This paper describes a study which gives insight into the size of improvement that is possible with individual in-car routing advice based on the actual traffic situation derived from floating car data (FCD). It also gives an idea about the required penetration rate of floating car data needed to achieve a certain degree of improvement. The study uses real loop detector data from the region of Amsterdam collected for over a year, a route generating algorithm for in-car routing advice, and emulated floating car data to generate the routing advice. The case with in-car routing advice has been compared to the base case, where drivers base their routing decisions on average knowledge of travel times in the network. The improvement in total delay using the in-vehicle system is dependent on penetration rate and accuracy of the floating car data and varies from 2.0% to 3.4% for 10% penetration rate. This leads to yearly savings of about 15 million euros if delay is monetarised using standard prices for value of time (VOT).@en

Travel and route guidance services are widely available. Social navigation services that provide travelers with advice aimed at minimizing driver travel time, while also taking into account the effect on travel times of other travelers, are relatively new. Theoretically, social navigation has been shown to reduce total travel time by 10% to 30%. This paper presents the evaluation results of a largescale field trial for pretrip and ontrip route advice with load balancing, in which about 20,000 participants were active. The evaluation provided insight into the potential effects of incar information services, such as effects on user behavior, traffic flow effects, and technical aspects. Participants used mostly the pretrip advisories. Compliance with the ontrip route advice was 50%, which was considered high (compared with compliance with route advice on variable message signs). An effect on traffic flow could not be measured, as penetration rates were (despite thousands of users) still too low. An offline study using measured travel times combined with a traffic model, however, showed that substantial delay reductions can be achieved for the Amsterdam, Netherlands, region. Participants’ appreciation of the service resulted in a mixed picture with positive and negative ratings. The main practical contribution of this paper is that the results can be used to develop social navigation services. Empirical insights about route advice compliance can be seen as the main scientific contribution.

@en

This paper discusses the assessment of the effects of Integrated full-Range Speed Assistance (IRSA), using the ITS modeller. The aim of IRSA is to assist drivers in their longitudinal driving task by providing speed advice or speed warnings and cruise control-like functionalities. The effects of the application of IRSA in two scenarios (Approaching a traffic jam and Approaching a reduced speed limit zone) are presented. In addition, general aspects of modelling vehicle and driver behaviour for co-operative systems are discussed, and how this is done in the ITS modeller.@en

The need for evaluation of ITS systems requires new modelling tools that allow a detailed modelling of both the roadside and the in-vehicle systems. One of the elements needed is a reliable longitudinal driver model. In this paper we outline the requirements of such a model and review the models that are available in the literature. We select the Helly car following model that was previously applied in the MIXIC simulation model as the most appropriate. We illustrate the use of the model by case studies from recent European projects and a Dutch project.

@en

Within the coming years, the developments of infrastructural and in-vehicle ITS systems will come together and result in the development of cooperative vehicle-infrastructure ITS systems. The development of these integrated cooperative systems will require new modelling tools that allow a detailed modelling of both the roadside and the in-vehicle systems and especially the cooperation between them. In this paper, such a modelling tool is presented: the ITS modeller. Within the ITS modeller, intelligent roadside and vehicle systems can be easily implemented and tested. It is equipped with ready-to-use evaluation modules for throughput, safety, noise and emissions.@en