About
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Introduction
I am an associate professor at the Department of Transport & Planning and co-director of the Traffic and Transportation Safety Lab (TTSLab). My research interests include the implications of road infrastructure design on road user behaviour and traffic safety, road user behaviour modelling, and safety evaluation methods. I combine my expertise in transportation engineering, with my curiosity in the fields of human factors and econometrics to study these connections.
Current institution
Additional affiliations
July 2014 - November 2020
August 2009 - December 2011
Education
April 2013 - April 2013
TMS Consultancy
Field of study
- Road safety
August 2009 - December 2011
October 2004 - March 2009
Publications
Publications (156)
As automated vehicles (AVs) are increasingly being deployed on our road network, it becomes important to understand how human drivers interact with them in mixed traffic. This research investigates how mixed traffic factors affect human-driven vehicles (HDV) gap acceptance behavior at a priority T-intersection. Using a driving simulator, four scena...
Detecting abnormal driving behavior is critical for road traffic safety and the evaluation of drivers’ behavior. With the advancement of machine learning (ML) algorithms and the accumulation of naturalistic driving data, many ML models have been adopted for abnormal driving behavior detection (also referred to in this paper as “anomalies”). Most ex...
Lane detection is crucial for automated vehicles and Advanced Driver Assistance Systems. However, current methods lack versatility in delivering accurate, robust, and real-time compatible lane detection, especially under challenging driving scenes. Vision-based methods often neglect critical regions of the image and their spatial-temporal (ST) sali...
As automated vehicles (AVs) become increasingly popular, the question arises as to how cyclists will interact with such vehicles. This study investigated (1) whether cyclists spontaneously notice if a vehicle is driverless, (2) how well they perform a driver-detection task when explicitly instructed, and (3) how they carry out these tasks. Using a...
Automated Vehicles (AVs) hold promise for revolutionizing transportation by improving road safety, traffic efficiency, and overall mobility. Despite the steady advancement in high-level AVs in recent years, the transition to full automation entails a period of mixed traffic, where AVs of varying automation levels coexist with human-driven vehicles...
As automated vehicles (AVs) become increasingly popular, the question arises as to how cyclists will interact with such vehicles. This study investigated (1) whether cyclists spontaneously notice if a vehicle is driverless, (2) how well they perform a driver-detection task when explicitly instructed, and (3) how they carry out these tasks. Using a...
Detecting abnormal driving behavior is critical for road traffic safety and the evaluation of drivers' behavior. With the advancement of machine learning (ML) algorithms and the accumulation of naturalistic driving data, many ML models have been adopted for abnormal driving behavior detection (also referred to in this paper as anomalies). Most exis...
Sharp curves in freeways are known to be unsafe design elements since drivers do not expect them. It is difficult for drivers to estimate the radius of a curve. Therefore, drivers are believed to use other cues to decelerate when approaching a curve. Based on previous successful experiences of driven speeds in curves, drivers are thought to have bu...
Automated vehicles (AVs) may require the implementation of an external human-machine interface (eHMI) to communicate their intentions to human-driven vehicles. The optimal placement of the eHMI, either on the AV itself or as part of the road infrastructure, remains undetermined. The current driving simulator study investigated the effect of eHMI po...
Automated vehicles (AVs) may require the implementation of an external human-machine interface (eHMI) to communicate their intentions to human-driven vehicles. The optimal placement of the eHMI, either on the AV itself or as part of the road infrastructure, remains undetermined. The current driving simulator study investigated the effect of eHMI po...
This study utilized Virtual Reality (VR) experiments to investigate pedestrian-autonomous vehicle interaction in shared spaces. In the VR experiment, pedestrians attempt to cross the road under different conditions, including the presence of another pedestrian, different external Human-Machine-Interfaces, AV driving styles, and road conditions. We...
This public Deliverable 3.4 describes the on-road evaluations of the vehicle-integrated Mediator system. Three real-life on-road studies were conducted to test the overall performance of the Mediator system and its effects on safety-relevant behaviours, driver reactions and driver opinions.
The gradual deployment of automated vehicles (AVs) results in mixed traffic where AVs will interact with humandriven vehicles (HDVs). Thus, social-aware motion planning and control while considering interactions with HDVs on the road is critical for AVs’ deployment and safe driving under various maneuvers. Previous research mostly focuses on the tr...
The burgeoning navigation services using digital maps provide great convenience to drivers. Nevertheless, the presence of anomalies in lane rendering map images occasionally introduces potential hazards, as such anomalies can be misleading to human drivers and consequently contribute to unsafe driving conditions. In response to this concern and to...
Traffic scenarios in roundabouts pose substantial complexity for automated driving. Manually mapping all possible scenarios into a state space is labor-intensive and challenging. Deep reinforcement learning (DRL) with its ability to learn from interacting with the environment emerges as a promising solution for training such automated driving model...
A shared space area is a low-speed urban area in which pedestrians, cyclists, and vehicles share the road, often relying on informal interaction rules and greatly expanding freedom of movement for pedestrians and cyclists. While shared space has the potential to improve pedestrian priority in urban areas, it presents unique challenges for pedestria...
This study utilized Virtual Reality (VR) experiments to investigate pedestrian-autonomous vehicle interaction in shared spaces. In the VR experiment, pedestrians attempt to cross the road under different conditions, including the presence of another pedestrian, different external Human-Machin-Interfaces, AV driving styles, and road conditions. We e...
A shared space area is a low-speed urban area in which pedestrians, cyclists, and vehicles share the road, often relying on informal interaction rules and greatly expanding freedom of movement for pedestrians and cyclists. While shared space has the potential to improve pedestrian priority in urban areas, it presents unique challenges for pedestria...
Driving automation holds significant potential for enhancing traffic safety. However, effectively handling interactions with human drivers in mixed traffic remains a challenging task. Several models exist that attempt to capture human behavior in traffic interactions, often focusing on gap acceptance. However, it is not clear how models of an indiv...
The gradual deployment of Connected and Automated Vehicles (CAV) in traffic will result in a transition period in which vehicles with various levels of automation and connectivity will have to co-exist with non-connected and non-automated road users for quite some time. Consequently, new types of interactions will emerge (and old types of interacti...
Autonomous Vehicles (AVs) are introduced to the traffic system with the promise to improve current traffic status. However, the empirical data also indicate the contrary effects by the estimated higher crash rate and the change of crash patterns.
Therefore, it is necessary to investigate the driving behavior of AVs and human-driven vehicles (HDVs)...
Driver anticipation plays a crucial role in crashes along horizontal curves. Anticipation is related to road predictability and can be influenced by roadway geometric design. Therefore, it is essential to understand which geometric design elements can influence anticipation and cause the road to be (un)predictable. This exercise, however, is not st...
Overtaking on two-lane roads can lead to increased collision risks due to drivers' errors in evaluating whether or not to accept the gap to the vehicle in the opposite lane. Understanding these gap acceptance decisions can help mitigate the risks associated with overtaking. Previous research on overtaking has focused on the factors influencing gap...
Although much research is done on speed and gaze behaviour inside curves, there is little understanding of which cues drivers use to anticipate and slow down while approaching freeway curves. Therefore, an on road experiment was conducted in which 31 participants drove through six curves in their own car. During the experiment, look-ahead fixations...
Although much research is done on speed and gaze behaviour inside curves, there is little understanding of which cues drivers use to anticipate and slow down while approaching curves. Therefore, an on road experiment was conducted in which 31 participants drove through six freeway curves in their own car. During the experiment, look-ahead fixations...
Lane detection is crucial for vehicle localization which makes it the foundation for automated driving and many intelligent and advanced driving assistant systems. Available vision-based lane detection methods do not make full use of the valuable features and aggregate contextual information, especially the interrelationships between lane lines and...
Lane detection serves as a fundamental task for automated vehicles and Advanced Driver Assistance Systems. However, current lane detection methods can not deliver the versatility of accurate, robust, and real-time compatible lane detection in real-world scenarios especially under challenging driving scenes. Available vision-based methods in the lit...
Highly automated vehicles (HAVs) have been introduced to the transportation system for the purpose of providing safer mobility. Considering the expected long co-existence period of HAVs and human-driven vehicles (HDVs), the safety operation of HAVs interacting with HDVs needs to be verified. To achieve this, HAVs’ Operational Design Domain (ODD) ne...
Future traffic will be composed of both human-driven vehicles (HDVs) and automated vehicles (AVs). To accurately predict the performance of mixed traffic, an important aspect is describing HDV behavior when interacting with AVs. A few exploratory studies show that HDVs change their behavior when interacting with AVs, being influenced by factors suc...
Automated vehicles (AVs) aim to dramatically improve traffic safety by reducing or eliminating human error, which remains the leading cause of road crashes. However, commonly accepted standards for the ‘safe driving behaviour of machines’ are pending and urgently needed. Unless a common understanding of safety as a design value is achieved, differe...
The gradual deployment of automated vehicles on the existing road network will lead to a long transition period in which vehicles at different driving automation levels and capabilities will share the road with human driven vehicles, resulting into what is known as mixed traffic. Whether our road infrastructure is ready to safely and efficiently ac...
The operation of automated vehicles (AVs) on shared roads requires attention concerning their interactions with vulnerable road users (VRUs), such as cyclists. This study investigates the safety of cyclists when they interact with an AV and compares it with their interaction with a conventional vehicle. Overall, 29 cyclists participated in a contro...
Road designers need to have insights where deceleration and acceleration are expected related to the position of the curve, and in in which amount so that drivers are able to safely decelerate and accelerate respectively into and out of a freeway curve. For this, empirical speed data is needed. Therefore, Floating Car Data in 153 curves in The Neth...
This study aims at assessing road infrastructure readiness and safety for automated vehicles (particularly, SAE levels 3-4). To this end, we organized a systematically designed workshop and asked experts to assess images of specific road segments to which several attributes such as road type and road users were associated. The experts were asked to...
Advancements in technology are bringing automated vehicles (AVs) closer to wider deployment. However, in the early phases of their deployment, AVs will coexist and frequently interact with human-driven vehicles (HDVs). These interactions might lead to changes in the driving behavior of HDVs. A field test was conducted in the Netherlands with 18 par...
Automated driving systems, which can take over certain dynamic driving tasks from the driver, are becoming increasingly available in commercial vehicles. One of these automated driving systems widely introduced in commercial vehicles is adaptive cruise control (ACC). This system is designed to maintain certain desired driving speeds and time headwa...
Accurate and reliable lane detection is vital for the safe performance of lane‐keeping assistance and lane departure warning systems. However, under certain challenging circumstances, it is difficult to get satisfactory performance in accurately detecting the lanes from one single image as mostly done in current literature. Since lane markings are...
Cyclists are expected to interact with automated vehicles (AVs) in future traffic, yet we know little about the nature of this interaction and the safety implications of AVs on cyclists. On-bike human-machine interfaces (HMIs) and connecting cyclists to AVs and the road infrastructure may have the potential to enhance the safety of cyclists. This s...
Lane detection serves as a fundamental task for automated vehicles and Advanced Driver Assistance Systems. However, current lane detection methods can not deliver the versatility of accurate, robust, and realtime compatible lane detection in real-world scenarios especially under challenging driving scenes. Available vision-based methods in the lite...
Lane detection serves as a fundamental task for automated vehicles and Advanced Driver Assistance Systems. However, current lane detection methods can not deliver the versatility of accurate, robust, and real-time compatible lane detection in real-world scenarios especially under challenging driving scenes. Available vision-based methods in the lit...
The impact of automated vehicles (AV) on pedestrians’ crossing behavior has been the topic of some recent studies, but findings are still scarce and inconclusive. The aim of this study is to determine whether the drivers’ presence and apparent attentiveness in a vehicle influences pedestrians’ crossing behavior, perceived behavioral control, and pe...
Reliable and accurate lane detection is of vital importance for the safe performance of Lane Keeping Assistance and Lane Departure Warning systems. However, under certain challenging peculiar circumstances, it is difficult to get satisfactory performance in accurately detecting the lanes from one single image which is often the case in current lite...
Connected and automated vehicles (CAVs) are expected to enhance traffic efficiency by driving at shorter time headways, and traffic safety by shorter reaction times. However, one of the main concerns regarding their deployment is the mixed traffic situation, in which CAVs and manually driven vehicles (MVs) share the same road.
This study investigat...
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 t...
The actual speed behaviour when drivers approach a curve is very relevant to assess the road design and safety but is mostly overlooked in the scientific literature. Most research into curve driving behaviour is focussed at the behaviour inside the curve, although the speed selection is done before curve entry. The main objective of this research i...
“Everything somewhere” or “something everywhere” is the classic dilemma concerning the development and implementation of the future generation of vehicles, i.e., automated vehicles (AVs). Both strategies include diverse policy options that could significantly impact road networks’ planning, design, operation, and utilization. Until now, no signific...
Automated vehicles (AVs) promise to improve road safety, reduce traffic congestion and emissions, and enhance mobility. However, evidence regarding their safety benefits has not been systematically investigated and documented. In this study, we utilise a scoping review approach to investigate and synthesise the existing literature on higher levels...
The impact of automated vehicles (AV) on pedestrians’ crossing behavior has been the topic of some recent studies, but findings are still scarce and inconclusive. The aim of this study is to determine whether the drivers’ presence and apparent attentiveness in a vehicle influences pedestrians’ crossing behavior, perceived behavioral control, and pe...
Cyclists are expected to interact with automated vehicles (AVs) in future traffic, yet we know little about the nature of this interaction and the safety implications of AVs on cyclists. On-bike human-machine interfaces (HMIs) and connecting cyclists to AVs and the road infrastructure may have the potential to enhance the safety of cyclists. This s...
Automated vehicles (AVs) are expected to improve traffic flow efficiency and safety. The deployment of AVs on motorways is expected to be the first step in their implementation. One of the main concerns is how human drivers will interact with AVs. Dedicating specific lanes to AVs have been suggested as a possible solution. However, there is still a...
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 ai...
Operating speeds in Dutch freeway curves differ often by 20 km/h compared to their design speeds. Operating speed is thought to be influenced by how drivers perceive curves when approaching a curve. This explorative research explores which curve cues and other variables influence drivers’ speed choice in curves. For this purpose, a survey was desig...
The report provides actions recommended for road authorities and operators to adapt their core business to utilise and facilitate connected and highly automated driving. The road map in this deliverable consists of tables describing actions in different areas of the national road authority core business areas up to 2040. The 92 actions of the roadm...
The tram is a sustainable mode of transport. However, tram tracks are often shared with vulnerable road users (VRUs) such as pedestrians and cyclists. In this mixed environment, accidents between trams and VRUs are very rare but severe at the same time. Previous studies have acknowledged that tram driving is a complex and very demanding task. Yet,...
In order to overcome the shortcomings of crash data a number of surrogate measures of safety have been developed and proposed by various researchers. One of the most widely used temporal indicators is time-to-collision (TTC) which requires the road users to be on a collision course. Road users that are strictly speaking not on a collision course ac...
Dedicated Lanes (DLs) have been proposed as a potential scenario for the deployment of Automated and/or Connected Vehicles (C/AVs) on the road network. However, evidence-based knowledge regarding the impacts of different design configurations, utilization policies, and the design of their access/egress on traffic safety and efficiency is limited. I...
The estimation of the free flow speed (FFS) distribution is important for capacity analysis, determination of the level-of-service, and setting speed limits. Subjective time headway thresholds have been commonly used to identify vehicles travelling under free flow speed conditions i.e., vehicles whose speeds are not influenced by the vehicle in fro...
Traffic congestion is a major societal challenge. By advising drivers on the optimal lane to drive, traffic flow can be improved, and congestion reduced. In this paper we describe the development of a lane-specific advice Human Machine Interface (HMI). Persuading drivers to follow an advice that is beneficial to the traffic situation, but may not b...
Lower levels of automation are designed to work in specific conditions referred to as the Operational Design Domain (ODD). Beyond these conditions, the human driver is expected to take control. A mismatch between a driver's understanding and expectations of the automated vehicle capabilities and its actual capabilities as prescribed in the Original...
In current motorway design practice, microscopic simulation is used to assess the traffic safety and capacity implications of design variants. Many different simulation packages are available, and many researchers have invested effort in improving and calibrating models that describe driving behavior. This paper examines traffic simulation models f...
Adaptive Cruise Control (ACC) can reduce traffic congestion and accidents. In dense traffic flow conditions and when changing lanes, drivers prefer to deactivate the ACC. These control transitions between automation and manual driving could impact driver behaviour characteristics. However, few studies have analysed the magnitude and duration of the...
There is a pressing need for road authorities to take a proactive role in the deployment of automated vehicles on the existing road network. This requires a comprehensive understanding of the driving environment characteristics that affect the performance of automated vehicles. In this context, a field test with Lane Departure Warning (LDW) and Lan...
This paper describes the functioning and development of HeartPy: a heart rate analysis toolkit designed for photoplethysmogram (PPG) data. Most openly available algorithms focus on electrocardiogram (ECG) data, which has very different signal properties and morphology, creating a problem with analysis. ECG-based algorithms generally don’t function...
In order to develop design guidelines and assess the implications on traffic flow operations and safety, microscopic behavioral models are used. The increasing interest in cycling in cities necessitates the development of a model that captures the movement of cyclists. Given the fact that cyclists exert effort for their motion, the theory of effort...
Partially and fully automated vehicles (AVs) are being developed and tested in different countries. These vehicles are being designed to reduce and ultimately eliminate the role of human drivers in the future. However, other road users, such as pedestrians and cyclists will still be present and would need to interact with these automated vehicles....
This paper describes the functioning and development of HeartPy: a heart rate analysis toolkit designed for photoplethysmogram (PPG) data. Most openly available algorithms focus on electrocardiogram (ECG) data, which has very different signal properties and morphology, creating a problem with analysis. ECG-based algorithms generally don’t function...
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 p...
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 intera...
Measuring risk is critical for collision avoidance. The paper aims to develop an online risk level classification algorithm for forward collision avoidance systems. Assuming risk levels are reflected by braking profiles, deceleration curves from critical evasive braking events from the Virginia "100-car" database were first extracted. The curves ar...
Professionals from various disciplines have been investing huge efforts in the last few decades in the development and deployment of connected and automated vehicles (CAVs). It is believed that CAVs can mitigate the main drawbacks of transport issues such as safety, emissions, and congestion. The main objective of this paper is to examine how inter...
Current road infrastructure is designed for human drivers, and may be unable to deal with the integration of highly automated vehicles. The aim of this paper is to explore potential infrastructure requirements for automated driving SAE Level 4. To cope with the wide range of uncertainties involved, a scenario-based approach was used to define tw...
The involvement of cyclists in road crashes has not been decreasing with the same magnitude as the involvement of other road users. In particular, the interactions between cyclists and motorized traffic can lead to high-severity crashes. To improve the safety of these interactions, a thorough understanding of road user behaviour is first needed. In...
Persuasive in-vehicle systems aim to intuitively influence the attitudes and/or behaviour of a driver (i.e. without forcing them). However, the challenge in using these systems in a driving setting, is to maximise the persuasive effect without infringing upon the driver’s safety.
This paper proposes a conceptual model for driver persuasion at the...
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 p...
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 th...
We developed a heart rate analysis toolkit for use in collecting and analysing heart rate signals collected in noisy settings. In the paper we describe the development, functioning and (open source) availability of the software.
The paper has been submitted to the Journal of Open Research Software. Pre-print is available.
Automated vehicles (AVs) will be introduced on public roads in the future, meaning that traditional vehicles and AVs will be sharing the urban space. There is currently little knowledge about the interaction between pedestrians and AVs from the point of view of the pedestrian in a real-life environment. Pedestrians may not know with which type of v...
On interchanges there are higher probabilities of risky situations compared to uninterrupted motorway sections due to increased speed variability and higher frequency of lane-changes. In this study, we focus on understanding and modelling drivers’ longitudinal speed behavior when negotiating horizontal ramp curves in interchanges in the Netherlands...
To create a safer environment for bicyclists and pedestrians, the usefulness of different types of kerbs as a separation between these two modes has been questioned by both researchers and practitioners. Right angled kerbs pose risks to cyclists due to their height but are assumed to separate them well from pedestrians. Sloped and levelled kerb typ...
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 envir...
In the vicinity of ramps, drivers make route choices, change lanes and in most cases also adjust their speeds. This can trigger anticipatory behaviour by the surrounding vehicles, which are also reflected in lane changes and/or changes in speed. This phenomenon is called turbulence and is widely recognised by the scientific literature and various d...
Heart rate data are collected often in human factors studies. 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) wavefor...
The integration of automated and connected vehicles on our existing road network is expected to impact traffic efficiency and safety. This upcoming new reality causes road operators, researchers, and policy makers to raise critical questions on the requirements and implications of automated and connected vehicles on the road infrastructure. We pres...