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    <title>Transport Research International Documentation (TRID)</title>
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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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      <link>https://trid.trb.org/</link>
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    <item>
      <title>A scenario-based stochastic programming approach for the public charging station location problem</title>
      <link>https://trid.trb.org/View/2092016</link>
      <description><![CDATA[This paper presents an integrated framework for the optimal planning of public charging stations for plug-in electric vehicles (PEVs) in urban areas. The framework consists of two main components: (i) an out-of-home charging demand model based on an activity-based travel demand model, and (ii) a public charging station location-allocation model using a scenario-based stochastic programming (SP) approach. In order to capture the dynamic charging behaviour of PEV users, a chi-squared automatic interaction detector (CHAID)-based mixed effects decision tree is induced from multi-day activity diaries. Moreover, because the stochastic error of the micro-simulation approach brings about uncertainty, the authors adopted a two-stage stochastic mixed-integer programming (TSMIP) model, which measures uncertainty by means of a finite set of scenarios obtained from the derived decision rules underlying PEV charging. The proposed approach is demonstrated for the City of Eindhoven, The Netherlands, and benefits of the stochastic solution are discussed.]]></description>
      <pubDate>Thu, 16 Feb 2023 12:11:27 GMT</pubDate>
      <guid>https://trid.trb.org/View/2092016</guid>
    </item>
    <item>
      <title>Real-time train motion parameter estimation using an Unscented Kalman Filter</title>
      <link>https://trid.trb.org/View/1999568</link>
      <description><![CDATA[Train movement dynamics are usually modelled by means of Newton’s second law. The resulting dynamic equation can be very precise if the parameters that it depends on are determined accurately. However, these parameters may vary in time and show wide variations, making the calibration task nontrivial and jeopardizing the performance of a broad variety of applications in the railway industry: from timetable planning and railway traffic simulation to Driver Advisory Systems and Automatic Train Operation. In this article, the online train motion model calibration problem is addressed with a special focus on energy-efficient on-board applications. To this end, location and speed measurements are assumed to be available for a train running under normal operation conditions. A well-known real-time parameter estimation algorithm, the Unscented Kalman Filter, is combined with a driving regime calculator and a post-processing module in order to obtain bounds and statistics of parameters such as the maximum applied tractive effort and power, the applied brake rates, the cruise speed and the length of the final coasting and braking. The proposed framework is tested in a case study with real data from trains operating on the Eindhoven-’s-Hertogenbosch corridor in the Netherlands. Results obtained show that UKF is able to track the speed and location measurements and to estimate the parameters that model the running resistance in the dynamic equation. The proposed driving regime and the post-processing modules can determine the current regime accurately and give a deeper insight into the variations of the driving style, respectively.]]></description>
      <pubDate>Thu, 15 Sep 2022 09:20:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/1999568</guid>
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    <item>
      <title>A comparative study of social interaction frequencies among social network members in five countries</title>
      <link>https://trid.trb.org/View/1763512</link>
      <description><![CDATA[Social interaction patterns are relevant to explain (social) travel behavior. As such, the objective of this paper is to comparatively study the factors that influence social interaction frequency among social network members with different communication modes. Based on data from seven surveys on social networks, this analysis seeks to shed some light on (i) the similarities and differences in social interaction frequency patterns, (ii) the relation of personal and network characteristics with observed patterns, and (iii) the extent to which these associations are consistent across contexts, in terms of effect direction and magnitude.A multilevel-multivariate lognormal hurdle model is used to jointly analyze social interaction frequency patterns across all datasets. Level 1 includes information on ego-alter dyad characteristics, level 2 includes ego-level socio-demographic and aggregate social network characteristics, while level 3 includes information specific to each context where data was collected. In line with network capital theory, results show the existence of very consistent associations between social interaction frequency and some network and dyad characteristics such as network size, ego-alter distance, and emotional closeness, which showed some degree of generality irrespective of context. Building up on previous research, results also suggest that the effect of a higher transport cost-to-earnings ratio is more likely to manifest in the tie-formation phase, in such a way that the geographical spread of the network will tend to be smaller, but conditional on such a network distribution, the cost-to-earnings ratio effect becomes negligible. For other variables such as education level, gender and relationship type, effect patterns were less clear, which might be explained by socio-economic, and other contextual factors, as well as methodological differences across studies.The model presented here can provide average levels of demand for social interactions, which bounded by the geographical distribution of networks, can be used to further understand travel demand in urban environments and transportation systems at the local or regional level.]]></description>
      <pubDate>Tue, 02 Mar 2021 13:33:09 GMT</pubDate>
      <guid>https://trid.trb.org/View/1763512</guid>
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    <item>
      <title>The challenge of the bicycle street: Applying collaborative governance processes while protecting user centered innovations</title>
      <link>https://trid.trb.org/View/1738183</link>
      <description><![CDATA[The innovation of the bicycle street allows missing links in cycling networks to be developed in places where financial or spatial constraints present challenges to implementing separated cycling facilities. Two separate cases in the Netherlands demonstrate that when the intent is to use the innovation to resolve spatial constraints, the goal of reaching consensus between different stakeholders involved with a collaborative governance process can lead to a result in which the user practices necessary to make the innovation a success are not sufficiently protected. These cases show how collaborative governance processes in transportation planning can lead to innovations being implemented in ways that fail to support the group that they are intended to benefit. This argument is supported by drawing on two different bodies of literature: 1) collaborative governance literature that describes the movement to increase the legitimacy of government supported projects through substantial stakeholder involvement; and 2) strategic niche management literature that describes the role that established user practices play in the upscaling potential of innovations. These literatures are connected through the evaluation technique of Strategic Policy Niche Management (SPNM), which has been used to apply strategic niche management principles to innovations in transportation policy. The article uses the concept of SPNM to illustrate the need for understanding the connection between citizens in collaborative governance and users in innovation development. This relationship is illustrated by examining the history of a transportation innovation, the bicycle street, with a particular focus on how its development in Germany and Belgium as a means to provide bicycle infrastructure at low cost differs from its introduction in the Netherlands, where it has been used as a compromise solution between different user groups. The history of the bicycle street and its uses in different contexts is followed by a detailed case study on the contested implementation of a bicycle street in Eindhoven, the Netherlands. This specific case reveals what can happen when an innovative project is undertaken with a focus on consensus among potentially impacted stakeholders and does not give increased weight to the needs of the users of the innovation. The innovation may develop sufficient support to be implemented but may not be sufficiently attuned to user practices to meet the needs of its intended user group, creating an obstacle to future upscaling. The article concludes with a discussion of how adopting specific regulations for bicycle streets could resolve this issue, preventing bicycle streets from being implemented in places where other options would better serve cyclists.]]></description>
      <pubDate>Mon, 05 Oct 2020 14:36:48 GMT</pubDate>
      <guid>https://trid.trb.org/View/1738183</guid>
    </item>
    <item>
      <title>Increasing control of operations and improving financial performance at regional airports: A case study of Viggo Eindhoven Airport</title>
      <link>https://trid.trb.org/View/1722734</link>
      <description><![CDATA[This case study describes the growth and development of Viggo in both its volume and its level of professionalism. Viggo is a privately owned airport service provider at Eindhoven Airport and Lelystad Airport in The Netherlands. A strong growth rate in the beginning of this century required Viggo to shift from the traditional ground handling of legacy carriers and charters to being a broad airport service provider handling mainly low-cost carriers. The explosion in volume and complexity led to many organisational and operational changes. This case study focuses on the implementation of the continuous improvement methodology and how evidence-based management is achieved through the creation of data-driven decision-making in both the operational execution and the improvement cycles. The implementation of these concepts substantially improved the operational efficiency and effectiveness while creating a stable and profitable financial situation at a regional airport fully reliant on low-cost carriers. The case tends to set an example for regional airports, its service providers and other stakeholders sizing between two and ten million passengers annually in how continuous improvement and data-based evidence can increase the control of operations and boost financial results.]]></description>
      <pubDate>Thu, 27 Aug 2020 10:05:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/1722734</guid>
    </item>
    <item>
      <title>Validation of a simulation system exploring land-use impacts on travel behavior</title>
      <link>https://trid.trb.org/View/1581290</link>
      <description><![CDATA[This paper aims to validate a simulation system for exploring the land-use impacts on travel behaviour. The system simulates urban layout and travel behaviour. The key parameters and input for simulating urban layout are calibrated by Eindhoven, and a set of hypothetic cities are then generated to validate the travel behaviour, with the measurement of entropy employed measuring the land use pattern. The results show that the simulation system can generate a variety of land use patterns, and the different travel behaviour of the land use patterns are captured. The results also show that when the land use patterns are similar to a real city pattern, their travel behaviour is similar as well. The system is proved to be a helpful simulation tool to explore the impacts of land use on travel behaviour.]]></description>
      <pubDate>Mon, 29 Apr 2019 21:14:07 GMT</pubDate>
      <guid>https://trid.trb.org/View/1581290</guid>
    </item>
    <item>
      <title>A Two-Stage Stochastic Programming Approach for the Electric Vehicle Public Charging Station Location Problem Under Uncertain Dynamic Household Activity-Travel Demand</title>
      <link>https://trid.trb.org/View/1572550</link>
      <description><![CDATA[In this paper, the authors propose a novel two-stage stochastic mixed integer programming (TSMIP) algorithm with recourse for locating plug-in electric vehicle (PEV) public charging stations in conjunction with an advanced activity-based model of charging demand. A chi-square automatic interaction detector (CHAID)-based dynamic decision tree is used to estimate charging demand under uncertainty represented by a set of scenarios. The dynamic decision tree represents some measure of uncertainty since it consists of a series of nodes and branches that specify the condition states and personal profiles (i.e., deterministic part), and the leaf nodes with probabilistic action states that lead to particular choice behavior (i.e., stochastic part). The contributions of this study can be listed as follows: (i) Charging demand is directly estimated from multi-day activity-travel diary data of PEV users; (ii) Given the uncertain nature of demand inherited from the probabilistic decision tree, a two-stage stochastic programming model is proposed to solve the strategic location-allocation optimization problem of PEV public charging stations; (iii) A novel scenario-generation method combining decision tree and multiple scenario trees is proposed, which results in statistically well-defined models; (iv) The proposed approach is demonstrated for the city of Eindhoven, The Netherlands using activity-based travel demand model ALBATROSS.]]></description>
      <pubDate>Fri, 01 Mar 2019 15:51:02 GMT</pubDate>
      <guid>https://trid.trb.org/View/1572550</guid>
    </item>
    <item>
      <title>Quantified street: Smart governance of urban safety</title>
      <link>https://trid.trb.org/View/1514184</link>
      <description><![CDATA[The rapid deployment of technology in urban settings drastically changes the way urban safety is being governed. This article investigates smart governance of urban safety empirically through an in-depth case study of a project to improve the safety of a street in the Dutch city of Eindhoven. This collaboration between the city government, technology producers, knowledge institutes and owners of bars and restaurants entails the use of new technologies – noise detection, twitter analyses, data analysis, light interventions, gaming – for instantaneous monitoring and intervention. The authors analyze these smart governance practices from a socio-technological perspective. On the basis of their analysis, they qualify the case as a quantified street: enormous amounts of data are being collected to strengthen the governance of urban safety. The governance analysis showed that these actors shared the idea that more information results in better governance. External funding facilitated collaboration since money was no longer a scarce resource and technology became a ‘lens’ for building a shared understanding of the street. The relative absence of rules created the room for building innovative practices. In the conclusion, the authors raise questions concerning the strong focus on information as the key to a safer street and present an agenda for further research into the smart governance of urban safety.]]></description>
      <pubDate>Mon, 22 Oct 2018 16:27:06 GMT</pubDate>
      <guid>https://trid.trb.org/View/1514184</guid>
    </item>
    <item>
      <title>High Statistics Measurements of Pedestrian Dynamics</title>
      <link>https://trid.trb.org/View/1326139</link>
      <description><![CDATA[Aiming at a quantitative understanding of basic aspects of pedestrian dynamics, extensive and high-accuracy measurements of real-life pedestrian trajectories have been performed. A measurement strategy based on Microsoft Kinect™ has been used. Specifically, more than 100,000 pedestrians have been tracked while walking along a trafficked corridor at the Eindhoven University of Technology, The Netherlands. The obtained trajectories have been analyzed as ensemble data.  The main result consists of a statistical descriptions of pedestrian characteristic kinematic quantities such as positions and fundamental diagrams, possibly conditioned to the local crowd flow (e.g. co-flow or counter-flow).]]></description>
      <pubDate>Wed, 29 Oct 2014 11:27:01 GMT</pubDate>
      <guid>https://trid.trb.org/View/1326139</guid>
    </item>
    <item>
      <title>Mobi - Modal Shift Through Gamification</title>
      <link>https://trid.trb.org/View/1315416</link>
      <description><![CDATA[From5To4  (F5T4) is web-based tool which combines personal and group incentives for employees into an attractive game. It aims for a reduction of the energy impact of commuter and business trips through the provision of a 'Commuter Challenge' competition. F5T4 is a game-changer, introducing new trends in social media and gamification into the field of mobility management. F5T4 encourages employees to change their travel behaviour and use sustainable modes for at least 20% of their travel to work trips. This is possible if they work and travel smart. A digital coach, the personal obligation to fill in travel choices and team coherence are strong incentives. Peer pressure, competition and small awards help to stay motivated. Recent implementations in 10 sites reaching over 1,000 employees show an average drop in car-use during rush-hour of 21%. In one specific case (Municipality of Eindhoven, 60 contestants), the participants reduced car trips by 27%, biked 5.8 km more per week per average participant and drove 6.25 km per week less.]]></description>
      <pubDate>Thu, 24 Jul 2014 15:22:11 GMT</pubDate>
      <guid>https://trid.trb.org/View/1315416</guid>
    </item>
    <item>
      <title>Distributive effects of new highway infrastructure in the Netherlands: the role of network effects and spatial spillovers</title>
      <link>https://trid.trb.org/View/1302033</link>
      <description><![CDATA[Network effects and spatial spillovers are intrinsic impacts of transport infrastructure. Network effects imply that an improvement in a particular link in a network generates effects in many other elements of that network, while spillover effects can be defined as those impacts occurring beyond the regions where the actual transport investment is made. These two related effects entail a redistribution of impacts among regions, and their omission from road planning is argued to cause the systematic underestimation of the profitability of transport projects and therefore the public financing they require. However, traditional transport appraisal methodologies fail to consider network and spillover effects. In this study the authors focus on the spillover impacts of two highway sections planned in the city region of Eindhoven, located in the Dutch province of Noord-Brabant, a region with traffic congestion problems. The new road infrastructure will be financed mainly by national government, the province and the urban region of Eindhoven (‘Stadsregio Eindhoven’), which consists of 21 municipalities. The authors measure the benefits of the additional links in terms of travel time savings and the accompanying monetary gains. The results show that important spillovers occur in those municipalities close to the new links. The province of Noord-Brabant will benefit the most. The authors also found important spillovers in the province of Limburg. This latter province will benefit from reduced travel times without contributing financially to the establishment of the analyzed new road links.]]></description>
      <pubDate>Thu, 03 Apr 2014 10:19:22 GMT</pubDate>
      <guid>https://trid.trb.org/View/1302033</guid>
    </item>
    <item>
      <title>Traffic conflicts on bicycle paths: A systematic observation of behaviour from video</title>
      <link>https://trid.trb.org/View/1286806</link>
      <description><![CDATA[In The Netherlands, on bicycle paths, single-bicycle accidents, bicycle–bicycle and bicycle–moped accidents constitute a considerable share of all bicyclist injuries. Over three quarters of all hospitalised bicyclist victims in the Netherlands cannot be directly related to a crash with motorised traffic. As the usage of bicycle paths steadily increases, it is to be expected that safety on bicycle paths will become a major issue in the coming years in The Netherlands.  A study was conducted into the behaviour of bicyclists and moped riders to improve traffic safety on bicycle paths. By behavioural observations with video, mutual conflicts and bicyclist behaviour on bicycle paths were recorded and analysed, among other things by means of the conflict observation method DOCTOR (Dutch Objective Conflict Technique for Operation and Research). The explorative phase of the study (phase 1), included two research locations, one in the city of Amsterdam and one in Eindhoven. The results gave guidance for a better understanding of the behaviour between different users of separate two-directional bicycle paths. An example includes the relationship between bicyclist–moped rider behaviour and the width of the bicycle path. For a condition with busy bicycle traffic in both directions the width of the bicycle path in Amsterdam (effectively 3.55 m) is relatively narrow, whereas the bicycle path width in Eindhoven (>4.94 m) appears to be sufficient to accommodate large flows of bicyclists. Because of a large flow of crossing pedestrians resulting in (severe) conflicts with bicyclists in Amsterdam, additional countermeasures to better control these interactions are needed.  The DOCTOR conflict observation method from video appears to be applicable for conflicts between intersecting road users and for head-on conflicts on the bicycle path. Conflict situations between bicyclists in the same direction (constituting an important share of injury accidents on bicycle paths) require an additional and more general systematic observation of specific behaviour. Therefore, phase 2 of the project will focus in particular on interactions between bicycle path users in the same direction and underlying processes.]]></description>
      <pubDate>Wed, 26 Mar 2014 10:11:12 GMT</pubDate>
      <guid>https://trid.trb.org/View/1286806</guid>
    </item>
    <item>
      <title>Sequence Alignment Analysis of Variability in Activity Travel Patterns Through 8 Weeks of Diary Data</title>
      <link>https://trid.trb.org/View/1288338</link>
      <description><![CDATA[Variability of activity travel patterns has long been an important issue in transportation research. Such variability has been typically explained in relation to covariance with a set of sociodemographic characteristics of travelers. However, variability also stems from differences in knowledge about the environment, which changes over time. To improve understanding of the contribution of different sources to variability in observed activity travel patterns, this paper applies sequence alignment to investigate different sources of variability in longitudinal patterns. The data on activity travel patterns were collected in 2010 for 3 months from newcomers to the city of Eindhoven, Netherlands. GPS technology was used to obtain traces that were processed with TraceAnnotator to impute activities and trips. A set of activity travel sequences for 8 weeks for 27 respondents was used in the analysis. The results show that (a) interpersonal variability is significantly higher than intrapersonal variability, although intrapersonal variability is yet substantial and should not be ignored; (b) intrapersonal variability reflecting different speeds of learning the new environment substantially changes over time; and (c) both interpersonal and intrapersonal variability are affected by sociodemographic characteristics such as gender and country of origin. The paper also discusses the implications of these findings for future research.]]></description>
      <pubDate>Sat, 01 Mar 2014 18:12:47 GMT</pubDate>
      <guid>https://trid.trb.org/View/1288338</guid>
    </item>
    <item>
      <title>Effects of Fuel Price on Individual Dynamic Travel Decisions: Binary Probit Selection Model That Uses GPS Panel Data</title>
      <link>https://trid.trb.org/View/1287884</link>
      <description><![CDATA[The goal of this study is to explore the impact of fuel price changes on individual activity travel behavior. Previous studies in transportation research have examined both short- and long-term fuel price elasticities on vehicle miles traveled (VMT) and vehicle stock through aggregated data at the country or subnational level. This study is one of the few to use individual-level panel data. Furthermore, studies that consider context effects such as weather conditions, accessibility, and travel companion are rare. Noninclusion of these context-variable effects may produce spurious results on the influence of fuel price changes on activity travel patterns. On the basis of a unique set of GPS panel data of 122 respondents living in the Eindhoven area of the Netherlands, the authors collected corresponding weather conditions data and daily fuel price data. A two-step estimation approach was applied to estimate (a) individuals’ decisions of making car-based trips and (b) the influence of fluctuations in real fuel price on car travel distance. The results show that fuel price has significant negative effects both on an individual’s decision to use a car and on travel distance by car if a person uses it. In addition, results indicate that days of the week, weather conditions, and 3-week lagged and 1-week expected fuel prices have significant negative effects on individuals’ car use decisions. However, once people decide to travel by car, weather conditions do not have any significant effects on VMT. The 2-week lagged fuel price has a significant negative effect on only VMT.]]></description>
      <pubDate>Fri, 28 Feb 2014 13:32:34 GMT</pubDate>
      <guid>https://trid.trb.org/View/1287884</guid>
    </item>
    <item>
      <title>Map Matching of GPS Data with Bayesian Belief Networks</title>
      <link>https://trid.trb.org/View/1284031</link>
      <description><![CDATA[This paper proposes a map matching algorithm using Bayesian belief network for GPS traces to generate the spatial-temporal information of individuals. The algorithm incorporates the road network topology, distance from trace nodes to road segments, the angle between two lines, direction difference, accuracy of measured GPS log point, and position of roads. The GPS data collected in the Eindhoven region, The Netherlands, was used to examine the performance of this algorithm. Results based on a small sample show that the algorithm has a good performance in both processing efficiency and prediction accuracy of correctly identified instances. Even with a small sample, the overall prediction accuracy reaches 87.02%.]]></description>
      <pubDate>Wed, 29 Jan 2014 07:32:39 GMT</pubDate>
      <guid>https://trid.trb.org/View/1284031</guid>
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