Day-to-day evolution of network flows under real-time information and reactive signal control

Ta Yin Hu, Hani S. Mahmassani

Research output: Contribution to journalArticlepeer-review

129 Citations (Scopus)


A day-to-day dynamic framework, in which the DYnamic Network Assignment Simulation Model for Advanced Road Telematics (DYNASMART) simulation-assignment model is applied to evaluate the performance of traffic networks, is developed to study network dynamics under real-time information and responsive signal control systems. The focus in this paper is primarily on commuter trips from home to work in a general network. Two levels of tripmaker decision-making processes are incorporated: (1) day-to-day dynamics and (2) real-time dynamics. Day-to-day dynamics consider the choices of departure time and route according to indifference bands of tolerable 'schedule delay', defined as the difference between the user's actual and preferred arrival times, and are thus governed by tripmakers' daily learning processes. Real-time dynamics consider en-route switching decisions in response to real-time information on prevailing traffic conditions. The resulting flows could be used in updating the supplied real-time information as well as the traffic control parameters. Two types of traffic control responsiveness are evaluated: (1) daily adjustment of signal timing parameters to reflect the preceding day's traffic patterns; and (2) real-time traffic-responsive signal control driven by prevailing flow patterns. The framework is illustrated through numerical experiments to investigate the day-to-day evolution of network flows under real-time information and responsive signal control, and assess the effectiveness of such information in a proper dynamic perspective.

Original languageEnglish
Pages (from-to)51-69
Number of pages19
JournalTransportation Research Part C: Emerging Technologies
Issue number1
Publication statusPublished - 1997 Feb

All Science Journal Classification (ASJC) codes

  • Civil and Structural Engineering
  • Automotive Engineering
  • Transportation
  • Computer Science Applications


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