Uncertainty Estimation with Distributional Reinforcement Learning for Applications in Intelligent Transportation Systems: A Case Study

2019 ◽  
Author(s):  
Pengyue Wang ◽  
Yan Li ◽  
Shashi Shekhar ◽  
William F. Northrop
Keyword(s):  
Reinforcement Learning ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Uncertainty Estimation

Incorporating Intelligent Transportation Systems into Major Investment Studies: Conceptual Issues and Challenges

1998 ◽  
Vol 1651 (1) ◽  
pp. 8-16 ◽  
Author(s):  
S. Gregory Hatcher ◽  
James A. Bunch ◽  
Donald L. Roberts
Keyword(s):  
Intelligent Transportation Systems ◽  
Planning Process ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Problem Definition ◽  
Corridor Planning ◽  
Surface Transportation ◽  
Key Steps ◽  
Measures Of Effectiveness

The issues associated with incorporating intelligent transportation systems (ITS) strategies into alternatives analysis planning studies such as major investment studies (MIS), which have emerged since the Intermodal Surface Transportation Efficiency Act was passed in 1991, are discussed. The challenges and implications of including ITS in three of the key steps of the MIS process—problem definition, alternative definition, and analysis—are examined. As context for the specific issues addressed, a case study is presented on incorporating ITS into a corridor planning process that is being conducted using Seattle data. Critical to incorporating ITS elements within an MIS process is developing a problem statement, goals and objectives, and measures of effectiveness that are sensitive to ITS and other operational improvements for the corridor or subarea under study. Traditional MIS processes have focused on facility/service improvements and on average conditions and demand. ITS strategies, on the other hand, aim at improving ( a) operations; ( b) response to nonrecurrent conditions; and ( c) providing better information. To be able to address ITS strategies, the analysis approach used in an MIS should be sensitive to these issues. An illustration of how ITS strategies are being incorporated and evaluated in the Seattle (MIS-like) case study concludes the discussion.

Wireless Communication Alternatives for Intelligent Transportation Systems: A Case Study

2011 ◽  
Vol 15 (3) ◽  
pp. 147-160 ◽  
Author(s):  
Yan Zhou ◽  
Glenn Hamilton Evans ◽  
Mashrur Chowdhury ◽  
Kuang-Ching Wang ◽  
Ryan Fries
Keyword(s):  
Wireless Communication ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems

Effect of Environmental Factors on Driver Speed: A Case Study

1998 ◽  
Vol 1635 (1) ◽  
pp. 155-161 ◽  
Author(s):  
Wei Lien Liang ◽  
Michael Kyte ◽  
Fred Kitchener ◽  
Patrick Shannon
Keyword(s):  
Environmental Factors ◽  
Intelligent Transportation Systems ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Passenger Cars ◽  
Factors Affecting ◽  
Operational Test ◽  
Field Operational Test ◽  
Baseline Conditions

A case study on the effects of visibility and other environmental factors on driver speed was conducted as part of an intelligent transportation systems field operational test to reduce accidents caused by sudden changes in visibility levels. Baseline conditions established normal vehicle speeds for passenger cars and trucks. Reduced visibility and winds exceeding 40 km/h were found to be the primary factors affecting driver speed.

Costs and Benefits of Using Intelligent Transportation Systems as an Alternative Data Source: Case Study

2002 ◽  
Vol 1804 (1) ◽  
pp. 85-90
Author(s):  
Pat S. Hu ◽  
Richard T. Goeltz ◽  
Richard L. Schmoyer
Keyword(s):  
Intelligent Transportation Systems ◽  
Value Added ◽  
Intelligent Transportation ◽  
Transportation Systems ◽  
Traffic Data ◽  
Costs And Benefits ◽  
Data Resource ◽  
Address Data ◽  
Data Source

Intelligent transportation systems (ITSs) are an alternative data source that could lead to win–win situations: this source will not only benefit the transportation operations and planning communities by allowing them to access more and better data, but it will also enhance the appeal of ITS deployment by significantly broadening its originally intended benefits. Use of ITS-generated data as an alternative data resource is reflected in the archived data user services (ADUS) in the national ITS architecture. Usually, an agency will evaluate the costs and the benefits of ADUS before it decides whether to deploy ADUS. The costs and benefits of ADUS are examined on the basis of results from a case study in which ITS-generated traffic data were analyzed to determine whether they can help meet such traffic data needs as estimating the total travel volume and the total vehicle miles traveled. The cost is measured in terms of the effort needed to archive and reformat the data, revamp the software, and address data quality and data integration issues. The benefits are measured in terms of the value added by the ITS-generated data. Although the costs are high to use ITS-generated data for purposes other than the originally intended use, the research has proved that ITS-generated data can improve transportation decisions by, in this case, improving traffic estimates.

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