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The use of modeling and simulation aids in deriving many decisions related to transportation planning and traffic operations. Representing the real systems via simulation allows exploring system behavior in an articulated way, which is often impossible in the real world. In this paper, a simulation-based framework is presented to evaluate the impact of congestion charging on daily activity plans of the individuals. Personal decision to accept the congestion charges is evaluated by comparing the value of time with congestion charge. Value of time varies throughout the day depending upon the time pressure at any moment exerted by preceding and succeeding activities. Time pressure during an activity increases if available time for that activity is insufficient to attain the perceived utility. Daily activities in the schedules are modeled using bell-shaped marginal utility that results in sigmoid utility. A model is presented which derives the activity-specific parameters of the marginal utility function for the specific individual. To examine value of time of each person, the congestion charging is applied where personal willingness-to-pay is determined by comparing the ratios of cost to utility for original and adapted schedules. A large-scaled microsimulation of the modeled framework is used to simulate the whole population, which is created by FEATHERS, an operational activity-based model for Flanders, Belgium. The results of the simulation show that the number of individuals who avoid the congestion charges by adapting their schedules is almost three times the number of those who agree to pay it. The proposed framework can be useful to evaluate the tradeoff between value of time and costs where flexibility in selection of time defines the variability in cost. [ABSTRACT FROM AUTHOR]

Research on demand-responsive collective transportation facilities that can act as feeder services to time-table based public transportation (PT) requires detailed and accurate information about the PT infrastructure, including the attachment of bus stops to the appropriate network link. Due to the size of the infrastructure, the data integration shall be automated. This paper describes the effort to prepare data from publicly available OpenStreetMap (OSM) and General Transit Feed Specification (GTFS) sources. Procedures are proposed (i) to build a network derived from OSM suitable for simulations in transportation, (ii) to extract bus stops from GTFS and remove anomalies and (iii) to find candidate network links to attach them. [ABSTRACT FROM AUTHOR]

In order to commute by carpooling, individuals need to communicate, negotiate and coordinate, and in most cases adapt their daily schedule to enable cooperation. Through negotiation, agents (individuals) can reach complex agreements in an iterative way, which meets the criteria for the successful negotiation. The procedure of negotiation and trip execution in the long-term carpooling consists of a number of steps namely; (i) decision to carpool, (ii) exploration and communication, (iii) negotiation, (iv) coordination and schedule adaptation, (v) long term trip execution (carpooling), (vi) negotiation during carpooling and (vii) carpool termination and exploration for new carpool. This paper presents a conceptual design of an agent-based model (ABM) of a set of candidate carpoolers. A proof of concept implementation is presented. The proposed model is used for simulating the interactions between autonomous agents. The model enables communication to trigger the negotiation process; it measures the effect of pick-drop and shopping activities on the carpooling trips. Carpooling for commuting is simulated: we consider a set of two intermediate trips (home-to-work and work-to-home) for the long-term carpooling. Schedule adaptation during negotiation depends on personal preferences. Trip timing and duration are crucial factors. We carried out a validation study of our results with real data (partial) collected in Flanders, Belgium. Simulation results show the effect of constraining activities on the carpooling trips. The future research will mainly focus on enhancing the mechanisms for communication and negotiation between agents. [ABSTRACT FROM AUTHOR]

Freight flows are in essence a result from the exchange of goods between producers and consumers and the transporting firms moving the goods. This essentially constitutes a market interaction among different type of firms, differentiated by many attributes like industry type, size, location and role in the supply chain. A usual final outcome of such an interaction manifests itself in the form of Production-Consumption (PC) matrices, tabulating regional production and consumption pairs for the different goods and geographical region being simulated. It is often the case that this information is obtained only at an aggregate level, either due to firms’ unwillingness to share their trading information or the high cost of obtaining this data or both. Different techniques are used to disaggregate such data. This process often implies over simplified assumptions. In this paper we present a bottom up approach to simulate this goods interchange process between production and consumption firms. The proposed model is based on an offer negotiation and evaluation process among three types of firms; production firms, consumption firms and carrying (transport) firms. The interaction is based on actual firms’ decisions. Agent based simulation technique is used to facilitate capturing some behavioral aspects of the different agents (firms) in the model. One outcome of this model is a set of PC matrices which can be used in further transport modelling steps. [ABSTRACT FROM AUTHOR]

In Underwater Acoustic Sensor Networks (UASNs), fundamental difference between operational methodologies of routing schemes arises due to the requirement of time-critical applications therefore, there is a need for the design of delay-sensitive techniques. In this paper, Delay-Sensitive Depth-Based Routing (DSDBR), Delay-Sensitive Energy Efficient Depth-Based Routing (DSEEDBR) and Delay-Sensitive Adaptive Mobility of Courier nodes in Threshold-optimized Depth-based routing (DSAMCTD) protocols are proposed to empower the depth-based routing schemes. The proposed approaches formulate delay-efficient Priority Factors (PF) and Delay-Sensitive Holding time ( DS HT) to minimize end-to-end delay with a small decrease in network throughput. These schemes also employ an optimal weight function WF for the computation of transmission loss and speed of received signal. Furthermore, solution for delay lies in efficient data forwarding, minimal relative transmissions in low-depth region and better forwarder selection. Simulations are performed to assess the proposed protocols and the results indicate that the three schemes largely minimize end-to-end delay of network. [ABSTRACT FROM AUTHOR]

In the carpooling, individuals need to communicate, negotiate and in most cases adapt their daily schedule to enable cooperation. Through negotiation, agents (individuals) can reach complex agreements in an iterative way which meet the criteria for successful negotiation. The result of the negotiation depends on “negotiation mechanism” used to match and on the behavior of the agents involved in the negotiation process. This paper presents an organizational and agent-based model for commuting by candidate carpoolers using a simple negotiation mechanism aimed at finding an acceptable agreement between agents to carpool. Initially, the agents involved in exploration process, search for their partners via some kind of Agent Communication Language (ACL); after finding potential partners, they start a negotiation to find matched partner to carpool. After having found a good match, the agents can carpool for a specified time period. The agents join the carpool group when the negotiation is successful and leave the carpool group when the agreed time period is expired. Agents can be part of several carpool groups sequentially. The first implementation used home and work locations as well as preferred trip start times and carpool periods determined by uniformly sampling given sets. Furthermore a simplistic negotiation mechanism used roughly to produce possible results for the synthetic data. An automated negotiation model is implemented and validated through simulation. The Janus multi-agent platform is used. Future research will mainly focus on the development of behaviorally sound negotiation mechanism. [ABSTRACT FROM AUTHOR]

Abstract: Carpooling is an emerging alternative transportation mode that is eco-friendly and sustainable as it enables commuters to save time, travel resource, reduce emission and traffic congestion. The procedure of carpooling consists of a number of steps namely; (i) create a motive to carpool, (ii) communicate this motive with other agents, (iii) negotiate a plan with the interested agents, (iv) execute the agreed plans, and (v) provide a feedback to all concerned agents. The state-of-the-art research work on agent-based modeling is limited to a number of technical and empirical studies that are unable to handle the complex agent behavior in terms of coordination, communication and negotiations. In this paper, we present a conceptual design of an agent-based model (ABM) for the carpooling a that serves as a proof of concept. Our model for the carpooling application is a computational model that is used for simulating the interactions of autonomous agents and to analyze the effects of change in factors related to the infrastructure, behavior and cost. In our carpooling application, we use agent profiles and social networks to initiate our agent communication model and then employ a route matching algorithm, and a utility function to trigger the negotiation process between agents. We plan to, as a part of the future work, develop a prototype of our agent-based carpooling application based on the work presented in this paper. Furthermore, we also intend to carry out a validation study of our results with real data. [Copyright &y& Elsevier]

Abstract: This study aims to show an ability of Ontology, which is a formal explicit description of concepts in a domain of interest, in an activity-based microsimulation. Thus, an agent-based carpooling application using ontology techniques is presented as a case study with a focus on three functions of the Ontology. First, Ontology facilitates integrating between heterogeneous databases by defining the relationship between their concepts. Second, Ontology verifies the compatibility and consistency between the different angles to combine varied models in a common structure by providing shared knowledge between different domains modelling with the definition of objects and concepts. Lastly, Ontology is useful for modelling agent communication by means of making explicit the parsed message between agents with the shared knowledge. This paper introduces related studies and basic knowledge about using methodologies, and supports an example of using Ontology in an agent-based carpooling simulation. [Copyright &y& Elsevier]