PurposeThis paper claims that the parking policy is one of the most obvious tools for reducing traffic congestion, pollutant emissions and conflicts between transportation network users. The purpose of this paper is to propose and implement a strategy, via a simulation tool, for the sharing of parking places between light cars and vans for goods delivery.Design/methodology/approachTemporal and spatial dynamic booking of on‐street parking places is described by using the multi‐agent paradigm. Main agents concerned by the sharing of parking places, their rules and interactions are implemented. Behavioral models and learning process of cognitive agents based on stated preferences collected beside the network users are designed for capturing multi‐agent interactions.FindingsBy coupling a 2D traffic simulation tool and the Copert III methodology, it is possible to simulate the traffic and environmental consequences of several scenarios for different infrastructures, occupancy rate of the places reserved for goods delivery and durations of the delivery process.Research limitations/implicationsSeveral points are under development: a 3D environment will capture with more realism the behavior of agents in a larger spatial scale and in real time. The behavioral models will be designed by stated preferences obtained from surveys containing questions coupled with pictures of possible scenarios.Practical implicationsApplied in a real context, the sharing of parking places strategy shows benefits for traffic and for the environment. A decision maker can use this strategy for simulating scenarios, in the context of an urban area in particular.Originality/valueThe paper demonstrates how a simulation tool based on strategy of parking place sharing can satisfy constraints of transportation network users.

This study is carried out in the framework of SUCCESS (Smaller Urban Communities in CIVITAS for Environmentally Sustainable Solutions), an European project funded by the European Commission under the CIVITAS program. These demonstration projects provide a means of testing out a wide range of projects in a number of cities and the results of the evaluation will assist in showing which were successful, in what way and how that was achieved. One of these projects is the car-sharing implementation. Carsharing is defined as a self service which allows to each subscriber for reaching a vehicle, for the duration and the way of his choice. In the current state, where the impacts of the pollution and the congestion of cities are increasingly acute, the car-sharing service can be an attractive complement for other means of transportation. For it, this type of service must ensure a high level of temporal and spatial availability. For the managers of a car-sharing service it means an efficient management of the existing system and for the local authorities it means the study of the opportunities of its extension. This work proposes to the decision makers an approach of aid to the extension of the service based on the modeling of the preferences of the potential users.

Complexity of car park activity is reproduced from a concurrent execution of behaviour of various drivers. This paper presents a step in the development of a multimodal traffic simulator based on multi-agent paradigm and designed as a decision aid tool as well as a video game. The user-player has the opportunity to test different scenarios. We propose an approach for designing the decision-making rules and the learning mechanism for a car driver agent. For that, a panel of methods such as stated preference modelling, Design Of Experiments and data fusion is used. Initial behavioural models, based on similar preferences, are developed for specified categories. Each agent will adapt its behaviour after executing its learning process. Our approach can be used in order to optimize needs of road network users and those of people in charge of traffic regulation. A demonstrator has been developed to test parking policies in an urban area as well as changes of car park characteristics.