Adam J. Pel

EVAQ: A New Analytical Model for Voluntary and Mandatory Evacuation Strategies on Time-varying Networks

The analytical evacuation network model EVAQ enables forecasting traffic flow conditions on a road network for a wide range of emergency situations, such as hurricanes, bushfires and floods. The proposed model is innovative as it combines voluntary evacuation, with possible pre-trip and enroute decisions, and mandatory evacuation, with prescribed destinations, routes and departure times, within a single generic model framework. Furthermore, we introduce dynamic road infrastructure, in which characteristics such as speed limits, capacity and flow direction can be time-varying due to the hazards progress in space and time and prevailing traffic regulations and control measures. The evacuation model can function as a decision support system for regional authorities and emergency services supervising an evacuation or constructing an evacuation strategy for planning purposes.

Impact of Variations in Travel Demand and Network Supply Factors for Evacuation Studies

Traffic simulation models are frequently used to support decisions when an evacuation is planned. These models typically focus on traffic dynamics and the effect of traffic control measures to locate possible bottlenecks and predict evacuation times. However, a clear view of the crucial factors that determine evacuation time and emergent traffic states is lacking. In this paper, a structured and comprehensive sensitivity analysis identifies and quantifies the impact of variations in travel demand and network supply in the case of evacuation. The sensitivity analysis involves applying the macroscopic evacuation traffic simulation model EVAQ, in which aspects such as trip generation, departure rates, route flow rates, road capacities, and maximum speeds are systematically varied. That is accomplished using a case study that describes evacuation of the Rotterdam, Netherlands, metropolitan area. Departure rates and route flow rates are found to have a substantial nonlinear impact on network conditions and arrival pattern, particularly when the network load is relatively high, whereas trip generation and road capacities have a smaller quasilinear impact. Maximum speeds, independent of the effect on road capacities, have no significant impact on evacuation. The results, discussion, and conclusions presented can be used to identify the most important factors in (a) verifying, calibrating, and validating an evacuation model; (b) designing a network for evacuation studies; and (c) evaluating and testing the robustness of evacuation plans.

Hybrid Route Choice Modeling in Dynamic Traffic Assignment

Dynamic traffic assignment (DTA) models typically describe travelers selecting their routes before departure (pretrip) or during the trip (en route). However, in reality, people follow a certain route but have the opportunity to deviate from that route. An analytical hybrid route choice model is proposed that unifies pretrip and en route route choice in a tractable way. It enables modeling intermediate states where travelers make pretrip route choice decisions and may deviate from this route if they receive information about a more attractive route, for instance, because of unforeseen adverse traffic conditions. The hybrid route choice model is widely applicable to various planning and management applications in DTA and makes the DTA model more realistic in cases such as route guidance problems, where the combination of prescribed routes and en route route choice is evident. Furthermore, the proposed route choice model is generic because different dynamic traffic flow models can be used in the model, analytical or simulation-based. Also, two common problems in DTA related to gridlock and time-varying network conditions are solved in the hybrid route choice model.

Optimizing evacuation instructions while anticipating traveler compliance behavior

Instructing evacuees on their departure time, destination and route can lead to more efficient traffic operations. Empirical findings on evacuation behavior support the view that in practice a share of travelers decides not to comply, while current evacuation plan optimization techniques are limited to assessing mandatory evacuation under the assumption of full compliance. In this contribution we show I) how traveler compliance behavior affects evacuation efficiency, and II) how evacuation efficiency can be improved in case of partial compliance when this traveler compliance is anticipated on. The optimization method and case study application presented here underline the relevance and importance of capturing traveler compliance behavior, as this has a large impact upon the evacuation efficiency.

Model complexities and requirements for multimodal transport network design: Assessment of classical, state-of-the-practice, and state-of-the-research models

In the aim for a more sustainable transport system, governments try to stimulate multimodal trip making by facilitating smooth transfers between modes. The assessment of related multimodal policy measures requires transport models that are capable of handling the complex nature of multimodality. This complexity sets requirements for adequate modeling of multimodal travel behavior and can be categorized into three classes that are related to the range and combinatorial complexity of the available alternatives, the mathematical complexity of modeling the choice between them, and the complex effect of demand–supply interactions. Classical modeling approaches typically fail to meet these requirements and state-of-the-practice approaches only partly fulfill them. Therefore, the underlying hypothesis of this study was that the application of such models in network design implied an ill-advised decision-making process. Thus, these modeling approaches, as well as the promising state-of-the-research supernetwork approach, were conceptually compared with each other. Requirements for multimodality were constructed, and all three models were tested on the way in which these requirements can be met. The findings of this conceptual comparison were supported by realistic examples in the real-world transport network of the Amsterdam Metropolitan Area in the Netherlands. The theoretical shortcomings of the classical and state-of-the-practice approach were shown to indeed result in implausible predictions of multimodal travel behavior. The flexibility of the supernetwork approach, however, was very capable of describing the expected effect of supply changes on travel behavior in most situations. This study illustrates the urgency for applying sound multimodal modeling approaches in network design studies.

Sensitivity analysis on heterogeneity of driving behavior for evacuation studies and its impacts on traffic safety

The driving behavior of travelers has been found to be different in case of emergency conditions compared to normal traffic conditions. In this paper, we show how this different driving behavior, as well as the heterogeneity among drivers, has an impact on traffic safety. We do so by performing a sensitivity analysis on the model parameters representing the different (heterogeneous) driving behavior and investigating the impact of these variations on traffic safety. The analysis is conducted applying an evacuation simulation framework using S-Paramics. The results show that reductions in mean time headway and minimum gap substantially increase the number of potential safety conflicts. Also, it is found that variation in driving behavior plays a smaller, yet still important, role in traffic safety.

A Generic Method to Optimize Instructions for the Control of Evacuations

Abstract A method is described to develop a set of optimal instructions to evacuate by car the population of a region threatened by a hazard. By giving these instructions to the evacuees, traffic conditions and therefore the evacuation efficiency can be optimized. The instructions, containing a departure time, a destination, and a route, are created using an optimization method based on ant colony optimization. Iteratively is searched for an approximation of the optimal evacuation instructions. The usefulness of the optimization method compared to other optimization methods is the simultaneous optimization of the departure time, destination, and route instructions instead of the optimization of only one or two of these variables for a dynamic instead of static evacuation problem. In a case study, the functioning of the method is illustrated. The relative high fitness in the case study of the set of instructions following from the optimization method compared with the fitness of a set of instructions set up by straightforward rules (like evacuating to the nearest destination) shows also the usefulness of applying an optimization method to create a set of evacuation instructions.

Investigating the effects of improving public transport system linkage to spatial strategy on controlling urban sprawl: evidence from Surabaya City, Indonesia

The phenomenon of sprawl has been a huge issue since the beginning of the 20th century and is characterized by rapid and unbalanced settlement development, with transportation network, particularly in the suburban areas. Academic research has explained the linkage strategy between transportation network and urban planning. However, insufficient empirical verification has been carried out to reduce this phenomenon by using the integrated approach of space-transport development. This paper focuses on analyzing the improvement of public transport supply incorporated in the settlement development. The improvement of public transport (PT) is designed by planning Mass Rapid Transit (MRT), Light Rapid Transit (LRT), Bus Rapid Transit (BRT) and feeder systems. The impact of PT improvement has an effect on the settlement development. In addition, creating a balance between employment and population density is designed as an alternative to urban spatial strategy. These approaches are necessary in order to analyze and to evaluate the many alternatives proposed as a solution to overcome this phenomenon. The conclusions reveal that the requirement for linkage space-transport development strategy in order to control settlement in the suburbs has to involve reduction of 35% in travel time and to increase doubling of the use of PT.

Network effects of percentile-based route choice behavior for stochastic travel times under exogenous capacity variations

This study analyzes the properties of network reliability and efficiency with regard to the role of route choices under stochastic travel times, here due to exogenous link capacity variations. A percentile-based route choice model is derived, which has as underlying behavioral assumption that drivers make routing decisions based on route travel time distributions collected from past experiences and do so by accounting for the travel time budget that needs to be allocated in order to ensure a desired probability of avoiding the trip taking longer than the allocated travel time budget. This may represent, e.g., the routing decisions of commuters without real-time traffic information. The model application to the Sioux Falls road network then shows how variations in routing percentiles of homogeneous and segmented driver populations substantially impact the route travel time distributions as well as network performance metrics, such as buffer times and delay times, and how these effects vary with travel demand.

Travel time reliability during evacuation

Earlier studies have shown that driving behavior differs strongly in emergency conditions compared with behavior in normal traffic conditions. In this paper, these findings are followed up with an investigation of how these differences in driving behavior affect travel time reliability. In particular, the focus is on the effect of relatively strong heterogeneity in driving behavior. The microscopic simulation framework S-PARAMICS is adapted accordingly and applied to the emergency evacuation network of the Dutch city of Almere. This experimental setup allows a structured and in-depth analysis of the relationship between a number of driving behavior parameters and the emergent travel time reliability. The main findings from this study are thus insightful and directly applicable to evacuation planning and management studies. For instance, it is found that although a reduction in drivers’ mean time headway and minimum gap acceptance typically improves the overall evacuation time, travel times are simultaneously less reliable. Also, the reliability of travel times decreases over time and results in much less reliable travel times for those travelers who depart later. And finally, in general, heterogeneity in driving behavior strongly reduces travel time reliability.