Geospatial Analytics to Improve the Safety of Autonomous Vehicles

Finding the costs and risks associated with highway traffic routes would allow companies and people alike to find routes that offer a comfortable amount of risk. With the amount of traffic data being collected at a more granular level the ability to find costs and risks associated with traffic routes given real time circumstances is plausible. Weighing these data and finding the areas that are most accident-prone allows for an assessment of the probability that an accident happens and what the cost of that accident would be for any given route. This information is very valuable for both safety and cost saving for drivers and insurance companies.

[1]  C.M.J. Tampere,et al.  Modelling traffic flows with intelligent cars and intelligent roads , 2003, IEEE IV2003 Intelligent Vehicles Symposium. Proceedings (Cat. No.03TH8683).

[2]  T. Golob,et al.  Relationships Among Urban Freeway Accidents, Traffic Flow, Weather and Lighting Conditions , 2001 .

[3]  Tibebe Beshah,et al.  Mining Road Traffic Accident Data to Improve Safety: Role of Road-Related Factors on Accident Severity in Ethiopia , 2010, AAAI Spring Symposium: Artificial Intelligence for Development.

[4]  Sachin Tripathi,et al.  Network condition and application adaptive fitness based vehicular intelligent routing protocol , 2016, 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI).

[5]  Kaarin J Anstey,et al.  Ability perceptions, perceived control, and risk avoidance among male and female older drivers. , 2008, The journals of gerontology. Series B, Psychological sciences and social sciences.

[6]  Amin A. Shaqrah.  Future of Smart Cities in the Knowledge-based Urban Development and the Role of Award Competitions , 2016, Int. J. Knowl. Based Organ..

[7]  James G. Shanahan,et al.  Large Scale Distributed Data Science using Apache Spark , 2015, KDD.

[8]  S.P. Hoogendoorn,et al.  ADAS safety impacts on rural and urban highways , 2004, IEEE Intelligent Vehicles Symposium, 2004.

[9]  Pierre Héroux,et al.  Precise Point Positioning Using IGS Orbit and Clock Products , 2001, GPS Solutions.

[10]  Salvatore Cafiso,et al.  Safety Index for Evaluation of Two-Lane Rural Highways , 2007 .

[11]  M. Keith Wright,et al.  Towards a New Model for Causal Reasoning in Expert Systems , 2017, Int. J. Knowl. Based Organ..

[12]  J. C. Gerdes,et al.  Implementable Ethics for Autonomous Vehicles , 2016 .

[13]  Wafaa Saleh,et al.  Modelling motorcyclist injury severity by various crash types at T-junctions in the UK , 2008 .

[14]  Scott Shenker,et al.  Spark: Cluster Computing with Working Sets , 2010, HotCloud.

[15]  Matías Gámez,et al.  adabag: An R Package for Classification with Boosting and Bagging , 2013 .

[16]  Bjoern H. Menze,et al.  A comparison of random forest and its Gini importance with standard chemometric methods for the feature selection and classification of spectral data , 2009, BMC Bioinformatics.

[17]  Maryam Allahyar,et al.  The Evolving Role of Automation in Transportation , 2016 .

[18]  Cheng Soon Ong,et al.  Multivariate spearman's ρ for aggregating ranks using copulas , 2016 .

[19]  Wei-Ying Ma,et al.  Understanding mobility based on GPS data , 2008, UbiComp.

[20]  Dharminder Kumar,et al.  A Hybrid Approach Using Maximum Entropy and Bayesian Learning for Detecting Delinquency in Financial Industry , 2016, Int. J. Knowl. Based Organ..

[21]  Joydeep Ghosh,et al.  Investigation of the random forest framework for classification of hyperspectral data , 2005, IEEE Transactions on Geoscience and Remote Sensing.

[22]  Robert P. Sheridan,et al.  Random Forest: A Classification and Regression Tool for Compound Classification and QSAR Modeling , 2003, J. Chem. Inf. Comput. Sci..

[23]  Mohamed Abdel-Aty,et al.  Predicting Injury Severity Levels in Traffic Crashes: A Modeling Comparison , 2004 .

[24]  Ameet Talwalkar,et al.  MLlib: Machine Learning in Apache Spark , 2015, J. Mach. Learn. Res..

[25]  In Lee,et al.  An Evolutionary Distributed Agent System: A Framework and Application to Manufacturing Design and Control , 2016, Int. J. Knowl. Based Organ..

[26]  Hadley Wickham,et al.  ggmap: Spatial Visualization with ggplot2 , 2013, R J..

[27]  K. Nachimuthu,et al.  GIS and simulation based road accident cost estimation , 2008, 2008 First International Conference on Infrastructure Systems and Services: Building Networks for a Brighter Future (INFRA).