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The boom seen in artificial intelligence in recent years has led to a revolution in the automotive industry. Numerous automakers around the world, such as Tesla, Toyota, Honda, and BMW, have achieved giant strides in the development of e-autonomous vehicles. Consequently, shared electric automated vehicle mobility (SEAVM) systems, which are a crucial part of future innovative transportation solutions, have attracted significant attention from the research community, particularly from a design perspective. However, the flexibility of shared automated mobility systems may lead to a self-operating technology issue (unequal distribution of vehicles), since users in these systems can pick up and drop off electric vehicles wherever they like. With this in mind, this paper addressed the issues of autonomous repositioning and the assignment of shared autonomous electric vehicle systems to balance a system’s network and fulfill its demand. Modeling, analysis and assessment of the system’s performance were carried out using stochastic Petri nets formalism, which included determining the average time areas were empty/congested and the number of unserved consumers, and estimating the redistribution service launch moment. Furthermore, many simulation scenarios were analyzed, including repositioning and without repositioning scenarios, in order to evaluate the efficiency of the model and to show the potential of using Petri nets as a probabilistic formalism approach for the modeling of e-automated mobility systems.

In recent years, one-way Electric Car sharing (ECs) systems have been introduced in many cities. One-way trips, as well as battery range issues, directly influence the quality and dynamics of such systems. Due to the demand and supply imbalance at stations, the ECs operators are faced with crucial operational challenges to reduce the relocation costs and increase the number of users. An agent-based relocation strategy based on real-time inventory control within the framework of generalized stochastic Petri Nets (PN) and a discrete event simulation has been proposed in this paper. Furthermore, an associated system performance evaluation was also developed. This model further assesses the effects of system characteristics such as the battery charging level availability threshold on the behavior and dynamics of the system. Moreover, the developed model and simulation show the potential of using PN models to predict critical situations, analyze relocation strategy efficiency, and improve system performance. Results from the simulation indicate that the overall relocation trips are reduced by estimating the time to launch the relocation process, as well as the conflicts between agents (controlling the assignment of agents among stations) during the balancing process are efficiently resolved. The proposed model and simulation algorithm have been applied to the BlueSG network in downtown Singapore., IEEE Transactions on Intelligent Transportation Systems, 22 (5), ISSN:1524-9050, ISSN:1558-0016

In recent years, e-commerce businesses have seen an increase in the daily volume of packages to be delivered, as well as an increase in the number of particularly demanding customer expectations. In this respect, the delivery mechanism became prohibitively expensive, particularly for the final kilometer. To stay competitive and meet the increased demand, businesses began to look for innovative autonomous delivery options for the last mile, such as autonomous unmanned aerial vehicles/drones, which are a promising alternative for the logistics industry. Following the success of drones in surveillance and remote sensing, drone delivery systems have begun to emerge as a new solution to reduce delivery costs and delivery time. In the coming years, autonomous drone sharing systems will be an unavoidable logistical solution, especially with the new laws/recommendations introduced by the Flight World Organization on how to organize the operations of these special unmanned airline systems. This paper provides a comprehensive literature survey on a set of relevant research issues and highlights the representative solutions and concepts that have been proposed thus far in the design and modeling of the logistics of drone delivery systems, with the purpose of discussing the respective performance levels reached by the various suggested approaches. Furthermore, the paper also investigates the central problems to be addressed and briefly discusses and outlines a series of interesting new research avenues of relevance for drone-based package delivery systems.

Electric cars sharing system is a new mode of urban ecologic transportation increasing in the world. The exploitation of this transport system requires repositioning strategies. Rebalancing system is costly for the operator (number of trucks, number of cars) and the high number of tours of redistribution trucks between stations leave a pollution impact on the environment, therefore car sharing systems their contribution to improving the environment remains one of its main assets, risk of not hold. In this paper we present a pertinent model capable to reproducing the real functioning of car sharing systems using the stochastic Petri Net. The proposed approach is envisioned to permit planners improving the organization, dimensioning and management of this system in the city.

With the recent development of smart cities all over the world, many new performance services have been developed, including smart mobility, energy and waste collection. In general, waste collection operators face the challenge of routing management, so as to reduce the costs of transportation and energy consumption. This paper proposes a waste collection strategy model based on real time inventory control of the vehicles' routing problem, with stochastic Petri nets (PN). The developed model and simulations show the capability of using PN models to predict the critical situations, analyse collection strategy efficiency, and improve performance. Results from the numerical example indicate that the overall vehicle travel distance for waste collection has been significantly reduced by estimating the exact moment to launch the collection service, as well as resolves conflict between vehicles during the collection. Simulation scenarios were introduced to assess the real time impact by monitoring the collection process.

Public Bicycle-Sharing Systems (PBSS) have been appearing in more and more cities around the world in the last few years. Although their apparent success as an alternative form of public transportation mode, there are major challenges confronting the operators while few scientific works are available to support such complex dynamical systems to influence their economic viability and operational efficiency. One of the most crucial factors for the success of a PBS system is its ability to ensure that bicycles are available for pick up and vacant berths available for bicycle drop off at every station. In this paper, we develop an original discrete event approach for modelling and performance evaluation of public bicycle-sharing systems by using Petri nets with time, inhibitor arcs and variable arc weights.

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A crucial factor for the success of bike sharing system is its ability to ensure that bicycles are available for pick up and vacant berths available for bicycle drop off at every station. This paper deals with an original modelling approach of bike-sharing systems including their repositioning activities by using Petri nets with variable arc weights.

Public Bicycle-Sharing Systems (PBSS), also known as self-service public bicycle systems, are available in numerous big cities in the world (Velib' in Paris, Bicing in Barcelona, Call-aBicycle in Munich, OyBicycle in London, etc.). Since its inception, Bicycle-sharing programs have grown worldwide. There are now programs in Europe, North America, South America, Asia, and Australia. A still growing list of cities which provides such green public transportation mode can be found at the Bicycle-sharing world map (http://Bikesharing.blogspot.com) as shown in Figure 1. As a good complementary to other urban transportation modes, bicycle use entails a number of benefits including environmental, mobility and economic benefits. The public bicycle sharing systems are especially useful for short-distance city transport trips and to face many public transport problems, including growing traffic congestion, pollution, greater car dependency, buses caught in city congestion, and ageing transport infrastructure.

In recent years, self-service public bicycle systems (SPBS) are available in numerous big cities in the world (Velib’ in Paris, Bicing in Barcelona, Call-a-bike in Munich, Oybike in London …). As a new public transportation mode, bicycle use entails a number of benefits including environmental, mobility and economic benefits. In this paper, we develop an original Petri net approach for SPBS modelling and performance evaluation for control purposes. A modular framework based on Petri nets with marking dependent weights is proposed and a simulation software tool is developed and used to simulate and validate models described in this paper. Our approach is intended to help planners and decision makers in determining how to implement, and operate successfully these complex dynamical systems.