Normative pedestrian flow behavior theory and applications

Gaining insights into pedestrian flow operations and assessment tools for pedestrian walking speeds and comfort is important in for instance planning and geometric design of infrastructural facilities. Additionally, management of pedestrian flows requires knowledge of pedestrian flow behavior. However, compared to vehicular traffic, pedestrian flow operations are very complex. This is why vehicular flow simulation modeling approaches are generally not applicable to pedestrian flows. Motivated by the need for accurate pedestrian flow models, this report presents an integral theory and models for pedestrian activity scheduling, path determination in the twodimensional space, and walking behavior, under the assumption of utility optimization. In the theory put forward, pedestrians are assumed to make a simultaneous choice of the optimal activity pattern and path, on the one hand optimizing the utility of the activities, while on the other hand minimizing the cost of walking to reach the activity areas. In doing so, we formulate the pedestrian wayfinding problem as an optimal control problem in continuous time and space, where pedestrians aim to walk to the respective activity areas, while optimizing some trade-off between travel time, discomfort due to walking too close to obstacles and walking too quickly. At the same time, both the order in which the activities are performed (as far as their order is free), as well as whether an activity is performed at all, is optimized as well. Given that the pedestrian has determined both the optimal activity pattern as well as the optimal path, we postulate that pedestrian behavior at the operational level is also a result of a utility optimization process. At this level, pedestrians minimize the cost incurred while straying from the planned path, walking too close to other pedestrians, and cost due to large accelerations and decelerations. By applying calculus of variations, explicit mathematical relations are derived describing the acceleration, direction changing, and interaction behavior of a pedestrian. Throughout the report, the theory and models are illustrated by application examples.Transport and PlanningCivil Engineering and Geoscience

Smart mobility in smart cities: seamless integration of networks and sevices (PPT)

Power Point PresentatieTransport and Plannin

Multiclass continuum modelling of multilane traffic flow

Civil Engineering and Geoscience

Advanced Driver Assistance Systems: Traffic Impacts Assessed by Micro-simulation

This report presents results of research carried out in the ADVISORS project. The objective of this research is to develop a methodology to assess road traffic efficiency and environmental impacts of Advanced Driver Assistanc e Systems (ADAS) at both the microscopie and the network level. The results discussed in this report pertain to the microscopie analysis, in showing the impact ofADAS on bottleneck capacity and capacity distribution among the main-road and the on-ramps (if applicable) for both Autonomous Intelligent Cruise Control (AICC) as weil as Intelligent Speed Adaptation (ISA). Moreover, impact on traffic safety and driving comfort are studied indirectly, by considering cumulative exposure times to Time-To-Collision values that can be considered to be either unsafe and uncomfortable. This impact analysis is carried out using the microscopie simulation model SIMONE, developed by Delft University of Technology.Transport & PlanningCivil Engineering and Geoscience

Innovations in data collection; towards a better understanding of traffic flows

Transport and PlanningCivil Engineering and Geoscience

A neurofuzzy approach to modeling longitudinal driving behavior and driving task complexity

Technological innovations can be assumed to have made the driving task more complex. It is, however, not yet clear to what extent this complexity leads to changes in longitudinal driving behavior. Furthermore, it remains to be seen how these adaptation effects can best be modeled mathematically. In order to determine the effect of complexity on empirical longitudinal driving behavior we performed a driving simulator experiment with a repeated measures design. Through this experiment we established that complexity of the driving task leads to substantial changes in speed and spacing. In order to provide insight into how complexity is actually related to changes in longitudinal driving behavior we introduce a new theoretical framework based on the Task-Capability-Interface model. Finally in this paper we take some first steps towards modeling of adaptation effects in longitudinal driving behavior in relation to complexity of the driving task through the introduction of a new neurofuzzy car-following model and based on the proposed theoretical framework. In this paper we show that this model yields a relatively good prediction of longitudinal driving behavior in case of driving conditions with differing complexity. The paper finishes with a discussion section and recommendations for future research.Transport & PlanningCivil Engineering and Geoscience

Incorporating driver distraction in car-following models: Applying the TCI to the IDM

ITS can play a significant role in the improvement of traffic flow, traffic safety and greenhouse gas emissions. However, the implementation of Advanced Driver Assistance Systems may lead to adaptation effects in longitudinal driving behavior following driver distraction. It was however not yet clear how to model these adaptation effects in driving behavior mathematically and on which theoretical framework this should be grounded. To this end in this contribution we introduce a theoretical framework based on the Task-Capability-Interface model by Fuller and integrate this model into the Intelligent Driver Model. Through a case study using simulations we show that this integration provides a relatively adequate description of the effects of driver distraction. The contribution finishes with conclusions and recommendations for future research.Transport and PlanningTransport and Plannin

Capacity of doors during evacuation conditions

In this paper, we show how the capacity of evacuation doors is affected by the evacuation door width, population composition, the presence of an open door and evacuation conditions. For this, laboratory experiments have been performed. Varying door opening widths showed that only the experiment with the widest door opening (275 cm) resulted in a capacity lower than the threshold capacity from the design guidelines (2.25 P/m/s). The average observed capacities are for all widths lowest for the lowest stress level and highest for the highest stress level. The population with a greater part of children has the highest capacity, while the lowest capacity is, as expected, found for the experiment with 5% disabled participants. The presence of a door opened in the escape direction in an angle of 90 degrees for a door opening of 85 cm results in a 20% capacity reduction.Transport and PlanningCivil Engineering and Geoscience

A macroscopic model for multiple user-class traffic operations: Derivation, analysis and numerical results

In this report we derive a macroscopic Multiple User-Class traffic model from mesoscopic principles. These principles yield equilibrium relationships between traffic density and equilibrium velocities as a function of the current traffic conditions, the traffic composition, and the distribution of user-class dependent desired velocities, rather than these relations need to be defined exogenously. These relations encompass contributions of drivers accelerating towards their user-class specific desired velocity on the one hand, and contributions resulting from interaction between vehicles of the same or different classes on the other hand. Additionally, the velocity variance variable is introduced describing deviations from the average speed within the user-classes. We discuss several mathematical properties of the MUC equations. One of the results is an alternative model formulation, namely using the so-called conservative variables desity, momentum and energy, rather than the primitive variables density, velocity and velocity variance. Using this formulation, several new approaches are derived to numerically approximate solutions of the flow model. We discuss first results from macroscopic simulation using the developed multiple user-class traffic flow model. The simulation results are employed to investigate whether fundamental traffic flow model-equations hold. It is concluded that the MUC-model satisfies the anisotropy condition, the 'invariant personality condition', and the 'unaffected slow vehicles' condition. A test case illustrates the self-formation of congestion.Transport and PlanningCivil Engineering and Geoscience

Network transmission model: A dynamic traffic model at network level (poster)

New IT techniques allow communication and coordination between traffic measures. To best use this, one needs to coordinate over longer distances. Optimization of the measures is not possible using traditional microscopic or macroscopic simulation models. The Network Fundamental Diagram (NFD) describes the relation between flow and density on a network level. This paper introduces a traffic model which uses this relationship, representing traffic and traffic dynamics at a high spatial scale. The model shown to work on an example network. The model can be used to predict the effect of routing information or perimeter control.Transport and PlanningCivil Engineering and Geoscience