Research Papers

Safety, Mobility, and Environmental Impacts of Forward Collision Warning Algorithms on a Roadway Network

Version 1
Date added July 10, 2018
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Category 2018 CARSP XXVIII Victoria
Tags Research and Evaluation, Session 5B
Author/Auteur H. Tawfeek, El-Basyouny
Stream/Volet Research and Evaluation

Slidedeck Presentation Only (no paper submitted)

5B - Tawfeek - Safety, Mobility...

Abstract

Rear-end collisions represent a quarter to one-third of the total number of collisions occurring on North American roads. Consequently, Forward Collision Warning (FCW) algorithms were developed to mitigate this type of critical collision by warning drivers about an impending rear-end event. The algorithms are typically tested to ensure their effectiveness in reducing specific events such as rear-end conflicts and/or collisions or by assessing the change in the frequency and severity of braking maneuvers. Such assessments are usually microscopic in nature and deal with isolated (independent) situations. This paper aims at assessing six FCW algorithms at a network level with varying market penetration rates using a calibrated microsimulation model. A main freeway segment in Edmonton, Alberta was selected to test the algorithms and assess their performance within a microsimulation model. VISSIM was used as a microscopic simulation software package. The comparison framework started by including the FCW algorithm using VISSIM's external driver model. The market penetration rate was increased from 25-to-100% by increments of 25% to represent the introduction and saturation of FCW technologies overtime. Ten multi-runs were executed for each market penetration level. The Measures of Effectiveness (MOEs) were computed based on outputs from the VISSIM simulation. The following MOEs were selected; rear-end conflicts, travel time, and emissions/fuel consumption for measuring the impacts of safety, mobility, and environment, respectively. For safety, the number of rear-end conflicts was obtained by exporting the vehicles trajectories from VISSIM and inputting them into the Surrogate Safety Assessment Model (SSAM) for analysis. For mobility and environment, the travel time and emissions/fuel consumption were directly obtained from VISSIM. The results showed that Algorithm 3 provided inconsistent results when compared to the other algorithms at various market penetration rates. On the other hand, Algorithm 4 provided better results in terms of safety and mobility at 50% and 75% market penetration rates, however, the differences between the results of all algorithms, except Algorithm 3, were not statistically significant. In addition, Algorithm 2 was superior under low market penetration rates (i.e. 25%) for all MOEs. At the highest market penetration rate (i.e. 100%), Algorithm 1 performed better in terms of mobility and environmental impacts, although, Algorithm 2 had better results in terms of safety. Most of the FCW algorithms did not have a significant effect on mobility nor environmental impacts at various market penetration rates. On the contrary, all the algorithms showed significant safety improvements, in terms of reducing rear-end conflicts, as the market penetration rates increased. The only exception was a single algorithm (i.e. Algorithm 3) which tends to be more conservative in terms of braking distance. The results showed that situational improvements (on a driver level) caused by using FCW systems will generally translate into systematic improvements (on a network level). This is important due to the anticipated gradual increase in intelligent vehicles, which are expected to be equipped with FCW systems, on our roads in the near future.