A binary decision model for discretionary lane changing move based on fuzzy inference system

Chen

Journal of Advanced Transportation

et al. 2018

The objective of this study is to investigate lane-changing characteristics in freeway off-ramp areas using Shanghai Naturalistic Driving Study (SH-NDS) data, considering a four-lane freeway stretch in various traffic conditions. In SH-NDS, the behavior of drivers is observed unobtrusively in a natural setting for a long period of time. We identified 433 lane-changing events with valid time series data from the whole dataset. Based on the logit model developed to analyze the choice of target lanes, a likelihood analysis of lane-changing behavior was graphed with respect to three traffic conditions: free flow, medium flow, and heavy flow. The results suggested that lane-changing behavior of exiting vehicles is the consequence of the balance between route plan (mandatory incentive) and expectation to improve driving condition (discretionary incentive). In higher traffic density, the latter seems to play a significant role. Furthermore, we found that lane-change from the slow lane to the fast lane would lead to higher speed variance value, which indicates a higher crash risk. The findings contribute to a better understanding on drivers' natural driving behavior in freeway off-ramp areas and can provide important insight into road network design and safety management strategies.

Section: Introductionmentioning

confidence: 99%

Modeling Lane-Changing Behavior in Freeway Off-Ramp Areas from the Shanghai Naturalistic Driving Study

Chen

Journal of Advanced Transportation

et al. 2018

2019 International Conference on Robotics and Automation (ICRA)

“…Lane change prediction, being a fundamental building block for any autonomous driving task, is a hot topic in research and has been investigated for several years [6], [7], [8], [9], [10]. Picking the most informative features according to a criterion and then using "classical" methods, like SVMs or Random Forests [2], [3], [11], [12] contributed to the core of research in lane change prediction.…”

Section: Related Workmentioning

confidence: 99%

Attention-based Lane Change Prediction

Scheel

Nagaraja

Schwarz

et al. 2019

Lane change prediction of surrounding vehicles is a key building block of path planning. The focus has been on increasing the accuracy of prediction by posing it purely as a function estimation problem at the cost of model understandability. However, the efficacy of any lane change prediction model can be improved when both corner and failure cases are humanly understandable. We propose an attentionbased recurrent model to tackle both understandability and prediction quality. We also propose metrics which reflect the discomfort felt by the driver. We show encouraging results on a publicly available dataset and proprietary fleet data.

Intell Sys Acc Fin Mgmt

“…These fuzzy if–then rules are employed by the FIS to define a mapping from fuzzy sets in the input universe of discourse Un ⊂ R n to fuzzy sets in the output universe of discourse V ⊂ R , based on fuzzy logic principles. The fuzzy if–then rules are presented in the following (Balal, Cheu, & Sarkodie‐Gyan, :

R^{(1)} : IF x_{1} is F_{1}^{l} and \dots X_{n} is F_{n}^{l}; THEN y is G^{l}

where

F_{i}^{l}

and G l are fuzzy sets in Un ⊂ R n respectively, and x = ( x 1 , x 2 , …, x n ), T ∈ U and y ∈ V are input and output linguistic variables of the FIS which belong to the input and output universes respectively. Let M be the number of rules in the fuzzy rule base ( l = 1, 2, …, M in equation ).…”

Section: Fuzzy Inference Systemmentioning

confidence: 99%

Hybrid performance evaluation of sustainable service and manufacturing supply chain management: An integrated approach of fuzzy dematel and fuzzy inference system

Pourjavad

Shahin

2018

The aim of this paper is to propose a comprehensive framework for simultaneously measuring the performance of sustainable service and manufacturing supply chain management. Application of the proposed approach also results in reduced uncertainty of the performance measurement process caused by qualitative criteria evaluation. The proposed approach consists of two main steps. First, the fuzzy decision-making trial and evaluation laboratory (DEMATEL) method has been used to determine important criteria by avoiding low influences; and then a Mamdani fuzzy inference system model has been adopted and applied for performance evaluation of sustainable supply chain management (SSCM). This model is employed in order to cope with the vagueness that exists in the SSCM performance investigation due to the vagueness intrinsic in the evaluation of criteria. In the proposed model, human reasoning has been modelled with fuzzy inference rules and has been set in the system, which is an advantage compared with those models in which fuzzy set theory and multicriteria decision-making models are integrated. The proposed approach has been implemented in the pipe and fitting industry in order to highlight its application in real life. Sensitivity analysis has been carried out to determine the influence of service and manufacturing criteria on SSCM performance. The findings reveal that sustainable manufacturing criteria compared with sustainable service criteria have more effect on the performance of SSCM.