Serge P. Hoogendoorn

Modelling multimodal transit networks integration of bus networks with walking and cycling

Demand for (public) transportation is subject to dynamics affected by technological, spatial, societal and demographic aspects. The political environment, together with financial and spatial constraints limit the possibilities to address transit issues arising from growing demand through the construction of new infrastructure. Upgrading of existing services and improving integration over the entire trip chain are two options that can address these transport issues. However, transport planners and transport service operators often fail to include the entire trip when improving services, as improvement is normally achieved through the adaptations of characteristics (e.g. speeds, stop distances) of the services. Our developed framework consists of two parts: one to assess the characteristics of the different bus services and their access and egress modes, and one to assess the effects of integration of these services, which includes the modelling and analysis in a regional transit model. The framework has successfully been applied to a case study showing that bus systems with higher frequencies and speeds can attract twice the amount of cyclists on the access and egress sides. It also shows that passengers accept longer access and egress distances with more positive characteristics of the bus service (higher speeds, higher frequencies).

Two-Dimensional Approximate Godunov Scheme and What It Means For Continuum Pedestrian Flow Models

An efficient simulation method for two-dimensional continuum pedestrian flow models is introduced. It is a two-dimensional adaptation of the Godunov scheme for one-dimensional road traffic flow models. It is further extended to include multiple classes, representing groups of pedestrians with different behavior, origin, and destination. The method can be applied to continuum pedestrian flow models in a wide range of applications from the design of train stations and other travel hubs to the study of crowd behavior and safety at sports, religious, and cultural events. The combination of the efficient simulation method with continuum models enables the user to get simulation results much quicker than before. This opens doors to real-time crowd control and to more advanced optimization of planning and control. Test results show the importance of choosing appropriate numerical settings, including grid cell and time step size for realistic simulation results.

A geometric Brownian motion car-following model: towards a better understanding of capacity drop

ABSTRACT Traffic flow downstream of the congestion is generally lower than the pre-queue capacity. This phenomenon is called the capacity drop. Recent empirical observations show a positive relationship between the speed in congestion and the queue discharge rate. Literature indicates that variations in driver behaviors can account for the capacity drop. However, to the best of authors knowledge, there is no solid understanding of what and how this variation in driver behaviors lead to the capacity drop, especially without lane changing. Hence, this paper fills this gap. We incorporate the empirically observed desired acceleration stochasticity into a car-following model. The extended parsimonious car-following model shows different capacity drop magnitudes in different traffic situations, consistent with empirical observations. All results indicate that the stochasticity of desired accelerations is a significant reason for the capacity drop. The new insights can be used to develop and test new measures in traffic control.

Assessing and Improving Operational Strategies for the Benefit of Passengers in Rail-Bound Urban Transport Systems

Unplanned disruptions in transit can have consequent impacts on passengers. The more inconvenienced passengers are, the more likely operators will be negatively impacted. Yet so far, operators and researchers have addressed the rescheduling problem during disruptions mainly with a supply-side focus – timetable, crews, and vehicles – and not with a passenger perspective. Urban rail transit particularly lacks insights in terms of passenger-focused rescheduling. Being able to assess the inconvenience experienced by passengers during disruptions compared with what they normally experience, and being able to compare how different rescheduling strategies affect them are therefore two major challenges. The framework developed in this study precisely aims at tackling these challenges. A case study of the Rotterdam Metro is used to test the framework developed in this paper. Alternative strategies are developed focusing on the incident phase (from the beginning of the incident until its cause is resolved). The application of the framework reveals that a regularity-focused rescheduling strategy would be beneficial for high-frequency service users. Realistically, yearly savings could amount to around €900,000 in terms of societal passenger costs for the operator in the Rotterdam area alone. However, the omnipresence of the punctuality paradigm, through which most operators plan and analyze operations, makes the implementation of passenger-focused strategies a challenging task for traffic controllers. The results of the study are valuable for transit operators worldwide, and the framework could provide decision makers with insights on the performance of different strategies, bringing to light trade-offs between the supply and passenger sides during disruptions.

Estimating Choice Models to Quantify the Effect of Herding on the Decision to Evacuate: Application of a Serious Gaming Experimental Setup

Insight into factors influencing the choices people make in case of an evacuation from a natural disaster can help governments and emergency management personnel to manage people in case of such a situation. One of the aspects that influences the choices that people make in such a situation is herding. Since herding has not been quantified, this paper focuses on quantifying the effect of herding on the decision to evacuate by using an experimental setup that is based on the serious game Everscape. Around 400 people participated in 13 experiments with this setup. Choice models were estimated with the data from these experiments by including observable characteristics of herding as an attribute into the utility function. It is concluded that an important step is made in quantifying herding. It is shown that the more people someone sees leaving, the more inclined this person is to leave. Seeing people leave has more impact than seeing people stay. When people have no information from official sources, they tend to use other people as a source of information. In case of a disaster, this might result in following people who make the situation even more dangerous (for themselves and possibly for others as well). The information provided by official sources is therefore essential in managing people in the best possible way in case of a natural disaster.

The Potential of Demand-Responsive Transport as a Complement to Public Transport: An Assessment Framework and an Empirical Evaluation:

Demand-responsive transport (DRT) services (collective on-demand services, such as shared ridesourcing and microtransit) offer a collective flexible travel alternative that can potentially complement fixed transit (FT). The combination of an on-demand and line-based service holds the promise of improved mobility and increased service coverage. However, to date, it remains unknown whether DRT services deliver these much anticipated improvements. This study presents an assessment framework to evaluate the performance of DRT and related changes in accessibility, and performs an empirical analysis for a recently introduced DRT service in the Netherlands. The framework includes a performance benchmark between DRT and FT based on the computation of generalized journey times of the DRT rides and the FT alternatives, and can help identify whether DRT is used as a complement or a substitute for FT. The framework covers the spatial and temporal dimensions, and the explicit consideration of rejected trips is an integral part of the evaluation. Results suggest large accessibility improvements for DRT users, especially for some underserved origin–destination pairs.

Lane Change Behavior on Freeways: An Online Survey Using Video Clips

Freeways forman important part of the road network. Yet, driving behavior on freeways, in particular lane changes and the relation with the choice of speed, is not well understood. To overcome this, an online survey has been carried out. Drivers were shown video clips, and after each clip they had to indicate what they would do after the moment the video stopped. A total of 1258 Dutch respondents completed the survey. The results show thatmost people have a strategy to choose a speed first and stick to that, which is the first strategy. A second, less often chosen, strategy is to choose a desired lane and adapt the speed based on the chosen lane. A third strategy, slightly less frequently chosen, is that drivers have a desired speed, but contrary to the first strategy, they increase this speed when they are in a different lane overtaking another driver. A small fraction have neither a desired speed nor a desired lane. Of the respondents 80% use the right lane if possible, and 80% avoid overtaking at the right. Also 80% give way to merging traffic.The survey was validated by 25 survey respondents also driving an instrumented vehicle. The strategies in this drive were similar to those in the survey. The findings of this work can be implemented in traffic simulation models, e.g., to determine road capacity and constraints in geometric design.

Monitoring the Number of Pedestrians in an Area: The Applicability of Counting Systems for Density State Estimation

Crowd monitoring systems are more and more used to support crowd management organizations. Currently, counting systems are often used to provide quantitative insights into the pedestrian traffic state, since they are fairly easy to install and the accuracy is reasonably good under normal conditions. However, there are no sensor systems that are 100% accurate. Detection errors might have severe consequences for the density state estimation at large squares. The consequences of these errors for pedestrian state estimation have not yet been determined. This paper studies the impact of one specific type of detection error on the functionality of counting camera systems for density state estimation, namely, a randomly occurring “false negative” detection error. The impact is determined via two tracks, a theoretical track and a simulation track. The latter track studies the distribution of the cumulative number of pedestrians after 24 hours for three stylized cases by means of Monte Carlo simulations. This paper finds that counting camera systems, which have a detection error that is not correlated with the flow rate, provide a reasonably good estimation of the density within an area. At the same time, if the detection error is correlated with the flow rate, counting camera systems should only be used in the situation where symmetric demand patterns are expected.