International journal of transportation science and technology 

About: International journal of transportation science and technology is an academic journal published by Elsevier BV. The journal publishes majorly in the area(s): Transport engineering & Computer science. It has an ISSN identifier of 2046-0430. It is also open access. Over the lifetime, 431 publications have been published receiving 5477 citations. The journal is also known as: Transportation science and technology.

Assessing the impacts of deploying a shared self-driving urban mobility system: An agent-based model applied to the city of Lisbon, Portugal

Abstract: This paper examines the changes that might result from the large-scale uptake of a shared and self-driving fleet of vehicles in a mid-sized European city. The work explores two different self-driving vehicle concepts – a ridesharing system (Shared Taxi), which emulates a taxi-like system where customers accept small detours from their original direct path and share part of their ride with others and a dynamic bus-like service with minibuses (Taxi-Bus), where customers pre-book their service at least 30 min in advance (permanent bookings for regular trips should represent most requests) and walk short distances to a designated stop. Under the premise that the “upgraded” system should as much as possible deliver the same trips as today in terms of origin, destination and timing, and that it should also replace all car and bus trips, it looks at impacts on car fleet size, volume of travel and parking requirements. Mobility output and CO2 emissions are also detailed in two different time scales (24 h. average and peak-hour only). The obtained results suggest that a full implementation scenario where the existing metro service is kept and private car, bus and taxi mobility would be replaced by shared modes would significantly reduce travelled vehicle.kilometres and CO2 emissions.

Advancements, prospects, and impacts of automated driving systems

Abstract: Over the last decade, significant progress has been made in automated driving systems (ADS). Given the current momentum and progress, ADS can be expected to continue to advance and a variety of ADS products will become commercially available within a decade. It is envisioned that automated driving technology will lead to a paradigm shift in transportation systems in terms of user experience, mode choices, and business models. In this paper, we start with a review of the state-of-the-art in the field of ADS and their deployment paths. It is followed by a discussion of the future prospects of ADS and their effects on various aspects of the transportation field. We then identify two specific use cases of ADS where the impacts can be significant – personal mobility services and vehicle automation for aging society. A survey of impact assessment studies and the associated methodologies for evaluating ADS is given, which is followed by concluding remarks at the end of the paper.

Unmanned Aerial Aircraft Systems for Transportation Engineering: Current Practice and Future Challenges

Abstract: Acquiring and processing video streams from static cameras has been proposed as one of the most efficient tools for visualizing and gathering traffic information. With the latest advances in technology and visual media, combined with the increased needs in dealing with congestion more effectively and directly, the use of Unmanned Aerial Aircraft Systems (UAS) has emerged in the field of traffic engineering. In this paper, we review studies and applications that incorporate UAS in transportation research and practice with the aim to set the grounds from the proper understanding and implementation of UAS related surveillance systems in transportation and traffic engineering. The studies reviewed are categorized in different transportation engineering areas. Additional significant applications from other research fields are also referenced to identify other promising applications. Finally, issues and emerging challenges in both a conceptual and methodological level are revealed and discussed.

Exploring the use of automated vehicles as last mile connection of train trips through an agent-based simulation model: An application to Delft, Netherlands

Abstract: The last mile in a public transport trip is known to bring a large disutility for passengers, because the conventional transport modes for this stage of the trip can, in many cases, be rather slow, inflexible and not provide a seamless experience to passengers. Fully automated vehicles (AVs), that is, those which do not need a driver, could act as a first mile/last mile connection to mass public transport modes. In this paper, we study a system that we call Automated Last-Mile Transport (ALMT), which consists of a fleet of small, fully automated, electric vehicles to improve the last mile performance of a trip done in a train. An agent-based simulation model was proposed for the ALMT whereby a dispatching algorithm distributes travel requests amongst the available vehicles using a FIFO sequence and selects a vehicle based on a set of specified control conditions (e.g. travel time to reach a requesting passenger). The model was applied to the case-study of the connection between the train station Delft Zuid and the Technological Innovation Campus (Delft, The Netherlands) in order to test the methodology and understand the performance of the system in function of several operational parameters and demand scenarios. The most important conclusion from the baseline scenario was that the ALMT system was only able to compete with the walking mode and that additional measures were needed to increase the performance of the ALMT system in order to be competitive with cycling. Relocating empty vehicles or allowing pre-booking of vehicles led to a significant reduction in average waiting time, whilst allowing passengers to drive at a higher speed led to a large reduction in average travel time, whilst simultaneously reducing system capacity as energy use is increased.

INTEGRATION Framework for Modeling Eco-routing Strategies: Logic and Preliminary Results

Abstract: The paper presents the INTEGRATION microscopic traffic assignment and simulation framework for modeling eco-routing strategies. Two eco-routing algorithms are developed: one based on vehicle sub-populations (ECO-Subpopulation Feedback Assignment or ECO-SFA) and another based on individual agents (ECO-Agent Feedback Assignment or ECO-AFA). Both approaches initially assign vehicles based on fuel consumption levels for travel at the facility free-flow speed. Subsequently, fuel consumption estimates are refined based on experiences of other vehicles within the same class. The proposed framework is intended to evaluate the network-wide impacts of eco-routing strategies. This stochastic, multi-class, dynamic traffic assignment framework was demonstrated to work for two scenarios. Savings in fuel consumption levels in the range of 15 percent were observed and potential implementation challenges were identified.