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    <copyright>Copyright © 2026. National Academy of Sciences. All rights reserved.</copyright>
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    <managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor>
    <webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster>
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      <title>Online Competitive Algorithms and Reinforcement Learning for Traffic Management
</title>
      <link>https://rip.trb.org/View/2422816</link>
      <description><![CDATA[The management of traffic at intersections, both regulated and unregulated, has significant
impact on delays experienced. Traffic signal cycle times in urban centers are generally quite long leading to inefficiencies in traffic flow and increased environmental impact. Traffic flow coordination relies on partially outdated technology, which is rigid and not based in contemporary algorithmic models. As an example, a number of papers show that the well-known Webster formula, now almost 70 years old and widely used to estimate the minimum delay optimal traffic signal cycle length, indeed overestimates the cycle length for high degrees of traffic saturation – a degree of saturation now common in most urban areas. In the Las Vegas Valley the RTC follows an approach based in traditional transportation science, which tries to synchronize lights along corridors and which use long cycle length, i.e. when a car encounters a red light the wait can substantial. The study team proposes to
use computer science approaches, namely reinforcement learning and online competitive analysis to substantially improve the state of the art. In fact, as multi-modal traffic systems, ride-share systems and autonomous vehicles are becoming more prevalent vehicle traffic becomes more of a distributed system resembling internet traffic. With the use of deep learning techniques a system is envisioned that can analyze the large trove of data now available. The system will mine for systemic inefficiencies, and then give algorithmic solutions to eliminate such inefficiencies. When vehicles accumulate at an intersection this sequence of vehicles forms a platoon. Vehicles in a platoon all experience the same
stopped delay and are subject to the deceleration and acceleration delay at that intersection. The situation is similar to an area of research called “batch scheduling” and the proposer proposes to study the problem of delays in the framework of batching. Batching problems, both offline as well of online have been studied extensively (including by the proposer, see yet, to the proposers’ knowledge a connection has not been made in this area.]]></description>
      <pubDate>Tue, 27 Aug 2024 17:42:16 GMT</pubDate>
      <guid>https://rip.trb.org/View/2422816</guid>
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      <title>Transportation Needs and Economic Opportunities for Service Employees of
Socioeconomically Disadvantaged Populations in Las Vegas Hospitality and Tourism Industry
</title>
      <link>https://rip.trb.org/View/2422811</link>
      <description><![CDATA[The study team will continue and expand efforts initiated a few months ago (Year 1 of this PSR grant)
to examine transportation needs and challenges faced by service employees, especially those from
socio-economically disadvantaged (SED) populations. These individuals work at hotels along the
Las Vegas resort corridor (the Strip). The team aims to identify potential opportunities to address
these needs and challenges. In the first year, key deliverables were to develop and initiate an
assessment instrument, solicit local stakeholder input, and obtain UNLV IRB approvals. Progress
to date include developing the assessment instrument and its review by subject matter experts.
However, due to unanticipated delays to obtain stakeholder input, there has been a delay to
administer the survey. The team anticipates completing administering the survey in the next few
months. The team will then conduct focus group interviews in year 2. Thus, in the second year of
this study, main deliverables will be to complete evaluating the survey responses / data, conduct
focus group interviews and analyze the results, and make recommendations for effective, efficient,
and equitable solutions that address critical transportation commute needs of members of the
workforce in the service economy who come from diverse and SED populations. The study team
will document work related commute needs, experiences, and challenges faced by SED employees.
Key topics of interest include availability of alternative transportation modes, access to places of
employment, total travel times, and implications for employees’ balance between work responsibilities and personal lives, as well as their psychological well-being. Other items of interest include
how the adoption and use of innovative technologies can alleviate key challenges associated with
employees’ commutes. The study will attempt to explore incentives, policies and operational
strategies to help address the transportation challenges and needs identified. The study team will
collaborate with organizations such as the Regional Transportation Commission of Southern
Nevada, Culinary Workers Union and property owners and employees in the resort corridor.
Transportation Needs and Economic Opportunities for Service Employees of
Socioeconomically Disadvantaged Populations in Las Vegas Hospitality
and Tourism Industry.
The following are potential outcomes of this study. (1) Provide a template for a survey instrument
for potential use in similar efforts across the PSR UTC consortium, and beyond. (2) By identifying
the scope and magnitude of work-commute issues, the study will help identify transport access and
mobility challenges that SED populations and underserved community members in the greater
Las Vegas area experience. (3) Provide empirical evidence to support policy changes that advance
the equity and inclusion issues in the service industry. (4) Set the foundation for an externally funded
and more comprehensive study with the goal of making transportation needs of the community
future-proof]]></description>
      <pubDate>Tue, 27 Aug 2024 17:07:47 GMT</pubDate>
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