|Title||Mobility Towers: Improving transportation efficiency measures by persistent evaluation of city-wide travel behavior|
|Publication Type||Conference Paper|
|Year of Publication||2013|
|Authors||Laura Schewel, Anand R Gopal, Amol A Phadke|
|Conference Name||ECEEE 2013 Summer Study|
|Conference Location||Belambra Les Criques, France|
|Keywords||information and communication technologies, transport policies and measures, Transportation Data, urban planning, urban transport|
Transportation from personal vehicles is the primary source of urban air pollution worldwide and is one of the fastest growing sources of greenhouse gas emissions (Metz et al. 2007). Coordinated deployment of Avoid-Shift-Improve policies to reduce personal vehicle usage (measured in vehicle kilometres travelled or VKT) is essential to mitigate the worsening impact of these emissions. In this paper, we describe an innovative, longitudinal method to measure key transportation behavioural metrics over time, and thus evaluate the impact of efficiency measures that aim to reduce VKT in cities. Urban planners seeking to implement new transport measures and infrastructure (roads, public transportation, bike lanes, etc.) find it difficult to quantify the ex-ante and ex-post effectiveness of such measures. In the Global South, policy makers frequently cannot measure the baseline, much less measure change. In this paper, we will show how analyzing archival (day old to years old) records from cellular tower networks that include robust safeguards for personal information, may allow measurement of key transportation metrics in a manner that can be updated constantly with low marginal cost. Thus, this method can allow quantification of the effectiveness of urban transport efficiency measures. Much of the existing literature describes progress in utilization of mobile devices for transportation data collection depending on more extensive supporting geospatial data. Our approach, which does not require such supporting data, has important implications for cities in the Global South. We propose that our cellular tower methodology is even more useful in such cities due to three factors: (1) these cities lack even basic data on the mobility behaviour of its residents, many of which can be calculated at reasonable accuracy with cellular data alone, (2) transportation behaviour is changing more rapidly, requiring more frequent measurement, and (3) mobile telephony infrastructure is at par or frequently superior to that found in the Global North.