Social Issues in Computational Transportation Science

NII Shonan Meeting:

@ Shonan Village Center, December 17-20, 2012

NII Shonan Meeting Report (ISSN 2186-7437):No.2012-12


  • Ouri Wolfson, The University of Illinois, USA
  • Monika Sester, Institut für Kartographie und Geoinformatik, Leibniz Universität Hannover, Germany
  • Stephan Winter, The University of Melbourne, Australia
  • Glenn Geers, NICTA, Australia
  • Masaaki Tanizaki, Hitachi, Ltd., Kyoto University, Japan

1. Overview

This application proposes a meeting bringing together researchers working in areas contributing to Computational Transportation Science (CTS). CTS is a new discipline that combines computer science and engineering with the modeling, planning, social, and economic aspects of transportation. The discipline studies how to improve the safety, mobility, and sustainability of the transportation system by taking advantage of information technologies and ubiquitous computing. In the proposed seminar we plan to focus on the social computing aspect of CTS.

Whilst CTS is an important research discipline, it is also of high importance for industry to support the development of Intelligent Transportation Systems with novel computational methods.

Given the broad impact of transportation and particularly the high relevance of social computing to mass crowds, the seminar is very suitable to be communicated to a broader audience.


In the seminar that is being proposed, we plan to focus on the direction of social computing. The choice of this focus was influenced by the many recent developments in social networks and crowdsourcing for transportation as well as the integration of persuasive technologies, behavioral economics in social computing. The researchers and practitioners from industry will review the development in this direction, discuss issues and solutions, and plan an edited book on CTS from the social computing perspective.

Furthermore, closer links to researchers and practitioners from ITS will be sought. In the following we provide more in-depth discussion of social computing in CTS.

Social computing and information processing taps into the wisdom of crowds, and relies on the (ubiquitous) connectedness and communication ability of the members forming the society. Provided such infrastructure, cooperation in terms of computing and information processing becomes feasible and forms new research questions.

While social computing is making its way into many disciplines, it is not obvious how real-time social interaction between mobile and stationary individuals (people, vehicles, goods, and infrastructure) can improve transportation. From a state where every individual is acting autonomously in isolation, or with minimal (visual) interaction with their environment, it is quite a paradigm shift to think of transportation as an interconnected, communicating and cooperating complex system.

Such a paradigm shift brings up research questions in multiple dimensions including, but not limited to:

1) Managing Competition and Collaboration among Travelers

Travelers in a traffic network often need to make decisions about activities such as routing and parking.

With the advent of location based services, wireless communication devices, and car navigation systems with real-time traffic, travelers now have the information to help them make these decisions. However, the models and tools needed to take advantage of this information are lacking.

For example, the route guidance methods that are used by car navigation systems are based on choosing a shortest path. But the shortest path could be sub-optimal if a large number of vehicles choose the same path, leading to a “herding” effect. This in turn will backfire, i.e. lead to a longer travel, because as the number of vehicles on a route increases, so will the travel time on the route. Similarly, a bus, a train, or an available parking slot that seem attractive to a traveler may become much less desirable if many travelers make the same choice. In other words, the pervasiveness of real-time travel information renders the existing tools inadequate, and the decision-making unsupported.

The inappropriateness of existing methods results from competition among travelers with real-time information. But the travelers also cooperate since much of the travel information is provided via some sort of crowd-sourcing, a phenomenon that should be encouraged and incentivized because it increases the efficiency of the overall system.

2) Crowd Sourcing

In a crowdsourcing system, services are provided by the users themselves rather than by a business or organization. The transportation information that may be crowdsourced includes real-time traffic information of road segments, information about car accidents and available parking slots, ride sharing opportunities, and so on. Crowdsourcing may be implemented using either the client/server model, or the peer-to-peer model, or a combination of the two. In the transportation environment, peers can be highly mobile and the peer-to-peer communication is subjected to disconnections when a short-range wireless technology is used. In this case, the peer-to-peer crowdsourcing introduces special challenges to incentive mechanisms. Many issues remain to be solved. The following are some of them.

– Transactional/atomicity issues in pricing schemes.

– Reputation management in non-pricing schemes.

– Game theoretic schemes.

– Additionally, exploiting social networks like Twitter of Facebook, where it is assumed that friends share trustworthy information, will be elaborated.

– Privacy issues

3) Behavioral Economics and Persuasive Technologies

Behavioral economics uses social, cognitive and emotional factors in understanding the economic decisions of individuals and institutions performing economic functions. Behavioral economics has made inroads in transportation in the areas of survey design, prospect theory, and attitudinal variables. Further infusion into transportation could lead to significant benefits in terms of increased ability to both predict and influence behavior. In this seminar we will discuss the transferability of findings in behavioral economics to transportation, with a focus on lessons regarding personalized information and social influences.

Persuasive technologies are technologies that change attitudes or behaviors of the users through persuasion, social influence, and social marketing. We will discuss the use of persuasive technologies for “green” transportation.

3. Objectives and Expected Results

This NII Shonan Meeting has three objectives:

1. Discovering Social Computing in CTS

2. Growing a community in CTS

3. Seeking interaction and collaboration with scientists and practitioners from ITS

First, and more visibly, it will go into depth in one of the core CTS research areas: Social computing.

Informal presentations of ongoing work in this area will inspire and help us to better shape and understand the bigger picture on social computing in CTS. We aim to develop ideas for a number of joint publications that cover this field and can be used to introduce in this field. Ideally we find a joint publication platform for an edited piece that may form the point of reference in the future.

Secondly, by cross-disciplinary discussions we hope to shape a community. We will develop strategic ideas to nurture CTS such that we might have a vibrant annual conference with hundreds of participants in the future.

Such a seminar is needed for shaping new cooperation, and providing space and time for coordination and inspiration, and NII Shonan’s infrastructure provides just the needed environment. The participants group will cover expertise in areas such as computer science, transportation engineering, behavioral economics, persuasive technologies, geographic information science, intelligent transportation systems, and computer graphics. Also researchers from industry will be invited providing applications and examples to the discussions.