Simulation of railroad terminal operations and traffic control strategies in critical scenarios

n/

Traffic Modeling of a Cooperative Charge While Driving System in a Freight Transport Scenario

The aim of this paper is to present a research study on a traffic model developed for analysing the performance of the wireless inductive systems for charging while driving (CWD) fully electric vehicles (FEVs) from both traffic and energy points of view. The design assumptions of the developed traffic model are aimed to simulate in particular a freight distribution service in a fully cooperative traffic environment. In this case, the CWD service could be used to guarantee the minimum state of charge (SOC) of the batteries at the arrival to the depot that allows the vehicles to shortly start with further activities. In this way, the fleet manager could avoid wasting time for the stationary recharge, thus increasing the level of service of the freight distribution. The CWD system is applied to a multilane ring road with several intermediate on-ramp entrances, where the slowest lane is reserved for the charging activities, when authorized vehicles are present. A specific traffic model has been developed and implemented adopting a mesoscopic approach, where vehicle energy needs and charging opportunities affect drivers’ behavior. Overtaking maneuvers, as well as new entries in the CWD lane of vehicles which need to charge, have been modeled by taking into account a fully cooperative driving system among vehicles which manages an adequate gap between consecutive vehicles. Finally, a speed control strategy in which vehicles can be delayed to create an empty time-space slot in the CWD lane, is simulated at a defined node. This type of control, though is simulated to allow extraordinary maintenance operations, which may require a free charging zone for a given time slot, could also be applied to support merging maneuvers for on ramp vehicles

Monitoring urban accessibility for freight delivery services from vehicles traces and network modelling

n/

Analysis of real driving data to explore travelling needs in relation to hybrid–electric vehicle solutions

The paper presents a methodology and an analysis applied to a real-life dataset, which refer to an extendedperiod that lasted more than one year, pertaining to trips undertaken in Europe by more than one thousandvehicles. The results in this paper are an example of the detailed information that can be extracted from roughdata to support the decisions of stakeholders andfinal users (e.g. car makers, authorities, drivers), as well as tounderstand which road vehicle features will be able to comply with the observed daily usage of automobiles.The main scope of the paper has been to focus on variables concerning the duration and lengths of trips, theidle times, and the energy consumed by engines. These variables have been correlated and compared with thecurrent and expected hybrid and electric ranges of autonomy, as constrained by the present and next generationof electric batteries, both in terms of autonomy and time required for their recharging. Therefore, the aim of thestudy has been tofind answers to the following research question: considering the daily mileage, actual fuelconsumption and idle time structure, can hybrid and electric powertrains represent adequate alternatives totraditional engines, considering the present battery ranges and charging alternatives?Long distance trips have been analysed in detail to obtain a better understanding of whether they can becovered by electric cars in the same ways as they are with those based on internal combustion engines. In theextensive sample that has been analysed, in order to satisfy 99,9% of the daily trips, it would be necessary toraise the range to 400 km. This target could be reached by adopting a PHEV (plug-in) or a full-electric car withan equivalent range. This study provides a quantitative analysis of the energy needs, obtained over a wide rangeof usage of road vehicles, and attempts to correlate them with the opportunities of recovering energy during theidle time detected over real-life 24h driving cycles, assuming the availability of intermediate charge

Measure of urban accessibility provided by transport services in Turin: a traveller perspective through a mobility survey

n/

"Charge while driving" for electric vehicles: road traffic modeling and energy assessment

The aim of this research study is to present a method for analyzing the performance of the wireless inductive charge-while-driving (CWD) electric vehicles, from both traffic and energy points of view. To accurately quantify the electric power required from an energy supplier for the proper management of the charging system, a traffic simulation model is implemented. This model is based on a mesoscopic approach, and it is applied to a freight distribution scenario. Lane changing and positioning are managed according to a cooperative system among vehicles and supported by advanced driver assistance systems (ADAS). From the energy point of view, the analyses indicate that the traffic may have the following effects on the energy of the system: in a low traffic level scenario, the maximum power that should be supplied for the entire road is simulated at approximately 9 MW; and in a high level traffic scenario with lower average speeds, the maximum power required by the vehicles in the charging lane increases by more than 50 %

The influence of time windows on the costs of urban freight distribution services in city logistics applications

In freight distribution services a required quality level may have a relevant effect on transportation costs. For this reason an evaluation tool is useful to compare different service settings and support the decision, on the base of quantitative indicators. This paper proposes a method for cost evaluation in this context and presents an application to a case study concerning a freight distribution service, which operates on a wide road network having a city centre, a peripheral urban area and a peri-urban rural zone. A simulation method is proposed to obtain real-life scenarios in order to test the method and its indicators. The performance of each indicator has been evaluated in an experimental context to produce realistic test cases, using a trip planning tool and a demand generator. First, the behaviour of the indicators is analysed with regard to the time windows width planned for the service. Then, their ability in estimating the total transportation cost to satisfy all the requests, under different time period profiles, is shown. The results confirm the ability of the set of indicators to predict with a good approximation the transportation costs and therefore to be used in supporting the service quality planning decision

Estimating charging demand by modelling EV drivers' parking patterns and habits

The diffusion of battery electric vehicles (BEVs) requires a proper charging infrastructure to supply users the chance to charge their vehicles according to energy, time, and space needs. Thus, city planners and stakeholders need decision support tools to estimate the impacts of potential charging activities and compare alternative scenarios. The paper proposes a modelling approach to represent parking activities in urban areas and obtain key indicators of the electric energy required. The agent-based model reproduces the dynamics of user parking and assesses the impacts on the electricity grid during the day. Since the focus is on parking activities, no detailed data on vehicle trips are required to apply the standard demand modelling approach, which would require Origin-Destination matrices to simulate traffic flows on the road network. Preliminary results concerning the city of Turin are presented for simulated scenarios to identify zones where charging demand can be critical and peak events in electric power over the day. The model is designed to be scalable for all European cities because, as the case study shows, it uses available data. The results obtained can be used for the design of charging infrastructure (power and type) by zones

Evoluzione dell'auto verso l'autonomia: collocazione storico-evolutiva, motivazioni ed effetti sulla sicurezza

Intervento di sintesi sull'evoluzione dell'auto verso l'autonomia: dopo la collocazione evolutiva dell'innovazione e dell'automazione nella storia dell'automobile, vengono esposte le motivazioni per l'introduzione della guida assistita, forse un domani dell'autonomia integrale, con gli effetti attesi sulla sicurezza stradale

A Full-fledge Simulation Framework for the Assessment of Connected Cars

Abstract Intelligent Transport Systems (ITS) have emerged as an integral part of smart cities, providing increased ease of mobility as well as efficiency and safety in vehicular traffic. Given its wide array of applications, ITS has also become a multidisciplinary field of work where vehicular communications, traffic control, ADAS (Advance Driver Assistance System) sensors, and vehicle dynamics have all to be accounted for. The study of such diverse aspects makes the evaluation of new ITS approaches, algorithms, and protocols not a small feat. For this reason, the availability of an effective, scalable, and comprehensive tool for the investigation and virtual validation of new ITS solutions is paramount. In this work, we present a simulation framework, called CoMoVe (Communication, Mobility, Vehicle dynamics), that effectively addresses the above need, as it enables the virtual validation of innovative solutions for vehicles that are both connected and equipped with ADAS sensors. Our framework encapsulates the important attributes of vehicle communication, road traffic, and dynamics into a single environment, by combining the strengths of different simulators. CoMoVe finds its use to evaluate the impact of vehicle connectivity, while imposing causality on vehicle dynamics and mobility. Such an assessment can greatly facilitate the development of control systems, algorithms, and protocols for real-world ITS