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Smart Mobility Best Paper Awards

Nimrod Barshad

Nimrod Barshad

Painter, Sculptor, Conceptual Artist

Augue ut lectus arcu bibendum at varius vel pharetra vel. Vestibulum lorem sed risus ultricies. In curs turpis massa tincidunt dui ut ornare.

Nimrod Barshad
Sculptor, Conceptual Artist
+61986543210 /
Tankha Atska

Tankha Atska

Abstract Artist

Augue ut lectus arcu bibendum at varius vel pharetra vel. Vestibulum lorem sed risus ultricies. In curs turpis massa tincidunt dui ut ornare.

Tankha Atska
Abstract Artist
+61986543210 /
Nimrod Barshad

Nimrod Barshad

Painter, Sculptor, Conceptual Artist

Augue ut lectus arcu bibendum at varius vel pharetra vel. Vestibulum lorem sed risus ultricies. In curs turpis massa tincidunt dui ut ornare.

Nimrod Barshad
Painter, Conceptual Artist
+61986543210 /
Tommy Martinez

Tommy Martinez

Painter, Conceptual Artist

Augue ut lectus arcu bibendum at varius vel pharetra vel. Vestibulum lorem sed risus ultricies. In curs turpis massa tincidunt dui ut ornare.

Tommy Martinez
Painter, Conceptual Artist
+61986543210 /
Linda M. Dugan

Linda M. Dugan

Conceptual Artist

Augue ut lectus arcu bibendum at varius vel pharetra vel. Vestibulum lorem sed risus ultricies. In curs turpis massa tincidunt dui ut ornare.

Linda M. Dugan
Conceptual Artist
+61986543210 /
Henry Merparlo

Henry Merparlo

Painter, Sculptor

Augue ut lectus arcu bibendum at varius vel pharetra vel. Vestibulum lorem sed risus ultricies. In curs turpis massa tincidunt dui ut ornare.

Henry Merparlo
Painter, Sculptor
+61986543210 /

IEEE International Conference on Smart Mobility (SM’24) Best Paper Awards

Description:

These awards recognize the best paper in each of the three tracks of the conference (Smart Mobility Technology Best Paper, City Planning Best Paper and Smart Mobility Governance Best Paper).

Prize:

Certificates of recognition for individual authors of the winning paper in each track.

Eligibility:

All papers presented at IEEESM are eligible. There are no restrictions as to IEEE membership, organization, nationality, race, creed, sex, or age. Eligibility and Selection process shall comply with procedures and regulation established in IEEE and Society governing documents, particularly with IEEE Policy 4.4 on Awards Limitations.

Selection Process:

The Best Paper Award Committee is formed by selected members of the technical program committee of the conference, technical track chairs and the technical session chair(s). The award committee will determine the best paper. The chair of the committee is responsible for ensuring the selection process is fair and unbiased and that any possible conflicts of interests are handled appropriately. Papers are judged based on technical merit, originality, relevance to the smart mobility tracks, potential impact on the field, clarity of the written paper, and quality of the paper presentation and discussion during the session.

Evaluation Process:

The following 3-steps will be followed to select the best paper in each track.

  1. Each session chair(s) evaluates the presentation and discussion quality of the paper included in their session. The session chairs shall send their evaluations to the Best Paper Award Committee Chair.
  2. The papers are evaluated by the Best Paper Award Committee members according to their technical merit and originality. Papers will be then sorted based on the overall score. The overall score is the weighted sum of the technical quality score and the presentation score. Overall score=0.7*technical quality score+0.3*presentation quality score.
  3. The Best Paper Award Committee Chair reviews the summary of the overall evaluation scores received from the Award Committee and confirms the winning paper for each track.

Presentation:

The awards will be announced and presented during the closing ceremony of the conference.

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Panel Title: Engineering and Societal Adoption Challenges of Automated Driving Systems
IEEE International Conference on Smart Mobility (IEEESM)
IEEESM'23 Registration
Across the globe, there are tens of companies pursuing the development of automated driving systems (ADS), ranging over SAE Driving Automation Levels 3-5. There are several open engineering challenges of ADS software – particularly in development and validation of ADS operation in challenging weather conditions, critical corner cases, dealing with a variety of pedestrians and traffic conditions, and cooperation with human operated vehicles. Many standards (e.g., ISO 26262, ISO 21448) are emerging providing guidelines to ensure safety of ADS under the intended operating conditions. On the other hand, there are societal concerns that technological advancements such as ADS and robotics might bring in, e.g., people being out of work, competing with automation etc.. Initiatives like Partners for Automated Vehicle Education (PAVE) aim to alleviate such concerns by educating public and policymakers on pros and cons of automated driving systems. This panel discussion will focus on ADS engineering and societal adoption challenges and offer some possible solutions.
Ramesh S Senior Technical Fellow, General Motors, USA
Panel Moderator
Arun Adiththan Senior Researcher, General Motors, USA
Panel Moderator
Panel Description
Overlay Image
Panel Title: Engineering and Societal Adoption Challenges of Automated Driving Systems
IEEE International Conference on Smart Mobility (IEEESM)
IEEESM'23 Registration
Across the globe, there are tens of companies pursuing the development of automated driving systems (ADS), ranging over SAE Driving Automation Levels 3-5. There are several open engineering challenges of ADS software – particularly in development and validation of ADS operation in challenging weather conditions, critical corner cases, dealing with a variety of pedestrians and traffic conditions, and cooperation with human operated vehicles. Many standards (e.g., ISO 26262, ISO 21448) are emerging providing guidelines to ensure safety of ADS under the intended operating conditions. On the other hand, there are societal concerns that technological advancements such as ADS and robotics might bring in, e.g., people being out of work, competing with automation etc.. Initiatives like Partners for Automated Vehicle Education (PAVE) aim to alleviate such concerns by educating public and policymakers on pros and cons of automated driving systems. This panel discussion will focus on ADS engineering and societal adoption challenges and offer some possible solutions.
Ramesh S Senior Technical Fellow, General Motors, USA
Arun Adiththan Senior Researcher, General Motors, USA
Panel Moderator
Panel Description
Panel Moderator
Overlay Image