Francesco Viti

Joint Modeling of Advanced Travel Information Service, Habit, and Learning Impacts on Route Choice by Laboratory Simulator Experiments

A conceptual modeling framework is proposed, and mathematical sub-models for route choice on motorways and urban networks are derived. The models convey the most relevant aspects that play a role in route choice, including learning, risk attitude under uncertainty, habit, and the impacts of advanced travel information service on route choice and learning. To gain insight into the relative importance of the different aspects and processes of route choice behavior, which support the proposed conceptual framework, the models were estimated with data from two experiments carried out with a so-called interactive travel simulator. The latter is a new research laboratory that combines the advantages of both stated preference and revealed preference research. Many relevant contributions on the aforementioned aspects that play a role in route choice can be found in the literature, but a simultaneous consideration of all is lacking. On the basis of these contributions from the literature, a conceptual framework tha...

SPECIALIST: A dynamic speed limit control algorithm based on shock wave theory

In literature there are several approaches to eliminate shock waves on freeways by means of dynamic speed limits. Most of them incorporate control systems that have a high computational complexity or that contain parameters without direct physical interpretation, which may make the application in real life difficult. Here we present an approach called SPECIALIST that is based on shock wave theory, and that has parameters with clear physical meaning. The clear interpretation of the parameters leads to an intuitive and insightful formulation of the tuning guidelines. One of the most important features related to the parameter tuning is that the stability of the traffic flow can be ensured by selecting a proper maximum density that is allowed to occur in the speed-controlled area. In addition, other parameters can be tuned for more robust behavior of the algorithm. We first present the theory of shock wave resolution, and next we develop a practical control algorithm based on this theory. A unique feature of the algorithm is that it first judges the solvability of a shock wave and only starts controlling the speed limits if the shock wave is classified as solvable. The algorithm is demonstrated with a simulation example, and it is shown that its performance is similar to existing approaches.

Driving behavior interaction with ACC: results from a Field Operational Test in the Netherlands

In the Netherlands, a field operational test was conducted in 2006 to assess the impact of two advanced driver assistance systems (ADAS), namely adaptive cruise control (ACC) and lane departure warning (LDW) systems. The research goal was to estimate the effects of these systems on road capacity, safety and emissions. In this paper we focus on the interaction between driver and ACC system using the data from this FOT. It is found that drivers choose headway settings according to their manual driving behavior. Moreover, they often keep the system deactivated under dense traffic conditions. It is also observed from the data that the system, once de-activated, either automatically or manually, needs some time to become again active. These findings imply that, even with 100% cars on the road equipped with ACC, manual driving behavior will still be a determinant factor.

Valuation of Different Types of Travel Time Reliability in Route Choice: Large-Scale Laboratory Experiment

Travelers sometimes experience extremely long travel times on a route. The Travel Simulator Laboratory (TSL) of Delft University of Technology is used to study the effect of these extreme experiences on route choice. The TSL allows for a completely controlled experiment and good research methodology. It is hypothesized that together with the average travel time and the variance, the most extreme travel times experienced influence a persons perception of the attractiveness of the route. Travel information is assumed to be able to alter this perception. Data from 2,500 respondents were gathered with the TSL. Route switching behavior after a regular experience and after an extreme experience was analyzed. People switched routes after an extreme experience significantly more often when the information that they received before the route choice was wrong than they did when it was correct. Moreover, travelers clearly preferred a route that is sometimes bad and most of the time good over a route that is symmetr...

Speed and acceleration distributions at a traffic signal analyzed from microscopic real and simulated data

Modeling realistic driving behavior at signalized intersections is crucial for many applications, for instance to determine the traffic signal performance, to assess the effect of different control strategies, or to estimate traffic emissions. In these applications, often microscopic models are used to simulate the trajectory of each vehicle. Despite the possibility to model vehicles with great detail and at fractions of a second, speed, acceleration and deceleration characteristics are determined by parameters that are rarely calibrated using real data, and default parameters are often chosen. This is because collecting real vehicle trajectories near traffic signals is a challenging task. This paper presents a method to collect such dataset using image processing techniques. This methodology allows one to obtain vehicle trajectories near a signal control, and to measure individual vehicles speeds and accelerations at a microscopic level. We focus on the analysis the empirical distributions of speeds and accelerations observed with this unique dataset near and up to a few meters upstream of the stop-sign. We compared these distributions with the results of repeated simulations of two microscopic software programs, using default parameters. Some inconsistencies were found with this comparison, which suggests that the two analyzed microscopic simulation programs run with default parameters do not provide realistic results for this type of road sections.

Delay at Controlled Intersections: The Old Theory Revised

The calculation of delays at an intersection is an old problem that has been studied and solved by many researchers. This paper reanalyzes the problem by using a Markov chain model for the probability distribution of queue length. From the dynamics of the expectation value of the queue length, the authors derive a formula for the delay in fixed time traffic control. The effect of the overflow queue is made explicit. The result is a new formula, but even more important, a clear understanding of the role of the overflow queue

The Dynamics and the Uncertainty of Queues at Fixed and Actuated Controls: A Probabilistic Approach

The queue process at controlled junctions plays a fundamental role in many transportation problems, and they are a main determinant of the variability of traffic. Despite the large number of queue models developed in the last 50 years, there is a need for insight into the dynamic and stochastic behavior of traffic at controlled junctions. The existing models are often developed under heuristic, simplifying assumptions, which limit their application validity and interpretation opportunities. This article aims to fill this gap by formulating the queue process as probabilistic. This is done both at fixed and at vehicle actuated controls. Assuming a certain distribution of arrivals and departures one can calculate the probability distribution of queues at fixed control signals. Even if these distributions are assumed stationary, the probability of observing a number of vehicles in queue has a dynamic character. Vehicle actuated controls are in principle designed to adapt the duration of green times according to this dynamic process. By doing that, signal times become dynamic stochastic variables, thus vehicle delays and queues are still random processes in these systems. In this article we compare the performance of these two control types in view of network reliability. The models developed in this research are simple and require small computation times, and they are shown to be consistent with the more elaborate models used in microscopic simulation programs.

Dynamic Traffic Assignment: Recent Advances and New Theories Towards Real Time Applications and Realistic Travel Behaviour (Editorial)

This chapter gives an overview of the research elements characterizing dynamic traffic assignment (DTA) theory. Traditionally, traffic assignment has been developed exclusively in the static context, before the seminal works of Merchant and Nemhauser. This approach is still widely accepted in planning and design problems, or in general when congestion dynamics are of minor importance. The need for models able to capture in a more realistic way the dynamic features of traffic has been acknowledged since the growing application of dynamic management strategies, real time traffic control and information systems etc., and also because of the increasing congestion levels worldwide. The simplifying assumptions characterizing static assignment approaches (e.g., steady-state conditions, time independency of the demand and the travel costs) are under theses conditions unacceptable as they would fail in capturing important dynamic aspects and in assessing the impact of some management measure. The goal of DTA is therefore to represent more correctly the dynamic character of traffic and to capture the temporal effects of congestion.

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.

Microscopic Data for Analyzing Driving Behavior at Traffic Signals

Driving behavior observed at traffic networks varies considerably depending on the type of road section. At signalized junctions, drivers are taught to moderate their speed, and to comply with the priority rules set by the traffic light. Therefore, vehicles stop and queue up during the red phase, and they leave the junction during the green and amber phases. During these operations, vehicle driving patterns vary significantly. The way they decelerate, stop at the back of the queue and accelerate changes from driver to driver. Aggressive drivers may show to operate stronger accelerations and to respond more quickly to the right-of-way signal. During the amber phase, some aggressive drivers accelerate to clear the intersection faster, while risk-averse drivers may decide to decelerate earlier, or even brake hard to avoid passing the stop-sign after the start of the red phase. Moreover, the observed trajectories will depend on whether a queue is actually present and on its length, as well as on the road characteristics, e.g., how clear is the view upstream of the junction, whether one or more lanes are dedicated to a traffic stream, etc. Therefore, individual vehicle trajectories are found to be highly variable at signalized intersections, as individual speeds and speed variations have strong dynamic and stochastic patterns. In applications that require accurate estimates of vehicle driving modes, like when estimating concentration levels of emissions, it is fundamental to provide realistic estimates of these trajectories, and, more importantly, to derive, from these trajectories, realistic speeds and speed variations.