Traffic and Speeding During The Pandemic – The Sound of Ideas – WCPN (Cleveland Public Radio)

On May 18th,I was a guest on the WCPN Cleveland Public Radio show the Sound of Ideas.  We talk about the evidence of increased speeding in Ohio during the COVID-19 pandemic, and more broadly about the current opportunity to rethink how we use street space in our cities:

WCPN (Cleveland) – The Sound of Ideas: Traffic and Speeding During The Pandemic

 

CURA report: Less traffic is leading to more speeding in Ohio’s major cities during the Coronavirus pandemic

The Center for Urban and Regional Analysis (CURA) released a report that compared traffic data for Ohio’s three major cities for March-April 2020 versus 2019.  Less traffic during the Coronavirus crisis is leading to more speeding, especially extreme speeding.

CURA research report: Evidence Of Increased Vehicle Speeding In Ohio’s Major Cities During The Coronavirus Pandemic

This report is featured in several news sources:

  1. Ohio State News
  2. WOSU Public Media
  3. The Columbus Dispatch
  4. Columbus Underground
  5. WEWS TV5 Cleveland

New publication: Jaegal, Y. and Miller, H.J. (2020) “Measuring the structural similarity of network time prisms using temporal signatures with graph indices,” Transactions in GIS, 24, 3-26.

Abstract. The network‐time prism (NTP) is an extension of the space‐time prism that provides a realistic model of the potential pattern of moving objects in transportation networks. Measuring the similarity among NTPs can be useful for clustering, aggregating, and querying potential mobility patterns. Despite its practical importance, however, there has been little attention given to similarity measures for NTPs. In this research, we develop and evaluate a methodology for measuring the structural similarity between NTPs using the temporal signature approach. The approach extracts the one‐dimensional temporal signature of a selected property of NTPs and applies existing path similarity measures to the signatures. Graph‐theoretic indices play an essential role in summarizing the structural properties of NTPs at each moment. Two extensive simulation experiments demonstrate the feasibility of the approach and compare the performance of graph indices for measuring NTP similarity. An empirical application using bike‐share system data shows that the method is useful for detecting different usage patterns of two heterogenous user groups.