Driver interaction with vulnerable road users: Modelling driver behaviour in crossing scenarios
Doktorsavhandling, 2019

Every year, more than 5000 pedestrians and 2000 cyclists die on European roads. These vulnerable road users (VRUs) are especially at risk when interacting with cars. Intelligent safety systems (ISSs), designed to mitigate or avoid crashes between cars and VRUs, first entered the market a few years ago, and still need to be improved to be effective. Understanding how drivers interact with VRUs is crucial to improving the development and the evaluation of ISSs. Today, however, there is a lack of knowledge about driver behaviour in interactions with VRUs. To address this deficiency and contribute to realising the full potential of ISSs, this thesis has multiple objectives: 1) to investigate and describe the driver response process when a VRU crosses the driver path, 2) to devise models that can predict the driver response process, 3) to inform Euro NCAP with new knowledge about driver interactions with crossing VRUs that may guide the development of their test scenarios, and 4) to develop a framework for ISS evaluation through counterfactual simulation and analyse the impact of the chosen driver model on the simulation outcome. The thesis results show that the moment when a VRU becomes visible to the driver has the largest influence on the driver’s braking response process in driver-VRU interactions. Data gathered in driving simulators and on a test track were used to devise different predictive models: one model for the pedestrian crossing scenario, and three for the cyclist crossing scenario. The model for the pedestrian crossing scenario can estimate the moments at which key components of the driver response process (e.g. gas pedal fully released and brake onset) happen. For the cyclist crossing scenario, the first model predicts the brake onset time and the second predicts the experienced discomfort score given the cyclist appearance time. The third predicts the continuous deflection signal of the brake pedal based on the interaction of two visually-derived cues (looming and projected post-encroachment time). These models could be used to improve the design and evaluation of ISSs. From the models, appropriate warning or intervention times that are not a nuisance to the drivers could be adopted by the ISSs, therefore maximizing driver acceptance. Additionally, the models could be used in counterfactual simulations to evaluate ISS safety benefits. In fact, it was shown that driver models are a critical part of these simulations, further demonstrating the need for the development of more realistic driver models. The knowledge provided by this thesis may also guide Euro NCAP towards an improved ISS test protocol by providing information about scenarios that have not yet been evaluated.

Driver behaviour

Counterfactual analysis


Driver model

Active Safety



Campus Lindholmen, Saga building, Hörselgången 4, room Alfa
Opponent: Dr. Otto Lappi, Docent, University of Helsinki


Christian-Nils Åkerberg Boda

Chalmers, Mekanik och maritima vetenskaper, Fordonssäkerhet

Marco Dozza, Christian-Nils Boda, Leila Jaber, Prateek Thalya, and Nils Lubbe (2019). “How do drivers negotiate intersections with pedestrians? Fractional factorial design in an open-source driving simulator”

Modelling how drivers respond to a bicyclist crossing their path at an intersection: How do test track and driving simulator compare?

Accident Analysis and Prevention,; Vol. 111(2018)p. 238-250

Artikel i vetenskaplig tidskrift

Christian-Nils Boda, Marco Dozza, Pablo Puente Guillen, Prateek Thalya, Leila Jaber, and Nils Lubbe (2019). “Modelling discomfort: How do drivers feel when cyclists cross their path?”

Christian-Nils Boda, Esko Lehtonen, and Marco Dozza (2019). “A computational driver model to predict driver control at unsignalised intersections.”

Every year, many pedestrians and cyclists die in road crashes, most commonly when they cross a car's travel path. To avoid these crashes, car companies have already developed safety systems that control the car or warn the driver (such as autonomous emergency braking and frontal collision warning systems, respectively). However, these systems need to be improved; they are still not perfect. We can improve these systems by predicting drivers' control using mathematical models. Unfortunately, only a limited number of models are currently available, and few deal with crossing situations. This thesis supports the design and evaluation of safety systems that can predict driver control, through multiple objectives: 1) study driver behaviour when a cyclist or a pedestrian crosses the travel path, 2) create models that can predict driver control, 3) update evaluation programmes (for instance, Euro NCAP) with new knowledge to guide the development of their test protocols, and 4) develop a way to evaluate the potential impact of safety systems using virtual simulations. Results of our experiments show that the moment in which a cyclist or a pedestrian becomes visible to the driver (appearance time) had the largest effect on the driver’s braking. The data, recorded during driver behaviour experiments in driving simulators and on a test track, were used to devise four different predictive mathematical models: a gas-pedal release and braking initiation model in crossing-pedestrian scenarios, and a braking initiation model, a discomfort model, and a brake-pedal position model for crossing-cyclist scenarios. The brake-pedal position model is the most advanced model developed in this thesis. These models can provide information about the driver that can be used to determine the ideal activation time for a safety system in order to maximise its acceptance by the driver. The models can also be used in computer simulations to evaluate the systems' safety benefits. In fact, the thesis work demonstrated that models are an important part of the computer simulations used to evaluate systems' safety benefits. Not only has this thesis acquired more knowledge about driver behaviour, but it also delivers this knowledge in the form of models that can be used to improve the safety systems and test protocols of assessment programmes.

DIV - Driver Interaction with Vulnerable Road Users

Toyota Motor Europe, 2015-09-01 -- 2020-08-31.

Autoliv AB, 2015-09-01 -- 2020-08-31.







Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 4656


Chalmers tekniska högskola

Campus Lindholmen, Saga building, Hörselgången 4, room Alfa

Opponent: Dr. Otto Lappi, Docent, University of Helsinki

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