Traffic Signal Optimization

Government:

City of San José

Category:

Process Improvement, Data Analytics, Data Collection, Mobility, AI/ML, Public Safety

Budget:

Budget Exists

Procurement Method:

RFP
View doc

Application Period:

December 11, 2019

Through

February 7, 2020 3:59 PM

Q&A Period:

December 11, 2019 - January 17, 2020

Challenge

The City of San José Department of Transportation is seeking automated, cloud-based, and artificially intelligent solution to optimize traffic signal performance for all modes of transportation for our efficient management of the right of way for all users.

Background

An ongoing challenge for the Department of Transportation continues to be the maintenance associated with traffic signal intersection hardware.  Currently, comparative systems are highly manual and inefficient, due to the frequency of inputs and maintenance required.  In order to plan for the transportation system of the future, the Department of Transportation is interested in exploring the opportunity to leverage the cellular network to make traffic signals more adaptive for all modes. 

Requirements & Outcome

The Department of Transportation is seeking a solution that would have the following outcomes: 
  • Utilize an artificially intelligent software solution to optimize traffic signal performance for all modes of transportation leveraging cellular data 
  • Connect to 2070 controller running a version of CITY’s D4 software and send/receive NTCIP message sets 
  • Demonstrate controller optimization 
  • Connect to San Jose’s traffic network and learn about network performance 
  • Collect NTCIP Status Table message data and cellular data through existing City partnership and possibly additional data sources 
  • Use data to train algorithm 
  • Create Web Interface or Dashboard to demonstrate system performance, reporting and configuration 
  • Activate system by running optimization schemes 
  • Collect data for report including travel times, number of calls, and outcome 
  • Analyze data collected and make recommendations for system enhancements/expansion