Haneen Farah - Profile on Academia.edu (original) (raw)
Papers by Haneen Farah
Transportation Research Part B: Methodological, 2018
Adaptive Cruise Control (ACC) and automated vehicles can contribute to reduce traffic congestion ... more Adaptive Cruise Control (ACC) and automated vehicles can contribute to reduce traffic congestion and accidents. Recently, an on-road study has shown that drivers may prefer to deactivate full-range ACC when closing in on a slower leader and to overrule it by pressing the gas pedal a few seconds after the activation of the system. Notwithstanding the influence of these control transitions on driver behaviour, a theoretical framework explaining driver decisions to transfer control and to regulate the target speed in full-range ACC is currently missing. This research develops a modelling framework describing the underlying decisionmaking process of drivers with full-range ACC at an operational level, grounded on Risk Allostasis Theory (RAT). Based on this theory, a driver will choose to resume manual control or to regulate the ACC target speed if its perceived level of risk feeling and task difficulty falls outside the range considered acceptable to maintain the system active. The feeling of risk and task difficulty evaluation is formulated as a generalized ordered probit model with random thresholds, which vary between drivers and within drivers over time. The ACC system state choices are formulated as logit models and the ACC target speed regulations as regression models, in which correlations between system state choices and target speed regulations are captured explicitly. This continuous-discrete choice model framework is able to address interdependencies across drivers' decisions in terms of causality, unobserved driver characteristics, and state dependency, and to capture inconsistencies in drivers' decision making that might be caused by human factors. The model was estimated using a dataset collected in an on-road experiment with fullrange ACC. The results reveal that driver decisions to resume manual control and to regulate the target speed in full-range ACC can be interpreted based on the RAT. The model can be used to forecast driver response to a driving assistance system that adapts its settings to prevent control transitions while guaranteeing safety and comfort. The model can also be implemented into a microscopic traffic flow simulation to evaluate the impact of ACC on traffic flow efficiency and safety accounting for control transitions and target speed regulations.
Information
Most of cyclists’ fatalities originate from collisions with motorized vehicles. It is expected th... more Most of cyclists’ fatalities originate from collisions with motorized vehicles. It is expected that automated vehicles (AV) will be safer than human-driven vehicles, but this depends on the nature of interactions between non-automated road users, among them cyclists. Little research on the interactions between cyclists and AVs exists. This study aims to determine the main factors influencing cyclists’ crossing intentions when interacting with an automated vehicle as compared to a conventional vehicle (CV) using a 360° video-based virtual reality (VR) method. The considered factors in this study included vehicle type, gap size between cyclist and vehicle, vehicle speed, and right of way. Each factor had two levels. In addition, cyclist’s self-reported behavior and trust in automated vehicles were also measured. Forty-seven participants experienced 16 different crossing scenarios in a repeated measures study using VR. These scenarios are the result of combinations of the studied facto...
Journal of Advanced Transportation
Traffic microsimulation has a functional role in understanding the traffic performance on the roa... more Traffic microsimulation has a functional role in understanding the traffic performance on the road network. This study originated with intent to understand traffic microsimulation and its use in modeling connected and automated vehicles (CAVs). Initially, the paper focuses on understanding the evolution of traffic microsimulation and on examining the various commercial and open-source simulation platforms available and their importance in traffic microsimulation studies. Following this, current autonomous vehicle (AV) microsimulation strategies are reviewed. From the review analysis, it is observed that AVs are modeled in traffic microsimulation with two sets of strategies. In the first set, the inbuilt models are used to replicate the driving behavior of AVs by adapting the models’ parameters. In the second strategy, AV behavior is programmed with the help of externalities (e.g., Application Programming Interface (API)). Studies simulating AVs with inbuilt models used mostly VISSIM...
Intersection Control Type Effect on Automated Vehicle Operation
CICTP 2019
Infrastructure for Automated and Connected Driving: State of the Art and Future Research Directions
Road Vehicle Automation 4
IEEE Open Journal of Intelligent Transportation Systems
This work was supported in part by the Applied and Technical Sciences (TTW), a subdomain of the D... more This work was supported in part by the Applied and Technical Sciences (TTW), a subdomain of the Dutch Institute for Scientific Research (NWO) through the Project Safe and Efficient Operation of Automated and Human-Driven Vehicles in Mixed Traffic (SAMEN) under Contract 17187, and in part by the Netherlands Organization for Scientific Research (NWO) through the Project Spatial and Transport Impacts of Automated Driving (STAD) under Contract 438-15-161.
Allowing Level 4 Automated Vehicles (AVs) to drive on highways could potentially have an impact o... more Allowing Level 4 Automated Vehicles (AVs) to drive on highways could potentially have an impact on the road network performance. Although it might probably take a while before AVs are on the road, National Road Authorities (NRAs) are already concerned about understanding what changes would be required on their current infrastructure to make it ready for AVs. In this study, we simulate part of the highway network in the Netherlands, the region of Rotterdam The Hague, to investigate the impact of AVs on the network performance in terms of network travel times and distances travelled. Results allow us to conclude that 50% AVs (Level 4) result in an increase in distance travelled on highways but a decrease in the total network travel times and corresponding delays.
An Empirical Analysis to Assess the Operational Design Domain of Lane Keeping System Equipped Vehicles Combining Objective and Subjective Risk Measures
IEEE Transactions on Intelligent Transportation Systems
Critical Assessment of Microscopic Simulation Models for Simulating Turbulence around Motorway Ramps
Journal of Transportation Engineering, Part A: Systems
Accident Analysis & Prevention
Observed accidents have been the main resource for road safety analysis over the past decades. Al... more Observed accidents have been the main resource for road safety analysis over the past decades. Although such reliance seems quite straightforward, the rare nature of these events has made safety difficult to assess, especially for new and innovative traffic treatments. Surrogate measures of safety have allowed to step away from traditional safety performance functions and analyze safety performance without relying on accident records. In recent years, the use of extreme value theory (EV) models in combination with surrogate safety measures to estimate accident probabilities has gained popularity within the safety community. In this paper we extend existing efforts on EV for accident probability estimation for two dependent surrogate measures. Using detailed trajectory data from a driving simulator, we model the joint probability of head-on and rear-end collisions in passing maneuvers. In our estimation we account for driver specific characteristics and road infrastructure variables. We show that accounting for these factors improve the head-on collision prob
How do drivers negotiate horizontal ramp curves in system interchanges in the Netherlands?
Safety Science
Transportation Research Part F: Traffic Psychology and Behaviour
Heart rate data are often collected in human factors studies, including those into vehicle automa... more Heart rate data are often collected in human factors studies, including those into vehicle automation. Advances in open hardware platforms and off-the-shelf photoplethysmogram (PPG) sensors allow the non-intrusive collection of heart rate data at very low cost. However, the signal is not trivial to analyse, since the morphology of PPG waveforms differs from electrocardiogram (ECG) waveforms and shows different noise patterns. Few validated open source available algorithms exist that handle PPG data well, as most of these algorithms are specifically designed for ECG data. In this paper we present the validation of a novel algorithm named HeartPy, useful for the analysis of heart rate data collected in noisy settings, such as when driving a car or when in a simulator. We benchmark the performance on two types of datasets and show that the developed algorithm performs well. Further research steps are discussed.
Safety
Automated vehicles (AVs) are expected to assist in decreasing road traffic fatalities, particular... more Automated vehicles (AVs) are expected to assist in decreasing road traffic fatalities, particularly among passenger cars. However, until now limited research has been conducted on how they will impact the safety of vulnerable road users (VRUs) (i.e., cyclists and pedestrians). Therefore, there is a clear need to start taking into account the interactions between AVs and VRUs as an integrated element of the transport network, especially in urban areas where they are dominant. The objective of this study is to verify whether the anticipated implementation of AVs can actually improve cyclists’ safety. For this purpose, the microscopic traffic flow simulation software PTV Vissim combined with the surrogate safety assessment model (SSAM) were utilized. The road network used for this analysis was generated based on a real study case in a medium-sized city in Belgium, where narrow streets in the city center are shared on many occasions between vehicles and cyclists. The findings of the ana...
Transportation Research Part F: Traffic Psychology and Behaviour
Interaction between pedestrians and automated vehicles A Wizard of Oz experiment
Driving behaviour at motorway ramps and weaving segments based on empirical trajectory data
Transportation Research Part C: Emerging Technologies
A conceptual model for persuasive in-vehicle technology to influence tactical level driver behaviour
Transportation Research Part F: Traffic Psychology and Behaviour
Transportation Research Record: Journal of the Transportation Research Board
The present study aims to add to the literature on driver workload prediction using machine learn... more The present study aims to add to the literature on driver workload prediction using machine learning methods. The main aim is to develop workload prediction on a multi-level basis, rather than a binary high/low distinction as often found in literature. The presented approach relies on measures that can be obtained unobtrusively in the driving environment with off-the-shelf sensors, and on machine learning methods that can be implemented in low-power embedded systems. Two simulator studies were performed, one inducing workload using realistic driving conditions, and one inducing workload with a relatively demanding lane-keeping task. Individual and group-based machine learning models were trained on both datasets and evaluated. For the group-based models the generalizing capability, that is the performance when predicting data from previously unseen individuals, was also assessed. Results show that multi-level workload prediction on the individual and group level works well, achievin...
Special issue on simulation of traffic safety in the era of advances in technologies
Accident; analysis and prevention, 2018
Transportation Research Part F: Traffic Psychology and Behaviour
The study examined the influence of affect induction on actual risk-taking behavior in a driving ... more The study examined the influence of affect induction on actual risk-taking behavior in a driving simulator, as well as the links between personal variables (relevance of driving to selfesteem, sensation seeking) and the level of risky driving. Eighty young drivers aged 18-21 (M=19.24, SD=0.75) were randomly divided into four induction groups: relaxing positive affect; arousing positive affect; negative affect; and neutral affect. The participants drove on a simulator, with various parameters of risky driving measured before and after emotion priming.
Transportation Research Record: Journal of the Transportation Research Board
Passing maneuvers allow faster drivers to continue driving at their own desired speeds without be... more Passing maneuvers allow faster drivers to continue driving at their own desired speeds without being delayed behind an impeding vehicle. On two lane rural roads, this requires from the passing driver to occupy the opposing lane. This has tremendous implications on safety and operation of two-lane roads. In the literature, several studies investigated the passing behavior of drivers, and some have used driving simulators to analyze drivers' behavior during following and passing maneuvers. However, the validity of simulators has not been ensured, as their results have rarely been compared with real data. The main objective of this study is to compare drivers' passing behavior as observed in the field with passing behavior in a driving simulator. For this purpose, data on passing performance and passing gap acceptance decisions is required. This paper carried out a comparative analysis of the most significant variables related to passing behavior. The results showed similarities between passing time and passing distance of completed maneuvers (during the occupation of the opposing lane). However, drivers passed faster in the driving simulator, keeping higher clearances. Gap acceptance decisions were also found to be similar, as the distributions of both accepted and rejected gaps were similar, although critical gaps were found to be lower in the driving simulator. This might be explained by the absence of objective risks. Consequently, the applicability of driving simulation seems reasonable, although some improvements are still possible, in order to account for sight distance limitations, and to reproduce better the opposing traffic flow.
Transportation Research Part B: Methodological, 2018
Adaptive Cruise Control (ACC) and automated vehicles can contribute to reduce traffic congestion ... more Adaptive Cruise Control (ACC) and automated vehicles can contribute to reduce traffic congestion and accidents. Recently, an on-road study has shown that drivers may prefer to deactivate full-range ACC when closing in on a slower leader and to overrule it by pressing the gas pedal a few seconds after the activation of the system. Notwithstanding the influence of these control transitions on driver behaviour, a theoretical framework explaining driver decisions to transfer control and to regulate the target speed in full-range ACC is currently missing. This research develops a modelling framework describing the underlying decisionmaking process of drivers with full-range ACC at an operational level, grounded on Risk Allostasis Theory (RAT). Based on this theory, a driver will choose to resume manual control or to regulate the ACC target speed if its perceived level of risk feeling and task difficulty falls outside the range considered acceptable to maintain the system active. The feeling of risk and task difficulty evaluation is formulated as a generalized ordered probit model with random thresholds, which vary between drivers and within drivers over time. The ACC system state choices are formulated as logit models and the ACC target speed regulations as regression models, in which correlations between system state choices and target speed regulations are captured explicitly. This continuous-discrete choice model framework is able to address interdependencies across drivers' decisions in terms of causality, unobserved driver characteristics, and state dependency, and to capture inconsistencies in drivers' decision making that might be caused by human factors. The model was estimated using a dataset collected in an on-road experiment with fullrange ACC. The results reveal that driver decisions to resume manual control and to regulate the target speed in full-range ACC can be interpreted based on the RAT. The model can be used to forecast driver response to a driving assistance system that adapts its settings to prevent control transitions while guaranteeing safety and comfort. The model can also be implemented into a microscopic traffic flow simulation to evaluate the impact of ACC on traffic flow efficiency and safety accounting for control transitions and target speed regulations.
Information
Most of cyclists’ fatalities originate from collisions with motorized vehicles. It is expected th... more Most of cyclists’ fatalities originate from collisions with motorized vehicles. It is expected that automated vehicles (AV) will be safer than human-driven vehicles, but this depends on the nature of interactions between non-automated road users, among them cyclists. Little research on the interactions between cyclists and AVs exists. This study aims to determine the main factors influencing cyclists’ crossing intentions when interacting with an automated vehicle as compared to a conventional vehicle (CV) using a 360° video-based virtual reality (VR) method. The considered factors in this study included vehicle type, gap size between cyclist and vehicle, vehicle speed, and right of way. Each factor had two levels. In addition, cyclist’s self-reported behavior and trust in automated vehicles were also measured. Forty-seven participants experienced 16 different crossing scenarios in a repeated measures study using VR. These scenarios are the result of combinations of the studied facto...
Journal of Advanced Transportation
Traffic microsimulation has a functional role in understanding the traffic performance on the roa... more Traffic microsimulation has a functional role in understanding the traffic performance on the road network. This study originated with intent to understand traffic microsimulation and its use in modeling connected and automated vehicles (CAVs). Initially, the paper focuses on understanding the evolution of traffic microsimulation and on examining the various commercial and open-source simulation platforms available and their importance in traffic microsimulation studies. Following this, current autonomous vehicle (AV) microsimulation strategies are reviewed. From the review analysis, it is observed that AVs are modeled in traffic microsimulation with two sets of strategies. In the first set, the inbuilt models are used to replicate the driving behavior of AVs by adapting the models’ parameters. In the second strategy, AV behavior is programmed with the help of externalities (e.g., Application Programming Interface (API)). Studies simulating AVs with inbuilt models used mostly VISSIM...
Intersection Control Type Effect on Automated Vehicle Operation
CICTP 2019
Infrastructure for Automated and Connected Driving: State of the Art and Future Research Directions
Road Vehicle Automation 4
IEEE Open Journal of Intelligent Transportation Systems
This work was supported in part by the Applied and Technical Sciences (TTW), a subdomain of the D... more This work was supported in part by the Applied and Technical Sciences (TTW), a subdomain of the Dutch Institute for Scientific Research (NWO) through the Project Safe and Efficient Operation of Automated and Human-Driven Vehicles in Mixed Traffic (SAMEN) under Contract 17187, and in part by the Netherlands Organization for Scientific Research (NWO) through the Project Spatial and Transport Impacts of Automated Driving (STAD) under Contract 438-15-161.
Allowing Level 4 Automated Vehicles (AVs) to drive on highways could potentially have an impact o... more Allowing Level 4 Automated Vehicles (AVs) to drive on highways could potentially have an impact on the road network performance. Although it might probably take a while before AVs are on the road, National Road Authorities (NRAs) are already concerned about understanding what changes would be required on their current infrastructure to make it ready for AVs. In this study, we simulate part of the highway network in the Netherlands, the region of Rotterdam The Hague, to investigate the impact of AVs on the network performance in terms of network travel times and distances travelled. Results allow us to conclude that 50% AVs (Level 4) result in an increase in distance travelled on highways but a decrease in the total network travel times and corresponding delays.
An Empirical Analysis to Assess the Operational Design Domain of Lane Keeping System Equipped Vehicles Combining Objective and Subjective Risk Measures
IEEE Transactions on Intelligent Transportation Systems
Critical Assessment of Microscopic Simulation Models for Simulating Turbulence around Motorway Ramps
Journal of Transportation Engineering, Part A: Systems
Accident Analysis & Prevention
Observed accidents have been the main resource for road safety analysis over the past decades. Al... more Observed accidents have been the main resource for road safety analysis over the past decades. Although such reliance seems quite straightforward, the rare nature of these events has made safety difficult to assess, especially for new and innovative traffic treatments. Surrogate measures of safety have allowed to step away from traditional safety performance functions and analyze safety performance without relying on accident records. In recent years, the use of extreme value theory (EV) models in combination with surrogate safety measures to estimate accident probabilities has gained popularity within the safety community. In this paper we extend existing efforts on EV for accident probability estimation for two dependent surrogate measures. Using detailed trajectory data from a driving simulator, we model the joint probability of head-on and rear-end collisions in passing maneuvers. In our estimation we account for driver specific characteristics and road infrastructure variables. We show that accounting for these factors improve the head-on collision prob
How do drivers negotiate horizontal ramp curves in system interchanges in the Netherlands?
Safety Science
Transportation Research Part F: Traffic Psychology and Behaviour
Heart rate data are often collected in human factors studies, including those into vehicle automa... more Heart rate data are often collected in human factors studies, including those into vehicle automation. Advances in open hardware platforms and off-the-shelf photoplethysmogram (PPG) sensors allow the non-intrusive collection of heart rate data at very low cost. However, the signal is not trivial to analyse, since the morphology of PPG waveforms differs from electrocardiogram (ECG) waveforms and shows different noise patterns. Few validated open source available algorithms exist that handle PPG data well, as most of these algorithms are specifically designed for ECG data. In this paper we present the validation of a novel algorithm named HeartPy, useful for the analysis of heart rate data collected in noisy settings, such as when driving a car or when in a simulator. We benchmark the performance on two types of datasets and show that the developed algorithm performs well. Further research steps are discussed.
Safety
Automated vehicles (AVs) are expected to assist in decreasing road traffic fatalities, particular... more Automated vehicles (AVs) are expected to assist in decreasing road traffic fatalities, particularly among passenger cars. However, until now limited research has been conducted on how they will impact the safety of vulnerable road users (VRUs) (i.e., cyclists and pedestrians). Therefore, there is a clear need to start taking into account the interactions between AVs and VRUs as an integrated element of the transport network, especially in urban areas where they are dominant. The objective of this study is to verify whether the anticipated implementation of AVs can actually improve cyclists’ safety. For this purpose, the microscopic traffic flow simulation software PTV Vissim combined with the surrogate safety assessment model (SSAM) were utilized. The road network used for this analysis was generated based on a real study case in a medium-sized city in Belgium, where narrow streets in the city center are shared on many occasions between vehicles and cyclists. The findings of the ana...
Transportation Research Part F: Traffic Psychology and Behaviour
Interaction between pedestrians and automated vehicles A Wizard of Oz experiment
Driving behaviour at motorway ramps and weaving segments based on empirical trajectory data
Transportation Research Part C: Emerging Technologies
A conceptual model for persuasive in-vehicle technology to influence tactical level driver behaviour
Transportation Research Part F: Traffic Psychology and Behaviour
Transportation Research Record: Journal of the Transportation Research Board
The present study aims to add to the literature on driver workload prediction using machine learn... more The present study aims to add to the literature on driver workload prediction using machine learning methods. The main aim is to develop workload prediction on a multi-level basis, rather than a binary high/low distinction as often found in literature. The presented approach relies on measures that can be obtained unobtrusively in the driving environment with off-the-shelf sensors, and on machine learning methods that can be implemented in low-power embedded systems. Two simulator studies were performed, one inducing workload using realistic driving conditions, and one inducing workload with a relatively demanding lane-keeping task. Individual and group-based machine learning models were trained on both datasets and evaluated. For the group-based models the generalizing capability, that is the performance when predicting data from previously unseen individuals, was also assessed. Results show that multi-level workload prediction on the individual and group level works well, achievin...
Special issue on simulation of traffic safety in the era of advances in technologies
Accident; analysis and prevention, 2018
Transportation Research Part F: Traffic Psychology and Behaviour
The study examined the influence of affect induction on actual risk-taking behavior in a driving ... more The study examined the influence of affect induction on actual risk-taking behavior in a driving simulator, as well as the links between personal variables (relevance of driving to selfesteem, sensation seeking) and the level of risky driving. Eighty young drivers aged 18-21 (M=19.24, SD=0.75) were randomly divided into four induction groups: relaxing positive affect; arousing positive affect; negative affect; and neutral affect. The participants drove on a simulator, with various parameters of risky driving measured before and after emotion priming.
Transportation Research Record: Journal of the Transportation Research Board
Passing maneuvers allow faster drivers to continue driving at their own desired speeds without be... more Passing maneuvers allow faster drivers to continue driving at their own desired speeds without being delayed behind an impeding vehicle. On two lane rural roads, this requires from the passing driver to occupy the opposing lane. This has tremendous implications on safety and operation of two-lane roads. In the literature, several studies investigated the passing behavior of drivers, and some have used driving simulators to analyze drivers' behavior during following and passing maneuvers. However, the validity of simulators has not been ensured, as their results have rarely been compared with real data. The main objective of this study is to compare drivers' passing behavior as observed in the field with passing behavior in a driving simulator. For this purpose, data on passing performance and passing gap acceptance decisions is required. This paper carried out a comparative analysis of the most significant variables related to passing behavior. The results showed similarities between passing time and passing distance of completed maneuvers (during the occupation of the opposing lane). However, drivers passed faster in the driving simulator, keeping higher clearances. Gap acceptance decisions were also found to be similar, as the distributions of both accepted and rejected gaps were similar, although critical gaps were found to be lower in the driving simulator. This might be explained by the absence of objective risks. Consequently, the applicability of driving simulation seems reasonable, although some improvements are still possible, in order to account for sight distance limitations, and to reproduce better the opposing traffic flow.