Personal Mobility

Documents

Order by : Name | Date | Hits [ Descendent ]
  • Advancing Community Transportation Through Coordination Using ITS - Lessons Learned from Aiken

    The Mobility Services for All Americans (MSAA) initiative is a United States Department of Transportation’s (USDOT) Intelligent Transportation Systems (ITS) research initiative that aims to enhance the efficiency and quality of human service transportation utilizing ITS. Travel Management Coordination Centers (TMCC) demonstration is a major outcome of the MSAA initiative. ITS forms the basis of the TMCC system by enabling two essential functional features: 1) enhanced real-time traveler information capability, and 2) improved or enhanced operational coordination through advanced ITS fleet management tools. In 2008, the USDOT selected Aiken (South Carolina), Camden County (New Jersey), and Paducah (Kentucky) to develop and demonstrate the technological and institutional feasibility of a deployed TMCC and to assess its impacts. In 2010, Aiken and Paducah TMCCs became operational and began a new era of coordinated community transportation services. The Paducah KY TMCC received the 2010 Community Transportation System of the Year Award by the Community Transportation Association of America (CTAA). The process and approach that led to the ultimate success of these two TMCC demonstration projects suggests that while each TMCC design was significantly influenced by local unique operational needs and characteristics, certain foundational ITS capabilities, such as Computer-Aided Scheduling and Dispatching (CASD), are required by all. This paper documents real-world results from the Aiken deployment and confirms that human service transportation in general is an “under-challenged” area where ITS can make a major impact.

    U.S. DOT

    Noblis, Inc.

    Presented at the 18th World Congress on ITS, October 2011, Orlando, Florida

     

  • Mobile Accessible Pedestrian Signals (MAPS) For People Who are Blind

     

    People with vision impairment generally have difficulty crossing intersections due to lack of traffic information. The most difficult intersection crossing tasks for this population are locating the crosswalk, determining when to cross, and maintaining alignment to the crosswalk while crossing. Through our ongoing effort to develop a prototype Mobile Accessible Pedestrian Signal (MAPS) application for the blind and visually impaired, we interviewed ten blind and low-vision people to better understand the type of information they use at intersection crossings and identified information types that could assist them. With these survey results, a prototype MAPS is developed that provides signal and intersection geometry information to Smartphone users at signalized intersections. User interaction is via simple tactile input (single/double-tap) and Text-To-Speech (TTS) interface are used for feedback. In the future, intersections equipped with Dedicated Short Range Communications (DSRC) will advance the capabilities of MAPS to next level of mobility and safety applications for people with vision impairment. MAPS can take advantage of the low-latency capability of DSRC to coordinate cooperative communication among pedestrians (waiting at the crossing), traffic signal controllers, and approaching vehicles, thereby providing dynamic decision-making support to all travelers, not just the visually impaired.

    Minnesota Traffic Observatory

    Presented at the 18th World Congress on ITS, October 2011, Orlando, Florida

     

  • Deriving Transportation Mode Shares on Urban Freeways Based on Mobile Phone Data

    An innovative method is presented in this paper to derive the transportation mode shares on

    urban freeways using mobile-phone trajectory information. It consists of two major parts:

    offline learning and online inference. The offline learning first extracts the temporal feature

    from the mobile-phone trajectories. By comparing to the existed link volumes, the inference

    parameters are calibrated through the offline learning process. The online inference determines

    the transportation modes for each individual mobile phone users in a real-time manner. The

    methodology was tested via a case study designed for both the offline learning and online

    inference parts. The results show the great potential of using mobile-phone trajectory

    information as a means to estimating the transportation mode shares.

    University of Wisconsin-Madison

    Southeast University

    South Dakota State University

    Presented at the 18th World Congress on ITS, October 2011, Orlando, Florida

     

  • Page 40 of 40
    About Us | Membership | Advocacy | Councils | Forums | News | Calendar of Events
    © Intelligent Transportation Society of America
    1100 17th Street NW, Suite 1200  Washington, DC 20036
    1-800-374-8472 or 202-484-4847  Email: info@itsa.org