Sascha Hoogendoorn-Lanser

Investigating the Shape of the Macroscopic Fundamental Diagram Using Simulation Data

Macroscopic fundamental diagrams (MFDs) exist in large urban networks in which traffic conditions are homogenous. They can be used for estimation of the level of service on road networks, perimeter control, and macroscopic traffic modeling. However, before the MFD concept can be applied, the factors that influence the MFD shape should be identified and their effects investigated. A microscopic simulation model is used to change conditions, that is, to derive MFDs under different conditions and for different types of networks. Results indicate that a relationship indeed exists between production and accumulation for the whole network as well as for parts of the network focused on freeway or urban links. MFD shape is a property not only of the network itself but also of the applied traffic control measures. At the same time, congestion onset and resolution lead to heterogeneous traffic conditions with congestion at specific locations in the network, resulting in loops in congested parts of the MFD. Investigation of the effect of traffic demand on MFD also indicates that rapidly changing traffic demands drastically affect MFD shape.

MULTIMODAL CHOICE SET COMPOSITION: ANALYSIS OF REPORTED AND GENERATED CHOICE SETS

Multimodal trips are common in todays travel and are expected to become more important. An individual embarking on a multimodal trip faces a number of choice dimensions, such as access and egress mode or modes, origin and destination railway stations, train service types, and transfer stations. For each of these choice dimensions, multiple alternatives are available. To gain insight into the structure and complexity of multimodal trips, a dedicated survey was conducted. Its results include detailed data on chosen trips and reported trip alternatives of 511 multi-modal home-bound trips in which the train is the main transport mode. Furthermore, objective choice sets were generated for these respondents and compared with the chosen trips and the reported trip alternatives. It can be concluded that many alternatives are available to travelers, whereas only a limited subset of those alternatives is actually perceived. Even fewer alternatives are actually considered in the choice process. The obtained knowledge of the chosen trips and subjective choice sets can be used to improve choice set generation algorithms and to define strategies for modeling route choice in multimodal networks.

USING CHOICE SETS FOR ESTIMATION AND PREDICTION IN ROUTE CHOICE

This article investigates the relationships between choice set types and analysis purpose, especially estimation and prediction. The choice set types considered are generated objective choice sets and observed subjective choice sets. While for estimation purposes subjective choice sets might be preferred, although objective choice sets might have benefits as well, objective choice sets appear to be most suitable for prediction purposes. Empirical analysis of choice sets for multi-modal inter-urban train trips shows clear distinction between choice models estimated using objective choice sets and using subjective choice sets. Applying these choice models for prediction shows that choice models based on subjective choice sets have a poorer performance when applied to objective sets than vice versa. As a result it is recommended to use objective choice sets for both estimation and prediction purposes.

Application of Constrained Enumeration Approach to Multimodal Choice Set Generation

Collected data often include only information about chosen routes. To gain insight into travelers’ route choice behavior or to predict route shares, one must know the set of alternatives from which travelers have chosen their routes. An alternative approach to choice set generation in mixed multimodal networks is presented. This new algorithm—a run-based, constrained enumeration method that uses branch-and-bound techniques—is suitable for both estimation and prediction. One key characteristic of the algorithm is a set of constraints that reflects observed travel behavior. The proposed algorithm for choice set generation can be applied to a complete multimodal network at once. However, by exploiting knowledge about the structure of multimodal trips, the separate application of the algorithm to partial networks and consecutive concatenation of subroutes into complete door-to-door routes substantially reduce computation times without resulting in incomplete choice sets. This algorithm for choice set generation has been calibrated for and successfully applied to a real-size, mixed multimodal transport network in the Netherlands. A comparison of generated choice sets with reported chosen and known alternatives indicated that the algorithm can generate these alternatives, with high coverage levels as a result. This result clearly indicates that this constrained enumeration approach meets the requirements for choice set generation and thus offers interesting perspectives for route choice analysis and the prediction of route shares. Furthermore, the separate application of the algorithm to partial networks and the consecutive concatenation of subroutes into complete door-to-door trips substantially do not result in incomplete choice sets.

Modeling Transfers in Multimodal Trips: Explaining Correlations

Transfers are essential parts of multimodal trips. A detailed description of the transfer process identifies time, costs, and effort related to the different stages of the transfer process. Since inclusion of multiple transfer attributes generally leads to high correlations between parameter estimates, most travel choice models only distinguish a small number of transfer attributes. When attributes are highly correlated, it is difficult to establish their impact on the travel choice process, especially when more advanced random utility models are used. By analyzing pathsize logit models that differ in the way the transfer process is accounted for, combinations of transfer attributes that best reflect the role of transfers in the travel choice process are established. The analysis uses revealed-preference data on interurban multimodal train trip making in the Netherlands. Apart from log likelihood values, correlations between different classes of transfer attributes are used to evaluate the different model...

Future scenarios for traffic information and management

The limited coordination between public and private actors in the fields of traffic information and management has led to reduced efficiency and sometimes undesirable situations. The main objective of the Strategic Council for Traffic Information and Traffic Management installed by the Dutch Ministry of Transportation is to develop a joint strategy for the development and the organization of traffic information and traffic management by public authorities and private parties. This strategy will outline future developments and related actions, as well as the organization and roles of the relevant actors for traffic management and information activities. To satisfy these requirements, a proposed scenario-based approach entails sketching different scenarios to describe the situations in 2015, 2020, and 2028 for public and private stakeholders involved in traffic management and traffic information. The approach to determine these scenarios, the scenarios themselves, and their implications are described. The developed scenarios were built around the dimension of freedom of choice of the traveler. After extreme scenarios were identified, possible scenarios were sketched and were linked to instruments and to multiple objectives. On the basis of the scenarios, no-regret activities (those beneficial regardless of scenario) were identified as part of the robust strategy forming essential elements for all possible scenarios. These no-regret activities reflect an important outcome of the project; they entail setting up the value chain of traffic information, setting up a data warehouse to share all relevant data (including the functional and technical standards), and preparing for integrated network management and cooperative systems.

Calibrating Dynamic Network Models for Traffic Operator Decision Support

To support traffic operators in regional traffic management centers with their network control tasks, the Traffic Research Center of the Dutch Ministry of Transportation has proposed a two-step scenario-based approach. In the first step, traffic engineers prepare candidate traffic control scenarios that are likely to resolve problems that occur in real-world network traffic operations. In the second step, network operators can try out a limited number of control scenarios with an online prediction system to see which of these best resolves the problems at hand. To prepare the scenarios, a scenario assessment system is used that predicts the impacts of a specific control scenario by using a dynamic network traffic flow model (MetaNet). The development of a fully automated calibration approach for the input and parameters of this macroscopic network simulation model is described. The approach presented consisted of four steps—preparing inflows and turning proportions, establishing lane-specific traffic flow parameters, estimating the global simulation parameters, and determining unresolved model inputs—eventually leading to input data and a set of parameters that yield the best prediction of networkwide traffic conditions. Furthermore, the approach checks the available input data for inconsistencies in terms of network configuration and measurement errors. On the basis of the application examples tested, the approach is well suited for the calibration task at hand, yielding a remarkable improvement in the prediction error. Furthermore, the computation time for a realistic network is sufficient for most practical applications.