Starting from the market-ready self-driving shuttle (SDS) with electric propulsion, as well as demand from public sector stakeholders, private sector stakeholders, and end-users, this project aims at enabling faster utilization and diffusion, as well as generating integrated, scalable, and replicable innovation opportunities for the district and city-level mobility. The proposed technological transition relies on a concept of self-driving vehicle areas, integrating SDS into wider built environment infrastructure, policies, and services. Recognizing the complexity of interdependent factors required for technological transition in urban environments, the expected achievements include 1) assessment of end user requirements, 2) assessment of barriers and facilitators, 3) assessment of gatekeepers and leaders, including potential for establishing public-private ecosystem, and 4) advancement of planning support for transition management. The agile development and open innovation approach, relying on several methods (e.g., workshop, interview, online participation forum), and centred on a case study, enables coordination with several ongoing projects, and interaction with both end-users and experts. Expected systemic change in mobility should result in reduction in GHG emissions, and improvement in adaptation mechanisms, such as safety, fragmentation of land use, infrastructural resiliency, and energy security.
In Finnish urban regions, integrated land use, housing, transport, services and economic development (MALPE) has become a new practice to encompass key planning sectors, in cooperation between the state and municipalities. Progressing upon this framework, the project funded byt the Academy of Finland Strategic Research Council aims at: 1) comprehending Finnish urbanization processes and agglomeration dynamics in an international comparative context, and their implications to sustainability, functionality and economic livelihood; 2) gaining analytical insight of ambiguities in political agency formation, knowledge management and policy-making in the current MALPE work; and 3) providing normative solutions for coping with these processes and ambiguities. With insights gained from the above, the project aims at 4) incorporating qualitatively new knowledge in the co-coordination of policy sectors and scales, and 5) generating, in a co-creative fashion, policy and planning recommendations for the Finnish city regions involved in the MALPE work.
The project aims to improve planning for the emerging technology of self-driving vehicles. As this emerging technology is in its foundational development stage, there is a need to rethink the planning practice to include a range of societal advantages and disadvantages. This interdisciplinary project merges theoretical frameworks from transportation planning, planning theory, technology transitions, and Science and Technology Studies. The research will focus on a technological transition in Finland, and directly relate to the European transport planning framework, Sustainable Urban Mobility Plan. The project collaborates with the research groups from University of Otago, New Zealand, University of Sussex, UK, University of California, Irvine, and Indiana University, Bloomington, USA.
Growing cities face the challenge of organizing efficient and sustainable urban transport, which is the key for reducing CO2 emissions and energy consumption. This project funded by the Academy of Finland will collect and curate open data on public transport networks from a wide range of cities, and release this data as an open access repository. All collected data will be analyzed using network-theoretical methods to uncover common features that make systems efficient, resilient, and attractive in terms of travel time and cost. Moreover, the acquired understanding will be packaged as a set of decision-support tools for improving public transport planning and operation. Ultimately, this project will advance computer science and transport engineering knowledgebase, and help the development of new transport services and applications.
This research is trying to develop an intersection control principle for self-driving vehicles, within the framework of social justice. This principle will succeed in protecting fundamental human rights better than a conventional intersection control principle. Besides the development of control framework, the objective of this research includes development of intersection simulation model using agent-based modelling and reinforcement learning, evaluation of system performance and robustness, along with the empirical information on human decision-making within the developed framework. By reaching across several disciplinary dimensions, this framework provides the promise and the challenge for evolving self-driving vehicle control. Finally, the ultimate intention is initiating a discussion on the objectives and parameters for developing a sustainable future transportation systems, with a self-driving vehicle as its central element.
Some thoughts related to this research can be read here.
This research will collect and analyze data on the student’s preconceptions related to transportation engineering. Considering that student’s preconceptions might help or hinder learning during the transportation engineering course, this study will investigate how preconceptions might affect students’ learning, how can they be used for curriculum design, and how are they modified by knowledge gained during the course.
This research will evaluate and provide guidance related to control solutions that address safety issues related to dilemma zone problems. The solutions will include optimal and proper design of advanced detectors, use of advanced controller features, advanced controller algorithms (Detection-Control System [D-CS], Platoon Identification and Accommodation [PIA], etc.), and other potential advanced solutions. Potential benefits of this research include better safety at high-speed isolated intersections. Guidelines from the research could change signal design and operation practice in Virginia.
This research has provided recommendations for Virginia Department of Transportation for installation and operation of Advanced Warning Flashers (i.e. Flashing Beacons). The recommendations were provided based upon the operating principles, existing state practices across United States and Canada, and examination of advanced systems developed by research organizations. This research identified potential for developing advanced controller features, which could expand operational flexibility in resolving dilemma zone issues with Advanced Warning Flashers.
This research focused on studying functional requirements, advanced traffic signal system control features, retrofitting feasibilities, potential benefits of next-generation control system. In addition, this research focused on the development of new algorithms for traffic responsive plan selection (TRPS) systems based on VII data to optimize traffic operations along a signalized corridor in a closed-loop system. VII data was used to substitute existing system detectors for determining the prevailing traffic conditions.
This research was performed for the Virginia Department of Transportation’s (VDOT's) Northern Regional Operations (NRO). NRO operates and maintains more than half the traffic signals under VDOT's purview, which represents a significant investment and is a critical component of NRO’s operations infrastructure. Given the age of the system’s infrastructure, the need exists to fully define its limitations under growing traffic demands and to determine when or if the system should be replaced or updated. Phase I of this project resulted in the development of the functional requirements of traffic signal control systems in NRO, and an identification of the gap between these functional requirements and the existing traffic signal system capabilities. Phase I also performed the evaluation of the market controllers. Phase II of the project resulted in the development of a framework for the development of geospatial migration plans for traffic signal system hardware and software, both in NRO and statewide.
This project focused on the design of Traffic Management System (TMS) for the City of Belgrade. This large-scale development included both road traffic and transit control centers. Project developed TMS using FRAME architecture, identified specific macro and micro traffic management measures, systems, equipment, and interfaces, requirements to operation and organization, and implementation schedule.
This project focused on assessing and analyzing Level of Service for public transit system in the City of Belgrade. The focus was on the bus and tramway sub-systems. The assessment consisted of both vehicle schedule and time interval data, and surveyed user’s opinions.
This project focused on analyzing pedestrian Level of Service in the pedestrian area located in the center of Belgrade. Analysis was performed for both pedestrian walkways and signalized crossings.