Details:

Creators:
Zhang, Li ; Wen, Yi ; Wang, Feng ; Eksioglu, Sandra
Zhang, Li ; Wen, Yi ; Wang, Feng ; Eksioglu, Sandra Less -
Corporate Creators:
National Center for Intermodal Transportation
Subject/TRT Terms:
[+]
Adaptive Control Bus Priority Bus Transit Disasters And Emergency Operations Evacuation Microsimulation Routes And Routing Traffic Delay Traffic Signal Priority Travel Time Wireless Communication Systems
Resource Type:
Tech Report
Geographical Coverage:
United States
Corporate Publisher:
National Center for Intermodal Transportation
Abstract:
During an emergency evacuation, execution time is always critical to the evacuees who are

transit dependent. Transit Signal Priority (TSP) can speed up the transit services by prioritizing

the approaching bus at a signalized intersection. With the emergence of IntelliDrive (formerly

known as IVI), which is a wireless communication technology used to transfer data among

vehicles and infrastructures, a TSP system can obtain more accurate traffic data and react to

the approaching bus in a wider area. This report proposes an adaptive TSP system to facilitate

the transit-based emergency evacuation on the basis of the U.S. Department of Transportation

(DOT)’s IntelliDrive initiative.

The objective of this project is to study the TSP and IntelliDrive coordination and to evaluate

the impacts of the proposed TSP strategies on the transit-based emergency evacuation. The

emergency evacuation model consists of two optimization models: a TSP optimization model

and a bus routing optimization model. The TSP optimization model includes bus travel time

prediction and traffic signal optimization. The bus travel time prediction is used to estimate the

bus arrival time at the intersection. The traffic signal optimization considers both the bus delay

and the network-wide vehicle delay. It determines when and which TSP strategy will be applied.

The principal inputs for the TSP optimization model are: bus speed, position, busload, queue

length, and traffic signal status. The bus routing optimization model is proposed to optimize the

transit vehicles allocation and routing. The Dijkstra Algorithm has been modified to find out the

shortest paths among the pickup points and the shelters in the network. Additionally, a hybrid

intelligence algorithm consisting of a Genetic Algorithm and a Hill Climbing Algorithm, which

was developed under the sponsorship of a previous project, has been applied to solve the

transit vehicle routing and allocation problem.


Format:
PDF
Collection(s):
US Transportation Collection University Transportation Centers
Main Document Checksum:
[+]
urn:sha256:d1b17517a1b9848f899fd30f47d3a8fe8bdd4ea8add399e6493de706d0b2878d
Download URL:
https://rosap.ntl.bts.gov/view/dot/28373/dot_28373_DS1.pdf
File Type:

Supporting Files

• No Additional Files

More +