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S.C. Calvert
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1
Human factor models has been an increasingly more popular topic in traffic models. The objective of these models vary, from simulating cooperative driving to understanding the behaviour of distracted drivers. Regardless of these diverse objectives, the reasons motivating these researches boil down to one single reason, safety. By better understanding human behaviour it should be possible to increase the safety of drivers on the road. One model which offers a systematic approach of studying human factors is the task-capability interface (TCI) model, it models the underlying human thought process and uses it as a proxy for other human factors. This has made the model quite successful in replicating various human factors, including distractions. Multiple papers have studied distractions using the TCI model as a tool but they all had their own specific approach to distractions. This leads to the identified gap in literature: how can distraction be systematically modelled in a TCI traffic model.\\
To fill this gap a distraction framework has been developed. This framework relies on the low-level characteristics of distractions and separates their lifecycle into three stages. These stages are the distraction trigger, intensity and effect. In order to verify if this framework is capable of systematically and accurately modelling distractions it was subjected to a validation test. To this end the distraction framework was incorporated into the Multi-scale model, which was found to be the most fitting TCI model, this resulted in the Distraction model. The new Distraction model was subsequently calibrated with a genetic algorithm to two different datasets with vastly different distraction, a continuous mental-visual distraction and a spontaneous auditory distraction. The results were compared to the results of specialized Distraction models.\\
The validation test results show that the Distraction model has shown limited improvements over the specialized baseline models and that most of the time its performance is equivalent. To be more specific the Distraction model is significantly better at estimating the headway of drivers compared to the baseline models when calibrating for single drivers. That said when it's used as a calibrated model it loses this edge and its performance is fully equivalent to the baseline models. With these results it can be concluded that the distraction framework functions as intended. Despite the limited amount of different distractions in the validation test it has shown that it is capable of systematically modelling distraction on a similar level as other specialized models. This also shows that the main benefits of the framework are its systematic approach and flexibility and not its performance capabilities. ...
To fill this gap a distraction framework has been developed. This framework relies on the low-level characteristics of distractions and separates their lifecycle into three stages. These stages are the distraction trigger, intensity and effect. In order to verify if this framework is capable of systematically and accurately modelling distractions it was subjected to a validation test. To this end the distraction framework was incorporated into the Multi-scale model, which was found to be the most fitting TCI model, this resulted in the Distraction model. The new Distraction model was subsequently calibrated with a genetic algorithm to two different datasets with vastly different distraction, a continuous mental-visual distraction and a spontaneous auditory distraction. The results were compared to the results of specialized Distraction models.\\
The validation test results show that the Distraction model has shown limited improvements over the specialized baseline models and that most of the time its performance is equivalent. To be more specific the Distraction model is significantly better at estimating the headway of drivers compared to the baseline models when calibrating for single drivers. That said when it's used as a calibrated model it loses this edge and its performance is fully equivalent to the baseline models. With these results it can be concluded that the distraction framework functions as intended. Despite the limited amount of different distractions in the validation test it has shown that it is capable of systematically modelling distraction on a similar level as other specialized models. This also shows that the main benefits of the framework are its systematic approach and flexibility and not its performance capabilities. ...
Human factor models has been an increasingly more popular topic in traffic models. The objective of these models vary, from simulating cooperative driving to understanding the behaviour of distracted drivers. Regardless of these diverse objectives, the reasons motivating these researches boil down to one single reason, safety. By better understanding human behaviour it should be possible to increase the safety of drivers on the road. One model which offers a systematic approach of studying human factors is the task-capability interface (TCI) model, it models the underlying human thought process and uses it as a proxy for other human factors. This has made the model quite successful in replicating various human factors, including distractions. Multiple papers have studied distractions using the TCI model as a tool but they all had their own specific approach to distractions. This leads to the identified gap in literature: how can distraction be systematically modelled in a TCI traffic model.\\
To fill this gap a distraction framework has been developed. This framework relies on the low-level characteristics of distractions and separates their lifecycle into three stages. These stages are the distraction trigger, intensity and effect. In order to verify if this framework is capable of systematically and accurately modelling distractions it was subjected to a validation test. To this end the distraction framework was incorporated into the Multi-scale model, which was found to be the most fitting TCI model, this resulted in the Distraction model. The new Distraction model was subsequently calibrated with a genetic algorithm to two different datasets with vastly different distraction, a continuous mental-visual distraction and a spontaneous auditory distraction. The results were compared to the results of specialized Distraction models.\\
The validation test results show that the Distraction model has shown limited improvements over the specialized baseline models and that most of the time its performance is equivalent. To be more specific the Distraction model is significantly better at estimating the headway of drivers compared to the baseline models when calibrating for single drivers. That said when it's used as a calibrated model it loses this edge and its performance is fully equivalent to the baseline models. With these results it can be concluded that the distraction framework functions as intended. Despite the limited amount of different distractions in the validation test it has shown that it is capable of systematically modelling distraction on a similar level as other specialized models. This also shows that the main benefits of the framework are its systematic approach and flexibility and not its performance capabilities.
To fill this gap a distraction framework has been developed. This framework relies on the low-level characteristics of distractions and separates their lifecycle into three stages. These stages are the distraction trigger, intensity and effect. In order to verify if this framework is capable of systematically and accurately modelling distractions it was subjected to a validation test. To this end the distraction framework was incorporated into the Multi-scale model, which was found to be the most fitting TCI model, this resulted in the Distraction model. The new Distraction model was subsequently calibrated with a genetic algorithm to two different datasets with vastly different distraction, a continuous mental-visual distraction and a spontaneous auditory distraction. The results were compared to the results of specialized Distraction models.\\
The validation test results show that the Distraction model has shown limited improvements over the specialized baseline models and that most of the time its performance is equivalent. To be more specific the Distraction model is significantly better at estimating the headway of drivers compared to the baseline models when calibrating for single drivers. That said when it's used as a calibrated model it loses this edge and its performance is fully equivalent to the baseline models. With these results it can be concluded that the distraction framework functions as intended. Despite the limited amount of different distractions in the validation test it has shown that it is capable of systematically modelling distraction on a similar level as other specialized models. This also shows that the main benefits of the framework are its systematic approach and flexibility and not its performance capabilities.
This research developed a novel assessment method to enable driving examiners to effectively evaluate the safe use of Advanced Driver Assistance Systems (ADAS) during practical driving exams in the Netherlands. An Assessment Matrix was developed and refined through expert interviews, observations, and case studies. The need to streamline licensing protocols, focus on safety critical competencies and expand examiner training were highlighted in the interviews. ADAS functionality across scenarios and constraints within the driving exam was observed in the case studies. Safety critical competencies identified through observations were monitoring systems, smooth manual takeover, and avoiding distraction. The refined ADAS matrix enabled standardized evaluation despite operational constraints. The findings emphasized integrating ADAS assessments into existing exams, hands-on examiner training, and public education to address knowledge gaps.Recommendations included streamlining assessments, evaluating overall competence, aligning training, providing immersive examiner education, and collaborations to match training with vehicle automation advances. Limitations included sample size and generalizations. For the first time, an empirically validated ADAS evaluation matrix was developed to promote integrating safety critical ADAS competency within the constraints of the practical driving exam. Further research could build on this to refine protocols and ensure that drivers acquired the needed skills as vehicle automation advances.
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This research developed a novel assessment method to enable driving examiners to effectively evaluate the safe use of Advanced Driver Assistance Systems (ADAS) during practical driving exams in the Netherlands. An Assessment Matrix was developed and refined through expert interviews, observations, and case studies. The need to streamline licensing protocols, focus on safety critical competencies and expand examiner training were highlighted in the interviews. ADAS functionality across scenarios and constraints within the driving exam was observed in the case studies. Safety critical competencies identified through observations were monitoring systems, smooth manual takeover, and avoiding distraction. The refined ADAS matrix enabled standardized evaluation despite operational constraints. The findings emphasized integrating ADAS assessments into existing exams, hands-on examiner training, and public education to address knowledge gaps.Recommendations included streamlining assessments, evaluating overall competence, aligning training, providing immersive examiner education, and collaborations to match training with vehicle automation advances. Limitations included sample size and generalizations. For the first time, an empirically validated ADAS evaluation matrix was developed to promote integrating safety critical ADAS competency within the constraints of the practical driving exam. Further research could build on this to refine protocols and ensure that drivers acquired the needed skills as vehicle automation advances.
Master thesis
(2022)
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Roberto Villena Gonzales, W. Daamen, D.C. Duives, S.C. Calvert, Nienke Valkhoff
The COVID-19 pandemic has changed people's lives in greater or lesser degree since the outbreak back in December 2019 in Wuhan, China. Due to the high transmissibility of the virus and with the aim of preventing the virus from continue spreading, several measures have been applied during the last two years, which now have become part of people's daily life. One of these measures is physical distancing, which has been proven to be an effective way to reduce the transmission risk. The objective of this research is to understand how the walking behaviour of pedestrians has changed during COVID-19 because of physical distancing at bidirectional flows in locations where people might encounter difficulties for complying with this measure, and conduct a calibration of the pedestrian simulation model Pedestrian Dynamics (PD) to improve its accuracy for reproducing such behaviour. As a result, this research aims at determining the capability of the model to reproduce the walking behaviour during the pandemic. The results show that the walking behaviour has changed over the course of the pandemic, since in 2020 and 2021 pedestrians kept respectively larger and shorter distances than in 2019. Moreover, a larger variability in velocity and higher effort to traverse the measurement area suggest changes in the awareness of their surroundings during the pandemic. The calibration results show that the relaxation time is the most relevant parameter as the accuracy of the model significantly changes when values lower than its default are used, which in turn indicates a faster reaction of pedestrians. In conclusion, a calibrated model considering one parameter would not yield accurate predictions if a general usage for all COVID-19 scenarios is intended. Finally, different types of behaviour are recommended to be analysed to obtain insight into the capability of the model to reproduce them and moreover, the behavioural assessment at strategic and tactical level are adviced, since this research focused on the impact of physical distancing on the behaviour at operational level.
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The COVID-19 pandemic has changed people's lives in greater or lesser degree since the outbreak back in December 2019 in Wuhan, China. Due to the high transmissibility of the virus and with the aim of preventing the virus from continue spreading, several measures have been applied during the last two years, which now have become part of people's daily life. One of these measures is physical distancing, which has been proven to be an effective way to reduce the transmission risk. The objective of this research is to understand how the walking behaviour of pedestrians has changed during COVID-19 because of physical distancing at bidirectional flows in locations where people might encounter difficulties for complying with this measure, and conduct a calibration of the pedestrian simulation model Pedestrian Dynamics (PD) to improve its accuracy for reproducing such behaviour. As a result, this research aims at determining the capability of the model to reproduce the walking behaviour during the pandemic. The results show that the walking behaviour has changed over the course of the pandemic, since in 2020 and 2021 pedestrians kept respectively larger and shorter distances than in 2019. Moreover, a larger variability in velocity and higher effort to traverse the measurement area suggest changes in the awareness of their surroundings during the pandemic. The calibration results show that the relaxation time is the most relevant parameter as the accuracy of the model significantly changes when values lower than its default are used, which in turn indicates a faster reaction of pedestrians. In conclusion, a calibrated model considering one parameter would not yield accurate predictions if a general usage for all COVID-19 scenarios is intended. Finally, different types of behaviour are recommended to be analysed to obtain insight into the capability of the model to reproduce them and moreover, the behavioural assessment at strategic and tactical level are adviced, since this research focused on the impact of physical distancing on the behaviour at operational level.
Traffic jams occurring on highways cause increased travel time as well as increased fuel consumption and crashes. Traffic jams without a clear cause, such as an on-ramp or an accident, are called phantom traffic jams and are said to make up 50% of all traffic jams. They are the result of an unstable traffic flow caused by human driving behaviour. Recent studies have shown how automating the longitudinal vehicle motion of only 5% of all cars in the flow can dissipate phantom traffic jams. However, automation introduces new problems, mainly regarding safety when human drivers need to take over the control. This research tries to answer whether phantom traffic jams can be dissolved or prevented using haptic shared control. This means of control keeps the human in the loop and would therefore eliminate the takeover problems while still benefiting from the advantages of automation. 24 participants took part in a driving experiment in a fixed base simulator. In these experiments, we tested haptic shared control against manual control and full automation for longitudinal motion. Results show that traffic jam dissipation performance for haptic shared control lies between manual control and automation. The number of unsafe situations is reduced compared to the automated condition. We conclude that haptic shared control is able to reduce the increased fuel consumption and crashes caused by phantom traffic jams.
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Traffic jams occurring on highways cause increased travel time as well as increased fuel consumption and crashes. Traffic jams without a clear cause, such as an on-ramp or an accident, are called phantom traffic jams and are said to make up 50% of all traffic jams. They are the result of an unstable traffic flow caused by human driving behaviour. Recent studies have shown how automating the longitudinal vehicle motion of only 5% of all cars in the flow can dissipate phantom traffic jams. However, automation introduces new problems, mainly regarding safety when human drivers need to take over the control. This research tries to answer whether phantom traffic jams can be dissolved or prevented using haptic shared control. This means of control keeps the human in the loop and would therefore eliminate the takeover problems while still benefiting from the advantages of automation. 24 participants took part in a driving experiment in a fixed base simulator. In these experiments, we tested haptic shared control against manual control and full automation for longitudinal motion. Results show that traffic jam dissipation performance for haptic shared control lies between manual control and automation. The number of unsafe situations is reduced compared to the automated condition. We conclude that haptic shared control is able to reduce the increased fuel consumption and crashes caused by phantom traffic jams.
In recent years, the amount of traffic on the highways has increased continuously and in particular freight traffic. Despite solutions to maximize roadway capacity, the drop of capacity after congestions sets in, remains an active field of study. The influence of freight traffic on traffic flow has received little attention, especially regarding the capacity drop. The Kaplan-Meier Product Limit Method was used to estimate capacity and recovery distributions for selected sites to overcome stochastic characteristics of traffic flow and investigate the relation between heavy vehicle share and capacity drop at Dutch highways. Furthermore, a simulation study was executed to investigate increased heavy vehicle share scenarios and changing physical and operational characteristics of heavy vehicles. The empirical results show a connection between heavy vehicle share and the capacity drop, although not statistically significant. Currently, chaotic properties of breakdown flow seem to superimpose the impact. However, it is possible that the effect becomes influential as the current maximum observed share of heavy vehicles during breakdown grows from 9% up to 15%, which appeared to be the worst case scenario in simulation. Besides, concern is raised as a decreasing breakdown capacity was observed on several Dutch highways, even after correction with the PCE values of the increasing heavy vehicle share.
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In recent years, the amount of traffic on the highways has increased continuously and in particular freight traffic. Despite solutions to maximize roadway capacity, the drop of capacity after congestions sets in, remains an active field of study. The influence of freight traffic on traffic flow has received little attention, especially regarding the capacity drop. The Kaplan-Meier Product Limit Method was used to estimate capacity and recovery distributions for selected sites to overcome stochastic characteristics of traffic flow and investigate the relation between heavy vehicle share and capacity drop at Dutch highways. Furthermore, a simulation study was executed to investigate increased heavy vehicle share scenarios and changing physical and operational characteristics of heavy vehicles. The empirical results show a connection between heavy vehicle share and the capacity drop, although not statistically significant. Currently, chaotic properties of breakdown flow seem to superimpose the impact. However, it is possible that the effect becomes influential as the current maximum observed share of heavy vehicles during breakdown grows from 9% up to 15%, which appeared to be the worst case scenario in simulation. Besides, concern is raised as a decreasing breakdown capacity was observed on several Dutch highways, even after correction with the PCE values of the increasing heavy vehicle share.
Master thesis
(2020)
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Omiros Athanasiadis, Bart van Arem, Eleonora Papadimitriou, Simeon Calvert, Gerdien Klunder
The question of how well in terms of safety can a driver take over control of an automated vehicle in response to an emergency situation is of crucial importance. Most of the studies performed so far focus on the drivers’ reaction times and the mechanisms behind the transition. In this study, an effort is made to incorporate the braking times that are required in order to finalize a safety maneuver, with the aim to assess the safety implications of the entire transition in control. For this purpose, a new methodology was developed and a simulation model was used in order to simulate platoons of CACC equipped vehicles. Two new KPIs were defined: the Time to Control and the Safe Time Budget. The results suggest that higher number of critical events and crashes are associated with higher market penetration rates. This reveals that despite the fact that AV can in general increase traffic efficiency and safety, when it comes to emergency situations where safety is inextricably linked to the combination of AV and driver performance, overall safety may be compromised under certain conditions. In addition, the results revealed a strong connection of the above-mentioned action times with the initial speed of the vehicles involved in a conflict. The findings of this research, point to new directions particularly in concern to the extension of the operational design domain of automated vehicles in order to minimize system deactivations, and also with regard to the need for better prediction models and safety assessment tools.
...
The question of how well in terms of safety can a driver take over control of an automated vehicle in response to an emergency situation is of crucial importance. Most of the studies performed so far focus on the drivers’ reaction times and the mechanisms behind the transition. In this study, an effort is made to incorporate the braking times that are required in order to finalize a safety maneuver, with the aim to assess the safety implications of the entire transition in control. For this purpose, a new methodology was developed and a simulation model was used in order to simulate platoons of CACC equipped vehicles. Two new KPIs were defined: the Time to Control and the Safe Time Budget. The results suggest that higher number of critical events and crashes are associated with higher market penetration rates. This reveals that despite the fact that AV can in general increase traffic efficiency and safety, when it comes to emergency situations where safety is inextricably linked to the combination of AV and driver performance, overall safety may be compromised under certain conditions. In addition, the results revealed a strong connection of the above-mentioned action times with the initial speed of the vehicles involved in a conflict. The findings of this research, point to new directions particularly in concern to the extension of the operational design domain of automated vehicles in order to minimize system deactivations, and also with regard to the need for better prediction models and safety assessment tools.
Framework for Determining Impacts of Malfunctioning of DTM Systems on Traffic Flow
Development and A Case Study for the Amsterdam Region
Master thesis
(2020)
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Qi An, Hans van Lint, Serge Hoogendoorn, Henk Taale, Simeon Calvert, Martine van den Boomen, Zlatan Muhurdarevic
Dynamic traffic management (DTM) plays an important role from Dutch policy perspective to prevent road congestion and has been developed from control strategies to services. Five traffic control centers, 22 different DTM systems with 35 functions and over 50,000 DTM components make up the national traffic management network in the Netherlands. The malfunctioning of the DTM systems is expected to create negative impacts to the traffic, proper maintenance planning is necessary to ensure their availabilities. However, there is less knowledge about the DTM malfunctions, which makes it difficult to monetize the malfunction effects and therefore to optimally deploy the maintenance budget. In this research, a macroscopic dynamic traffic assignment model “MARPLE” is used to evaluate the social costs of the DTM malfunctions according to the failure function, failure duration, and failure location.
The motorway network around Amsterdam is chosen as the study area in this research, and four DTM systems and measures were evaluated, including the rush hour lane (RHL), the motorway traffic management (MTM) system, the dynamic route information panels (DRIPs) and the ramp metering (RM) system. By conversing the DTM malfunctions into the motorway network, the introduced impacts to the traffic both in local and network levels are identified.
This research made the first attempt to modify DTM malfunctions in a macroscopic dynamic traffic assignment model, and a methodology was developed to calculate the malfunction costs both in traffic flow and safety aspects. The outcome of this research answered what-if questions with regarding to DTM malfunctions, it also proved the feasibility of the ambition to translate the DTM malfunction impacts at a network level into its social costs, according to which the maintenance strategy for the DTM systems can be better deployed. Overall, the initial goal of calculating the malfunction costs of the DTM systems with a newly developed methodology is met. Through the identified limitations and improvement strategies, the framework developed in this study could offer the possibility to refine the analysis, and/or easily be applied to other DTM systems and road parts. ...
The motorway network around Amsterdam is chosen as the study area in this research, and four DTM systems and measures were evaluated, including the rush hour lane (RHL), the motorway traffic management (MTM) system, the dynamic route information panels (DRIPs) and the ramp metering (RM) system. By conversing the DTM malfunctions into the motorway network, the introduced impacts to the traffic both in local and network levels are identified.
This research made the first attempt to modify DTM malfunctions in a macroscopic dynamic traffic assignment model, and a methodology was developed to calculate the malfunction costs both in traffic flow and safety aspects. The outcome of this research answered what-if questions with regarding to DTM malfunctions, it also proved the feasibility of the ambition to translate the DTM malfunction impacts at a network level into its social costs, according to which the maintenance strategy for the DTM systems can be better deployed. Overall, the initial goal of calculating the malfunction costs of the DTM systems with a newly developed methodology is met. Through the identified limitations and improvement strategies, the framework developed in this study could offer the possibility to refine the analysis, and/or easily be applied to other DTM systems and road parts. ...
Dynamic traffic management (DTM) plays an important role from Dutch policy perspective to prevent road congestion and has been developed from control strategies to services. Five traffic control centers, 22 different DTM systems with 35 functions and over 50,000 DTM components make up the national traffic management network in the Netherlands. The malfunctioning of the DTM systems is expected to create negative impacts to the traffic, proper maintenance planning is necessary to ensure their availabilities. However, there is less knowledge about the DTM malfunctions, which makes it difficult to monetize the malfunction effects and therefore to optimally deploy the maintenance budget. In this research, a macroscopic dynamic traffic assignment model “MARPLE” is used to evaluate the social costs of the DTM malfunctions according to the failure function, failure duration, and failure location.
The motorway network around Amsterdam is chosen as the study area in this research, and four DTM systems and measures were evaluated, including the rush hour lane (RHL), the motorway traffic management (MTM) system, the dynamic route information panels (DRIPs) and the ramp metering (RM) system. By conversing the DTM malfunctions into the motorway network, the introduced impacts to the traffic both in local and network levels are identified.
This research made the first attempt to modify DTM malfunctions in a macroscopic dynamic traffic assignment model, and a methodology was developed to calculate the malfunction costs both in traffic flow and safety aspects. The outcome of this research answered what-if questions with regarding to DTM malfunctions, it also proved the feasibility of the ambition to translate the DTM malfunction impacts at a network level into its social costs, according to which the maintenance strategy for the DTM systems can be better deployed. Overall, the initial goal of calculating the malfunction costs of the DTM systems with a newly developed methodology is met. Through the identified limitations and improvement strategies, the framework developed in this study could offer the possibility to refine the analysis, and/or easily be applied to other DTM systems and road parts.
The motorway network around Amsterdam is chosen as the study area in this research, and four DTM systems and measures were evaluated, including the rush hour lane (RHL), the motorway traffic management (MTM) system, the dynamic route information panels (DRIPs) and the ramp metering (RM) system. By conversing the DTM malfunctions into the motorway network, the introduced impacts to the traffic both in local and network levels are identified.
This research made the first attempt to modify DTM malfunctions in a macroscopic dynamic traffic assignment model, and a methodology was developed to calculate the malfunction costs both in traffic flow and safety aspects. The outcome of this research answered what-if questions with regarding to DTM malfunctions, it also proved the feasibility of the ambition to translate the DTM malfunction impacts at a network level into its social costs, according to which the maintenance strategy for the DTM systems can be better deployed. Overall, the initial goal of calculating the malfunction costs of the DTM systems with a newly developed methodology is met. Through the identified limitations and improvement strategies, the framework developed in this study could offer the possibility to refine the analysis, and/or easily be applied to other DTM systems and road parts.