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To improve road safety on parts of the road network carrying low traffic volumes, road designs are proposed including single-lane road segments and periodic overtaking lanes. These roads have been proven to contribute to substantial benefits in terms of road safety. However, overtaking of slower vehicles is only possible on segments including an overtaking lane and not on the single-lane road segments. Driver and vehicle heterogeneity resulting in differences in desired speeds are consequently decisive for the traffic performance. Sufficient quality of service is relying on an appropriate design and distribution of single-lane segments and overtaking lanes. In this paper, we study the effect of the desired speed distribution on traffic performance on single-lane road segments. Expressions are derived for the travel time, delay and percent time spent following. The derived expressions link the desired speed distribution, the single-lane segment length and the traffic flow to the resulting traffic performance. The results are verified through comparison with measures based on microscopic traffic simulation. The conclusion is that there is a good agreement between derived measures and simulation results. The derived measures should therefore not only be of theoretical interest, but also of practical use to estimate traffic performance on single-lane road segments.

To improve road safety on parts of the road network carrying low traffic volumes, road designs are proposed including single-lane road segments and periodic overtaking lanes. These roads have been proven to contribute to substantial benefits in terms of road safety. However, overtaking of slower vehicles is only possible on segments including an overtaking lane and not on the single-lane road segments. Driver and vehicle heterogeneity resulting in differences in desired speeds are consequently decisive for the traffic performance. Sufficient quality of service is relying on an appropriate design and distribution of single-lane segments and overtaking lanes. In this paper, we study the effect of the desired speed distribution on traffic performance on single-lane road segments. Expressions are derived for the travel time, delay and percent time spent following. The derived expressions link the desired speed distribution, the single-lane segment length and the traffic flow to the resulting traffic performance. The results are verified through comparison with measures based on microscopic traffic simulation. The conclusion is that there is a good agreement between derived measures and simulation results. The derived measures should therefore not only be of theoretical interest, but also of practical use to estimate traffic performance on single-lane road segments.

To improve road safety on parts of the road network carrying low traffic volumes, road designs are proposed including single-lane road segments and periodic overtaking lanes. These roads have been proven to contribute to substantial benefits in terms of road safety. However, overtaking of slower vehicles is only possible on segments including an overtaking lane and not on the single-lane road segments. Driver and vehicle heterogeneity resulting in differences in desired speeds are consequently decisive for the traffic performance. Sufficient quality of service is relying on an appropriate design and distribution of single-lane segments and overtaking lanes. In this paper, we study the effect of the desired speed distribution on traffic performance on single-lane road segments. Expressions are derived for the travel time, delay and percent time spent following. The derived expressions link the desired speed distribution, the single-lane segment length and the traffic flow to the resulting traffic performance. The results are verified through comparison with measures based on microscopic traffic simulation. The conclusion is that there is a good agreement between derived measures and simulation results. The derived measures should therefore not only be of theoretical interest, but also of practical use to estimate traffic performance on single-lane road segments.

To improve road safety on parts of the road network carrying low traffic volumes, road designs are proposed including single-lane road segments and periodic overtaking lanes. These roads have been proven to contribute to substantial benefits in terms of road safety. However, overtaking of slower vehicles is only possible on segments including an overtaking lane and not on the single-lane road segments. Driver and vehicle heterogeneity resulting in differences in desired speeds are consequently decisive for the traffic performance. Sufficient quality of service is relying on an appropriate design and distribution of single-lane segments and overtaking lanes. In this paper, we study the effect of the desired speed distribution on traffic performance on single-lane road segments. Expressions are derived for the travel time, delay and percent time spent following. The derived expressions link the desired speed distribution, the single-lane segment length and the traffic flow to the resulting traffic performance. The results are verified through comparison with measures based on microscopic traffic simulation. The conclusion is that there is a good agreement between derived measures and simulation results. The derived measures should therefore not only be of theoretical interest, but also of practical use to estimate traffic performance on single-lane road segments.

To improve road safety on parts of the road network carrying low traffic volumes, road designs are proposed including single-lane road segments and periodic overtaking lanes. These roads have been proven to contribute to substantial benefits in terms of road safety. However, overtaking of slower vehicles is only possible on segments including an overtaking lane and not on the single-lane road segments. Driver and vehicle heterogeneity resulting in differences in desired speeds are consequently decisive for the traffic performance. Sufficient quality of service is relying on an appropriate design and distribution of single-lane segments and overtaking lanes. In this paper, we study the effect of the desired speed distribution on traffic performance on single-lane road segments. Expressions are derived for the travel time, delay and percent time spent following. The derived expressions link the desired speed distribution, the single-lane segment length and the traffic flow to the resulting traffic performance. The results are verified through comparison with measures based on microscopic traffic simulation. The conclusion is that there is a good agreement between derived measures and simulation results. The derived measures should therefore not only be of theoretical interest, but also of practical use to estimate traffic performance on single-lane road segments.

This paper examines how knowledge properties of a manufacturing activity transfer in international manufacturing network impact performance during the transfer itself and after steady state has been reached. Hierarchical regression was used to test the relationship on survey data from 178 companies. Knowledge properties as a group was significantly affected by both performance measures when controlling for the effects of sender unit experience, sender unit size and receiver unit experience. The activities transferred thus impact the success of the transfer. The control variables of sender unit experience and receiver unit experience have their relatively strongest performance effects after steady state has been reached. Independency was the single knowledge property dimensions with the strongest relative performance effect. This is one of the first survey studies to cover both the performance of the transfer itself and after reaching steady state of manufacturing transfers. Several strands of further research were therefore identified.

This paper examines how knowledge properties of a manufacturing activity transfer in international manufacturing network impact performance during the transfer itself and after steady state has been reached. Hierarchical regression was used to test the relationship on survey data from 178 companies. Knowledge properties as a group was significantly affected by both performance measures when controlling for the effects of sender unit experience, sender unit size and receiver unit experience. The activities transferred thus impact the success of the transfer. The control variables of sender unit experience and receiver unit experience have their relatively strongest performance effects after steady state has been reached. Independency was the single knowledge property dimensions with the strongest relative performance effect. This is one of the first survey studies to cover both the performance of the transfer itself and after reaching steady state of manufacturing transfers. Several strands of further research were therefore identified.

This paper examines how knowledge properties of a manufacturing activity transfer in international manufacturing network impact performance during the transfer itself and after steady state has been reached. Hierarchical regression was used to test the relationship on survey data from 178 companies. Knowledge properties as a group was significantly affected by both performance measures when controlling for the effects of sender unit experience, sender unit size and receiver unit experience. The activities transferred thus impact the success of the transfer. The control variables of sender unit experience and receiver unit experience have their relatively strongest performance effects after steady state has been reached. Independency was the single knowledge property dimensions with the strongest relative performance effect. This is one of the first survey studies to cover both the performance of the transfer itself and after reaching steady state of manufacturing transfers. Several strands of further research were therefore identified.

This paper examines how knowledge properties of a manufacturing activity transfer in international manufacturing network impact performance during the transfer itself and after steady state has been reached. Hierarchical regression was used to test the relationship on survey data from 178 companies. Knowledge properties as a group was significantly affected by both performance measures when controlling for the effects of sender unit experience, sender unit size and receiver unit experience. The activities transferred thus impact the success of the transfer. The control variables of sender unit experience and receiver unit experience have their relatively strongest performance effects after steady state has been reached. Independency was the single knowledge property dimensions with the strongest relative performance effect. This is one of the first survey studies to cover both the performance of the transfer itself and after reaching steady state of manufacturing transfers. Several strands of further research were therefore identified.

This paper examines how knowledge properties of a manufacturing activity transfer in international manufacturing network impact performance during the transfer itself and after steady state has been reached. Hierarchical regression was used to test the relationship on survey data from 178 companies. Knowledge properties as a group was significantly affected by both performance measures when controlling for the effects of sender unit experience, sender unit size and receiver unit experience. The activities transferred thus impact the success of the transfer. The control variables of sender unit experience and receiver unit experience have their relatively strongest performance effects after steady state has been reached. Independency was the single knowledge property dimensions with the strongest relative performance effect. This is one of the first survey studies to cover both the performance of the transfer itself and after reaching steady state of manufacturing transfers. Several strands of further research were therefore identified.

This paper examines how knowledge properties of a manufacturing activity transfer in international manufacturing network impact performance during the transfer itself and after steady state has been reached. Hierarchical regression was used to test the relationship on survey data from 178 companies. Knowledge properties as a group was significantly affected by both performance measures when controlling for the effects of sender unit experience, sender unit size and receiver unit experience. The activities transferred thus impact the success of the transfer. The control variables of sender unit experience and receiver unit experience have their relatively strongest performance effects after steady state has been reached. Independency was the single knowledge property dimensions with the strongest relative performance effect. This is one of the first survey studies to cover both the performance of the transfer itself and after reaching steady state of manufacturing transfers. Several strands of further research were therefore identified.

Dynamic Network Loading (DNL) models are typically formulated as a system of differential equations where travel times, densities or any other variable that indicates congestion is endogenous. However, such endogeneities increase the complexity of the Dynamic Traffic Assignment (DTA) problem due to the interdependence of DNL, route choice and demand. In this paper, attempting to exploit the growing accessibility of traffic-related data, we suggest that congestion can be instead captured by exogenous variables, such as travel time observations. We propagate the traffic flow based on an exogenous travel time function, which has a piece-wise linear form. Given piece-wise stationary route flows, the piece-wise linear form of the travel time function allows us to use an efficient event-based modelling structure. Our Data-Driven Network Loading (DDNL) approach is developed in accordance with the theoretical DNL framework ensuring vehicle conservation and FIFO. The first simulation experiment-based results are encouraging, indicating that the DDNL can contribute to improving the efficiency of applications where the monitoring of historical network-wide flows is required. Abbreviations: DDNL - Data Driven Network Loading; DNL - Dynamic Network Loading; DTA - Dynamic Traffic Assignment; ITS - Intelligent Transportation Systems; OD - Origin Destination; TTF - Travel Time Function; LTT - Linear Travel Time; DL - Demand level, Funding Agencies|Swedish Energy AgencySwedish Energy Agency [46963-1]

Dynamic Network Loading (DNL) models are typically formulated as a system of differential equations where travel times, densities or any other variable that indicates congestion is endogenous. However, such endogeneities increase the complexity of the Dynamic Traffic Assignment (DTA) problem due to the interdependence of DNL, route choice and demand. In this paper, attempting to exploit the growing accessibility of traffic-related data, we suggest that congestion can be instead captured by exogenous variables, such as travel time observations. We propagate the traffic flow based on an exogenous travel time function, which has a piece-wise linear form. Given piece-wise stationary route flows, the piece-wise linear form of the travel time function allows us to use an efficient event-based modelling structure. Our Data-Driven Network Loading (DDNL) approach is developed in accordance with the theoretical DNL framework ensuring vehicle conservation and FIFO. The first simulation experiment-based results are encouraging, indicating that the DDNL can contribute to improving the efficiency of applications where the monitoring of historical network-wide flows is required. Abbreviations: DDNL - Data Driven Network Loading; DNL - Dynamic Network Loading; DTA - Dynamic Traffic Assignment; ITS - Intelligent Transportation Systems; OD - Origin Destination; TTF - Travel Time Function; LTT - Linear Travel Time; DL - Demand level, Funding Agencies|Swedish Energy AgencySwedish Energy Agency [46963-1]

Dynamic Network Loading (DNL) models are typically formulated as a system of differential equations where travel times, densities or any other variable that indicates congestion is endogenous. However, such endogeneities increase the complexity of the Dynamic Traffic Assignment (DTA) problem due to the interdependence of DNL, route choice and demand. In this paper, attempting to exploit the growing accessibility of traffic-related data, we suggest that congestion can be instead captured by exogenous variables, such as travel time observations. We propagate the traffic flow based on an exogenous travel time function, which has a piece-wise linear form. Given piece-wise stationary route flows, the piece-wise linear form of the travel time function allows us to use an efficient event-based modelling structure. Our Data-Driven Network Loading (DDNL) approach is developed in accordance with the theoretical DNL framework ensuring vehicle conservation and FIFO. The first simulation experiment-based results are encouraging, indicating that the DDNL can contribute to improving the efficiency of applications where the monitoring of historical network-wide flows is required. Abbreviations: DDNL - Data Driven Network Loading; DNL - Dynamic Network Loading; DTA - Dynamic Traffic Assignment; ITS - Intelligent Transportation Systems; OD - Origin Destination; TTF - Travel Time Function; LTT - Linear Travel Time; DL - Demand level, Funding Agencies|Swedish Energy AgencySwedish Energy Agency [46963-1]

Dynamic Network Loading (DNL) models are typically formulated as a system of differential equations where travel times, densities or any other variable that indicates congestion is endogenous. However, such endogeneities increase the complexity of the Dynamic Traffic Assignment (DTA) problem due to the interdependence of DNL, route choice and demand. In this paper, attempting to exploit the growing accessibility of traffic-related data, we suggest that congestion can be instead captured by exogenous variables, such as travel time observations. We propagate the traffic flow based on an exogenous travel time function, which has a piece-wise linear form. Given piece-wise stationary route flows, the piece-wise linear form of the travel time function allows us to use an efficient event-based modelling structure. Our Data-Driven Network Loading (DDNL) approach is developed in accordance with the theoretical DNL framework ensuring vehicle conservation and FIFO. The first simulation experiment-based results are encouraging, indicating that the DDNL can contribute to improving the efficiency of applications where the monitoring of historical network-wide flows is required. Abbreviations: DDNL - Data Driven Network Loading; DNL - Dynamic Network Loading; DTA - Dynamic Traffic Assignment; ITS - Intelligent Transportation Systems; OD - Origin Destination; TTF - Travel Time Function; LTT - Linear Travel Time; DL - Demand level, Funding Agencies|Swedish Energy AgencySwedish Energy Agency [46963-1]

Dynamic Network Loading (DNL) models are typically formulated as a system of differential equations where travel times, densities or any other variable that indicates congestion is endogenous. However, such endogeneities increase the complexity of the Dynamic Traffic Assignment (DTA) problem due to the interdependence of DNL, route choice and demand. In this paper, attempting to exploit the growing accessibility of traffic-related data, we suggest that congestion can be instead captured by exogenous variables, such as travel time observations. We propagate the traffic flow based on an exogenous travel time function, which has a piece-wise linear form. Given piece-wise stationary route flows, the piece-wise linear form of the travel time function allows us to use an efficient event-based modelling structure. Our Data-Driven Network Loading (DDNL) approach is developed in accordance with the theoretical DNL framework ensuring vehicle conservation and FIFO. The first simulation experiment-based results are encouraging, indicating that the DDNL can contribute to improving the efficiency of applications where the monitoring of historical network-wide flows is required. Abbreviations: DDNL - Data Driven Network Loading; DNL - Dynamic Network Loading; DTA - Dynamic Traffic Assignment; ITS - Intelligent Transportation Systems; OD - Origin Destination; TTF - Travel Time Function; LTT - Linear Travel Time; DL - Demand level, Funding Agencies|Swedish Energy AgencySwedish Energy Agency [46963-1]

Waste management in the Architecture, Engineering and Construction (AEC) industry has been a major research topic owing to the AEC industry being one of the top contributors of waste generation. However, research has primarily focused on new build and has neglected refurbishment projects which become relevant due to an aging building stock in Sweden and Europe. Various actors are involved in refurbishment projects which makes it important to study each actor as well as tensions between them. By using a service ecosystem perspective and relying on 38 interviews, this paper aims to investigate tensions and barriers between actors within the service ecosystem of CDW for refurbishment projects in Sweden. Based on the results, spatial barriers are the most mentioned barrier which also create the highest number of tensions between project and contractor mother firm, subcontractors, waste recycling firms and society/citizens. The majority of the tensions are found between projects and the contractor mother firms, followed by tensions between projects and clients and projects and subcontractors. Unlike previous studies investigating only one of the actors waste management practices, this paper contributes by investigating the interactions between seven different actors which is important for improving waste management practices in refurbishment projects., Funding Agencies|Mistra Closing the Loop, the Foundation for Strategic Environmental Research [160026]

Waste management in the Architecture, Engineering and Construction (AEC) industry has been a major research topic owing to the AEC industry being one of the top contributors of waste generation. However, research has primarily focused on new build and has neglected refurbishment projects which become relevant due to an aging building stock in Sweden and Europe. Various actors are involved in refurbishment projects which makes it important to study each actor as well as tensions between them. By using a service ecosystem perspective and relying on 38 interviews, this paper aims to investigate tensions and barriers between actors within the service ecosystem of CDW for refurbishment projects in Sweden. Based on the results, spatial barriers are the most mentioned barrier which also create the highest number of tensions between project and contractor mother firm, subcontractors, waste recycling firms and society/citizens. The majority of the tensions are found between projects and the contractor mother firms, followed by tensions between projects and clients and projects and subcontractors. Unlike previous studies investigating only one of the actors waste management practices, this paper contributes by investigating the interactions between seven different actors which is important for improving waste management practices in refurbishment projects., Funding Agencies|Mistra Closing the Loop, the Foundation for Strategic Environmental Research [160026]

Waste management in the Architecture, Engineering and Construction (AEC) industry has been a major research topic owing to the AEC industry being one of the top contributors of waste generation. However, research has primarily focused on new build and has neglected refurbishment projects which become relevant due to an aging building stock in Sweden and Europe. Various actors are involved in refurbishment projects which makes it important to study each actor as well as tensions between them. By using a service ecosystem perspective and relying on 38 interviews, this paper aims to investigate tensions and barriers between actors within the service ecosystem of CDW for refurbishment projects in Sweden. Based on the results, spatial barriers are the most mentioned barrier which also create the highest number of tensions between project and contractor mother firm, subcontractors, waste recycling firms and society/citizens. The majority of the tensions are found between projects and the contractor mother firms, followed by tensions between projects and clients and projects and subcontractors. Unlike previous studies investigating only one of the actors waste management practices, this paper contributes by investigating the interactions between seven different actors which is important for improving waste management practices in refurbishment projects., Funding Agencies|Mistra Closing the Loop, the Foundation for Strategic Environmental Research [160026]

Waste management in the Architecture, Engineering and Construction (AEC) industry has been a major research topic owing to the AEC industry being one of the top contributors of waste generation. However, research has primarily focused on new build and has neglected refurbishment projects which become relevant due to an aging building stock in Sweden and Europe. Various actors are involved in refurbishment projects which makes it important to study each actor as well as tensions between them. By using a service ecosystem perspective and relying on 38 interviews, this paper aims to investigate tensions and barriers between actors within the service ecosystem of CDW for refurbishment projects in Sweden. Based on the results, spatial barriers are the most mentioned barrier which also create the highest number of tensions between project and contractor mother firm, subcontractors, waste recycling firms and society/citizens. The majority of the tensions are found between projects and the contractor mother firms, followed by tensions between projects and clients and projects and subcontractors. Unlike previous studies investigating only one of the actors waste management practices, this paper contributes by investigating the interactions between seven different actors which is important for improving waste management practices in refurbishment projects., Funding Agencies|Mistra Closing the Loop, the Foundation for Strategic Environmental Research [160026]

Waste management in the Architecture, Engineering and Construction (AEC) industry has been a major research topic owing to the AEC industry being one of the top contributors of waste generation. However, research has primarily focused on new build and has neglected refurbishment projects which become relevant due to an aging building stock in Sweden and Europe. Various actors are involved in refurbishment projects which makes it important to study each actor as well as tensions between them. By using a service ecosystem perspective and relying on 38 interviews, this paper aims to investigate tensions and barriers between actors within the service ecosystem of CDW for refurbishment projects in Sweden. Based on the results, spatial barriers are the most mentioned barrier which also create the highest number of tensions between project and contractor mother firm, subcontractors, waste recycling firms and society/citizens. The majority of the tensions are found between projects and the contractor mother firms, followed by tensions between projects and clients and projects and subcontractors. Unlike previous studies investigating only one of the actors waste management practices, this paper contributes by investigating the interactions between seven different actors which is important for improving waste management practices in refurbishment projects., Funding Agencies|Mistra Closing the Loop, the Foundation for Strategic Environmental Research [160026]

Time-dependent Origin-Destination (OD) matrices are an essential input to transportation models. A cost-efficient and widely used approach for estimating OD matrices involves the exploitation of flow counts from stationary traffic detectors. This estimation approach is also referred to as assignment-based OD matrix estimation because, typically, Dynamic Traffic Assignment (DTA) models are used to map the OD matrix to the link flows. The conventional DTA establish a complex non-linear relationship between the demand, and the link flows, adding an inherent complexity to the OD matrix estimation problem. In this paper, attempting to exploit the growing availability of Floating-Car Data (FCD), we suggest a solution approach that is based on a Data-Driven Network Assignment (DDNA) mechanism. The DDNA utilises the FCD from probe vehicles to capture congestion effects, providing a linear mapping of the OD matrix to the link flow observations. We present the results of two synthetic-data experiments that serve as proof of concept, indicating that if FCD are available, the computationally costly DTA may not be necessary for solving the OD matrix estimation problem., Funding Agencies|Swedish Transport Administration [TRV2018/132473, TRV2021/22404]; Swedish Energy Agency [46963-1]

Time-dependent Origin-Destination (OD) matrices are an essential input to transportation models. A cost-efficient and widely used approach for estimating OD matrices involves the exploitation of flow counts from stationary traffic detectors. This estimation approach is also referred to as assignment-based OD matrix estimation because, typically, Dynamic Traffic Assignment (DTA) models are used to map the OD matrix to the link flows. The conventional DTA establish a complex non-linear relationship between the demand, and the link flows, adding an inherent complexity to the OD matrix estimation problem. In this paper, attempting to exploit the growing availability of Floating-Car Data (FCD), we suggest a solution approach that is based on a Data-Driven Network Assignment (DDNA) mechanism. The DDNA utilises the FCD from probe vehicles to capture congestion effects, providing a linear mapping of the OD matrix to the link flow observations. We present the results of two synthetic-data experiments that serve as proof of concept, indicating that if FCD are available, the computationally costly DTA may not be necessary for solving the OD matrix estimation problem., Funding Agencies|Swedish Transport Administration [TRV2018/132473, TRV2021/22404]; Swedish Energy Agency [46963-1]

Time-dependent Origin-Destination (OD) matrices are an essential input to transportation models. A cost-efficient and widely used approach for estimating OD matrices involves the exploitation of flow counts from stationary traffic detectors. This estimation approach is also referred to as assignment-based OD matrix estimation because, typically, Dynamic Traffic Assignment (DTA) models are used to map the OD matrix to the link flows. The conventional DTA establish a complex non-linear relationship between the demand, and the link flows, adding an inherent complexity to the OD matrix estimation problem. In this paper, attempting to exploit the growing availability of Floating-Car Data (FCD), we suggest a solution approach that is based on a Data-Driven Network Assignment (DDNA) mechanism. The DDNA utilises the FCD from probe vehicles to capture congestion effects, providing a linear mapping of the OD matrix to the link flow observations. We present the results of two synthetic-data experiments that serve as proof of concept, indicating that if FCD are available, the computationally costly DTA may not be necessary for solving the OD matrix estimation problem., Funding Agencies|Swedish Transport Administration [TRV2018/132473, TRV2021/22404]; Swedish Energy Agency [46963-1]

Time-dependent Origin-Destination (OD) matrices are an essential input to transportation models. A cost-efficient and widely used approach for estimating OD matrices involves the exploitation of flow counts from stationary traffic detectors. This estimation approach is also referred to as assignment-based OD matrix estimation because, typically, Dynamic Traffic Assignment (DTA) models are used to map the OD matrix to the link flows. The conventional DTA establish a complex non-linear relationship between the demand, and the link flows, adding an inherent complexity to the OD matrix estimation problem. In this paper, attempting to exploit the growing availability of Floating-Car Data (FCD), we suggest a solution approach that is based on a Data-Driven Network Assignment (DDNA) mechanism. The DDNA utilises the FCD from probe vehicles to capture congestion effects, providing a linear mapping of the OD matrix to the link flow observations. We present the results of two synthetic-data experiments that serve as proof of concept, indicating that if FCD are available, the computationally costly DTA may not be necessary for solving the OD matrix estimation problem., Funding Agencies|Swedish Transport Administration [TRV2018/132473, TRV2021/22404]; Swedish Energy Agency [46963-1]

Time-dependent Origin-Destination (OD) matrices are an essential input to transportation models. A cost-efficient and widely used approach for estimating OD matrices involves the exploitation of flow counts from stationary traffic detectors. This estimation approach is also referred to as assignment-based OD matrix estimation because, typically, Dynamic Traffic Assignment (DTA) models are used to map the OD matrix to the link flows. The conventional DTA establish a complex non-linear relationship between the demand, and the link flows, adding an inherent complexity to the OD matrix estimation problem. In this paper, attempting to exploit the growing availability of Floating-Car Data (FCD), we suggest a solution approach that is based on a Data-Driven Network Assignment (DDNA) mechanism. The DDNA utilises the FCD from probe vehicles to capture congestion effects, providing a linear mapping of the OD matrix to the link flow observations. We present the results of two synthetic-data experiments that serve as proof of concept, indicating that if FCD are available, the computationally costly DTA may not be necessary for solving the OD matrix estimation problem., Funding Agencies|Swedish Transport Administration [TRV2018/132473, TRV2021/22404]; Swedish Energy Agency [46963-1]