, the number of vehicles in queue, and the number of stops.]]></description>
      <pubDate>Fri, 16 Dec 2022 09:41:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2019134</guid>
    </item>
    <item>
      <title>Identification and Prediction of Urban Travel Hot Spots with a Potential-Based Approach: A Case Study for New York City</title>
      <link>https://trid.trb.org/View/2019133</link>
      <description><![CDATA[Identifying and predicting urban travel hot spots are crucially important for urban planning and safety management. Recently, the increasing availability of taxi data contributes to the exploration of travel characteristics of inhabitants. In this study, the taxi data of New York City is employed to generate the vector field of human mobility. The key property of vector field potentials is used to quantify the attraction of different locations and identify urban travel hot spots. In addition, the normalized potentials were used to generate the Markov chain model and predict urban travel hot spots. Experimental results indicate that it is feasible to identify urban travel hot spots with the potential-based method, and urban travel hot spots can be predicted using the Markov chain model with normalized potentials as inputs.]]></description>
      <pubDate>Fri, 16 Dec 2022 09:41:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2019133</guid>
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    <item>
      <title>Evaluating the Road Network Capacity of Shanghai with the Macroscopic Fundamental Diagram</title>
      <link>https://trid.trb.org/View/2019132</link>
      <description><![CDATA[As the world rapidly urbanizes, traffic congestion has become a significant global problem. Using the macroscopic fundamental diagram (MFD) to evaluate the traffic capacity of urban networks is advantageous because it can present a complete picture of the traffic conditions of a particular road network. This paper studied the road network capacity of a 15.4 km² region in Shanghai using the MFD based on microscopic traffic simulation with projected increased and decreased travel demands. We estimated the OD matrix using traffic count data in Shanghai from 2011 to 2020, and carried out traffic simulations with travel demands ranging from 25% to 400% of the 2020 morning peak hour. Results showed that the areas analyzed reached similar average peak flows per lane at different critical densities per lane. The traffic capacity and critical accumulation per area obtained correspond with results from major world cities, indicating the healthy capacity of the road network.]]></description>
      <pubDate>Fri, 16 Dec 2022 09:41:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2019132</guid>
    </item>
    <item>
      <title>Analysis of the Influence of Built Environment on Peak Hour Travel Demand of Youth Group Based on Cell Phone Signaling Data: A Case Study of Shanghai</title>
      <link>https://trid.trb.org/View/2019131</link>
      <description><![CDATA[There is a close interaction between the urban built environment and the spatial behavior characteristics of individuals in time. Youths are an important group in urban development, and their travel affects the overall efficiency of the city. This study uses cell phone signaling data and POI data to build linear regression models and geographically weighted regression models, respectively, to analyze the impact of built-up environment on the peak hour travel of youth groups. It is found that there are similarities in the morning and evening peak models, and there are significant differences in travel time and space; residential population and job density have significant effects on the travel of the youth population, and commuting travel is still the most important which exists a separation of jobs and residences; construction of new cities in Shanghai is steadily advancing, and accessibility and equity of urban services and facilities need to be strengthened.]]></description>
      <pubDate>Fri, 16 Dec 2022 09:41:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2019131</guid>
    </item>
    <item>
      <title>Enhancing the Discrete Choice Model of Residential Location with Big Data and Representation Learning</title>
      <link>https://trid.trb.org/View/2019130</link>
      <description><![CDATA[The coordination of transport and land use is essential for a competitive and sustainable urban development. Residential location choice is one decisive factor which influences transportation and land use layout. Based on multi-source big data, representation learning is used to enhance the accuracy of the machine learning method, discrete choice model. The utility function is divided into knowledge-driven and data-driven. The knowledge driven part estimates interpretable parameters. Data-driven automatically discovers a good utility specification from available data. It is then applied to the north zone of Zhongguancun Science Park in Beijing to forecast the evolution trend of residential location choice based on land use polices. The general trend verifies the objectives of the government plan to enhance the attractiveness of advanced industries and promote job-resident balance. The proposed approach to discrete choice modeling by integrating representation learning in the formulation provides a distinct tool for the urban spatial policy makers.]]></description>
      <pubDate>Fri, 16 Dec 2022 09:41:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2019130</guid>
    </item>
    <item>
      <title>Calibration of Route Choice Preferences and Dynamic Traffic Assignment Model in China Using Automated Vehicle Identification Data</title>
      <link>https://trid.trb.org/View/2019129</link>
      <description><![CDATA[Automated vehicle identification (AVI) data has been prevalent in China due to high coverage of policy camera. Longitudinal AVI data has the potential to help interpret commuters’ route choice behavior and further help to build a dynamic traffic assignment (DTA) model of large-scale road networks. With the help of DTA model, the authors can understand the influence of the evolution of route choice preference on traffic operation efficiency. In this study, the authors adopted the finest AVI data set so far in Shanghai, China, and performed route choice preference classification. With AVI trajectories and multi-source traffic data, a DynusT DTA model was built and calibrated from the both sides of supply and demand. Then the authors investigated the impact of route choice preferences. It is found that if all commuters followed suggestions of user equilibrium route choice, the total travel time across the entire network would be saved by around 35%, which is significant.]]></description>
      <pubDate>Fri, 16 Dec 2022 09:41:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2019129</guid>
    </item>
    <item>
      <title>Electric Vehicle Routing with Soft Time Windows</title>
      <link>https://trid.trb.org/View/2019127</link>
      <description><![CDATA[Due to the new policies regarding greenhouse gas emission, logistics enterprises have already integrated electric vehicles (EVs) into their fleets, especially for delivery services in the center of large cities. Due to the limited battery capacity of EVs, visits to charging stations need to be considered in the routes. This paper addresses the electric vehicle routing problem with soft time windows (EVRPSTW). The problem is to determine the optimal routes of a homogeneous fleet of EVs, to minimize the total cost, which includes the number of EVs, the distance traveled, the charging time, and the time window penalty. Since the vehicle routing problem is NP-hard, a simulated annealing (SA) based heuristic method was developed and its efficacy was demonstrated over a direct solution of the mixed integer linear programming formulations of the underlying problems using commercial software (CPLEX). The computational experiment reveals the efficacy of the method.]]></description>
      <pubDate>Fri, 16 Dec 2022 09:41:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2019127</guid>
    </item>
    <item>
      <title>An Assessment of Driverless-Oriented Road Network Vulnerability under Disruptions</title>
      <link>https://trid.trb.org/View/2019126</link>
      <description><![CDATA[Various disruptions such as natural disasters, malevolent attacks, and emergencies are still inevitably posing threats on road networks in the driverless environment. However, most studies have focused on the impacts of micro mixed traffic flow characteristics, which cannot explicitly measure road network vulnerability in driverless environment. This paper develops a bi-objective framework to construct driverless environment based on travel demand. An improved accessibility-based methodology integrating traffic flow and driverless conditions evaluates the vulnerability of road network under disruptions. The proposed methodology was applied to the highway network in Florida, USA. Results demonstrate that the vulnerability of road network would be decreased with the increase of the penetration rate of autonomous vehicles. When the penetration rate gets in the range of 40%–80%, network vulnerability would significantly reduce, and they show linear relationship. Findings of this study could provide new sights into managing and planning driverless road network in future.]]></description>
      <pubDate>Fri, 16 Dec 2022 09:41:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2019126</guid>
    </item>
    <item>
      <title>Homogeneity, Heterogeneity, and Transformation of Travel Patterns—Case Studies in Chinese Cities</title>
      <link>https://trid.trb.org/View/2019125</link>
      <description><![CDATA[Exploration of travel patterns is the prerequisite of urban transport strategy decision-making and forecasting overall future trends of urban transport. 154 Chinese cities’ travel data were collected with the support of a national project. Homogeneity, heterogeneity and transformation of travel pattern were horizontally and longitudinally analyzed. The authors found that daily travel time per capita has a good homogeneity, which was consistent with previous studies. In contrast, other indicators of travel pattern including travel distance and mode structure showed much heterogeneity across city categories. Type II big cities, which has 3–5 million urban population, are the watershed of distinct variation of travel patterns. The proportion of private motorized vehicles in all motorized modes appeared as a vertex and a downward trend appeared in super cities, which was accompanied by a significantly increasing share of rail transit. The results will contribute to a comprehensive and timely understanding of fundamental urban transport characteristics in China and supplement other findings in the field of travel pattern.]]></description>
      <pubDate>Fri, 16 Dec 2022 09:41:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2019125</guid>
    </item>
    <item>
      <title>Study on the Effect of Pit Construction on the Deformation of Maglev Structure</title>
      <link>https://trid.trb.org/View/2019124</link>
      <description><![CDATA[The construction of the foundation pit that is close to a maglev line will lead to the deformation of the maglev line, thus affecting safe operation. Based on the foundation pit construction of the underground station of Shanghai airport connecting line and the fire resistance experimental building of Shanghai Tongji University, this paper studies the influence of foundation pit construction on the deformation of adjacent maglev structure and its deformation development law. Through the arrangement of a variety of deformation monitoring points and the statistical analysis of a variety of monitoring data, this paper reveals the correlation between maglev structure deformation and foundation deformation which includes the deformation of underground continuous wall and deep soil deformation and so on, the key factors and methods that can effectively control maglev structure deformation are put forward. The research results have certain reference significance for follow-up similar projects.]]></description>
      <pubDate>Fri, 16 Dec 2022 09:41:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2019124</guid>
    </item>
    <item>
      <title>Analysis of Network Traffic Capacity Based on Travelers Considering Travel Behavior Choice</title>
      <link>https://trid.trb.org/View/2019122</link>
      <description><![CDATA[The practical experience of traffic development indicates that there are some problems in increasing network traffic capacity by traditional means ignoring travel behavior. In order to increase the current capacity, this paper focuses on studying the relationship between network traffic capacity and travel behavior choice and explores a way to select individuals as objectives to study the network traffic capacity. Based on the space-time consumption method, the relationships between travel speed, travel distance, travel mode, and traffic capacity are discussed, respectively; the specific influence trends of these three aspects are obtained. This paper constructs a simple traffic capacity model considering mode choice under a certain modal ratio, and the internal binary logit model is calibrated by revealed preference (RP) survey in peak hour in Tai’an. This paper can provide reference for the calculation and modeling of traffic capacity, as well as suggestions for relevant departments in traffic demand management.]]></description>
      <pubDate>Fri, 16 Dec 2022 09:41:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2019122</guid>
    </item>
    <item>
      <title>Study on Shear Lag Effect of Closed Cavity Thin-Walled Components in Assembled Underground Structures</title>
      <link>https://trid.trb.org/View/2019123</link>
      <description><![CDATA[The assembled underground stations of Changchun Railway Line 2 use a series of closed cavity thin-walled components to reduce the structural weight. As for the hollow component, the shear lag effect is essential for the safety of the structure. Thus, the numerical simulation is used to analyze the normal stress of the component, which contains a simple straight model and an actual station model. The results show that the shear lag effect occurs in the intersection of flange and rib of the component, and the maximum amplification factor of stress is 1.02 which should be considered for relevant design.]]></description>
      <pubDate>Fri, 16 Dec 2022 09:41:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2019123</guid>
    </item>
    <item>
      <title>Estimate of Poverty Reduction Effects by the Transport Infrastructure and Industry Development Based on System Dynamics</title>
      <link>https://trid.trb.org/View/2019121</link>
      <description><![CDATA[This paper scientifically measures the impact of transport infrastructure and industry development on the poverty reduction effects. Based on spatial panel data that characterize the level of the transport industry, the authors use the SPSS, econometrics, and other tools to quantitatively analyze the correlation coefficients between indicators. Then the authors established the poverty reduction effect model of transport development by the system dynamics. Finally, the authors make sensitivity analysis of four indicators related to the development of transport industry. The road network density, the added value of logistics industry, the added value of postal services, and total retail sales of social consumer goods had a significant effect on regional poverty reduction, and the density of the road network has the largest contribution to the regional poverty reduction effect. When the road network density increases by 10%, regional GDP increases by 25%; when the retail sales of consumer goods increase by 50%, the regional GDP increases by 20%.]]></description>
      <pubDate>Fri, 16 Dec 2022 09:41:10 GMT</pubDate>
      <guid>https://trid.trb.org/View/2019121</guid>
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