Lambertus Immers

An Extended Kalman Filter Application for Traffic State Estimation Using CTM with Implicit Mode Switching and Dynamic Parameters

This paper presents a traffic state estimation and prediction model based on the cell transmission model (CTM). The nonlinear CTM is transcribed in a closed analytical state-space form for use within a general extended Kalman filtering framework. The state-space CTM switches implicitly between numerous possible linear modes. The paper provides measurement models for the traffic state and model parameters for automatically estimating traffic conditions and model parameters in an online context. The applicability of the approach is illustrated in a real and a simulated case study.

Marginal Incident Computation: An Efficient Algorithm to Determine Congestion Spillback due to Incidents

In studies on the influence of incidents on travel time, researchers rely on Monte Carlo simulation. Because this procedure is demanding computationally, the research scope is limited. This paper presents a highly efficient method for approximately quantifying congestion spillback due to incidents: marginal incident computation (MIC). MIC superimposes the effect of an incident on a single base simulation run (without incidents) instead of carrying out a complete dynamic network loading with the incident, which would involve many calculations identical to the base simulation (e.g., before or far away from the incident). Whereas the results obtained with MIC vary only slightly from the outcome of a complete dynamic network loading, the gain in computation time is significant: a factor > 1,100 for a case study of the Sioux Falls, South Dakota, benchmark network.

Stochastic Dynamic Networks Loading for Travel Time Variability Due to Incidents

This chapter presents a new method that allows fast Monte Carlo simulation of incidents on a road network. The marginal incident computation (MIC) model presented in this chapter applies similar link and node models as the link transmission model (LTM), a multi-commodity dynamic network loading (DNL) model that combines realistic queue propagation and congestion spillback (consistent with first order kinematic wave theory) with high computational efficiency. The MIC algorithm determines the congestion effects caused by an incident in an approximate way, superimposing these effects onto a single base simulation run with the LTM or an other existing DNL model. The base cumulative vehicle number are altered, according to the congesting arising from the incident. Calculations are only carried out for the affected links, not for the entire network. A significant computation advantage is achieved compared to full explicit simulation, where identical traffic flows are recalculated for different Monte Carlo samples. In large networks, the computation can be reduced to less than 0.1 percent of explicit simulation.

National Data Warehouse: How the Netherlands Is Creating a Reliable, Widespread, Accessible Data Bank for Traffic Information, Monitoring, and Road Network Control

Every day, traffic managers and road users use different sources of information on the current state of the road network in their decision process. The efficiency of these decisions strongly depends on how accurate, reliable, and timely the available information is. Moreover, the data collected are typically scattered in space and time; large areas are usually unmonitored, and data quality is undependable. Within this view, the distribution of a unique data set that contains sufficient levels of quality over the whole network may improve the way information is provided to the user and improve the effectiveness of management strategies. The need for guaranteed standard levels of data quality for road authorities and service providers motivated the establishment of the National Data Warehouse project to provide traffic information as well as information on the status of the road network system as a whole. This information is extended to a basic network level, which allows road authorities or service providers to combine this information with their own data set and obtain a broader view of the problems that occur on the network they manage or monitor. The requirements that such a data bank should satisfy—namely, the accuracy and reliability of information (which depend on the spatial location and aggregation time)—were investigated. The impact of these elements has been quantified through theoretical and numerical analysis, showing that both elements strongly affect good estimation and prediction of travel times and network states, especially under variable traffic conditions.

The effect of dynamic network loading models on DTA-based OD estimation

Congestion causes substantial economic losses, both for individual and commercial transport. This chapter will examine the effect of using different queue mechanisms in the dynamic network loading (DNL) models on the dynamic origin destination (OD) estimation problem on different test networks. The chapter begins with a short review of OD estimation methods based on traffic counts, followed by a discussion of the different dynamic network loading models and the solution algorithm used in this chapter. Next, the effect of choosing one of the above mentioned queuing approaches is examined by solving the OD estimation problem on different test networks. In the last section of the chapter the authors formulate conclusions along with possible future research.

Optimal Redesign of the Dutch Road Network

The Dutch national road network has been developed over centuries. In the past, roads were constructed according to contemporary spatial and transportation planning philosophies. Because the existing road network is a result of a long process of successive developments, the question can be asked whether this network is the most appropriate currently, especially considering the socioeconomic structure of the Netherlands. To answer this question, an optimization algorithm has been developed for designing road networks for a given spatial structure of cities, villages, and industrial activities. With this algorithm, the Dutch road network is redesigned on the basis of minimization of the travel and infrastructure costs and by taking into account the socioeconomic structure of the Netherlands. A comparison between the existing network and the new design shows that the redesigned Dutch national road network has significantly lower total costs than the existing road network. It is found that the construction of roads with more lanes on somewhat different locations leads to a reduction of the total travel time and the total vehicles kilometers traveled.

DYNAMIC ROUTE GUIDANCE DURING MAINTENANCE WORKS, A CASE STUDY

Abstract During road maintenance works traffic often has to be diverted over alternative routes to reach their destinations, since their normal route is not available or has not enough capacity left. This can be done with static signs but this is often not optimal. A better option is to divide the traffic over several alternative routes dynamically. With a case study the use of dynamic route guidance during maintenance works is shown. By dynamically dividing the traffic over several alternative routes, the total flow in the network increases without deteriorating the traffic operation in the rest of the network.