Are you an EPFL student looking for a semester project?
Work with us on data science and visualisation projects, and deploy your project as an app on top of Graph Search.
The use of Hard Shoulder Running (HSR) systems is a relatively recent control policy aiming to ameliorate traffic conditions in recurrent congested networks. This ITS strategy attracts researchers and practitioners interest, in an attempt to assess its impact on drivers’ behavior. The objective of this study is to analyze and optimize the operation of an HSR system from multiple perspectives: traffic, behavioral and economic. The analysis is performed at a freeway segment equipped with the aforementioned managed lane system between Lausanne and Geneva in Switzerland. Using traffic data collected from radar sensors, segmented/piecewise linear models are first developed to analyze free-flow or dense regimes and congested, followed by an estimation of short-term left-lane flow distribution ratio (LLFDR) models, aiming to provide timely hard shoulder activation. Ordered probit models are then specified using data collected by a road-side survey, to model the satisfaction of the freeway users about the HSR system. The results suggest that younger (4 times/week) of the particular road segment are the most satisfied. An economic analysis follows, identifying the benefits of the system. An economic evaluation of the managed lane system is then performed to assess the benefits –or costs– of the system since the beginning of its operation.
Nikolaos Geroliminis, Min Ru Wang
Friedhelm Christoph Hummel, Philipp Johannes Koch
,