## 1 Introduction  
At present, various research fields including _transport behavior_ require investigations and simulations of the dynamic behavior of travelers. In recent studies, it has become increasingly important to establish the interaction between agents. Traditional modeling applications have encountered difficulties in dealing with the complication of the interaction and negotiation of individuals (agents) that are essential to simulating the carpool travel demand [1]. The method that is more suitable for autonomous entity interaction is based on agent-based modeling (ABM). ABM is a distributed and personal-centric approach that allows agents to recognize the interaction of physical elements and describes many issues arising in research fields such as astronomy, biology,ecology, and social sciences. It has also been used in a wide range of topics within the field of transportation science, including vehicle or pedestrian flow simulations, route selection modeling, vehicle tracking and lane change models, and traffic simulations. Carpooling is an environmentally friendly and sustainable emerging traveling mode that aids travelers (carpoolers) to save travel time and travel expenses (fuel, charges, and parking fees). It also cuts emissions and reduces traffic jams. Change in some factors such as the rise in fuel prices, charged parking, or the introduction of new traffic policies may lead to a carpool initiative for an individual. In addition, the social economic characteristics (SEC) such as gender, age, relationships, income, education, job, and vehicle and driving license ownership, may play a dynamic role in finding the right persons to co-travel. In order to co-travel, individuals need to negotiate, coordinate, and in most cases, can adapt their daily schedules to enable co-operation [2; 3]. The agent's daily schedule or agenda is a group of sequential trips and activities. Each activity and trip of the daily schedule is specified by the start time and duration. Each negotiation consists of a small number of agents and their daily schedule can be interrelated through co-operation [2; 3]. This research presents an organizational-based model and agent-based simulation for long-term commuting at an aggregate level (Travel Analysis Zones (TAZ)) based on work trips (home-to-work _HW_ and work-to-home _WH_) that is designed to establish a framework and a carpooling social network of the candidates. The purpose of this research is to examine the effects of time limitations and models on how people adjust their own schedule to co-operate. Carpooling is a concrete example of co-operation between people. The focus is on the mechanisms that simulate human behavior when making collaborative decisions. The agent-based simulations can analyze the aggregation consequences of individual behavioral changes to enable carpooling. The model shall support research on both topics in the arena of large scale agent-based modeling and in the field of co-operation and rescheduling in activity-based models. This paper presents the model and simulation for co-traveling which generalize the conception of interaction, negotiation, and co-ordination of a multi-trips negotiation model. It takes the option of flexible activity planning into account. The model is based on an agent-based and organizational meta-model [4]. The role and organization are the foremost entities in the organizational meta-model. In order to co-travel, agents search for other participants to cooperate with while performing their periodic trips and explore the carpooling social network (CPSN) by emitting carpool invitations and sharing their agendas within a carpooling social group (CPSG). During negotiation, agents may reach complex contracts depending on the \"negotiation model\" (used to match with the carpooling participants) and also on the travel behavior of the individuals. The agents negotiate about trip timings, and on the driver and vehicle selection, and may adjust their daily agenda to enable co-operation.