A human-in-the-loop wireless warning message notification model and its application in connected vehicle systems

ABSTRACT Objective: Vehicle-to-vehicle (V2V) communication has become one of the most active fields of research recently. The implementation of the wireless connected vehicles has widely extended the transmission range of warning messages to inform drivers of hazards ahead. The present study addressed the human component with mathematical modeling of the human reaction time to warning messages in the connected vehicle systems (CVSs) with different confidence intervals (CIs). Methods: In the present study, human performance in warning responses is modeled by extending an existing mathematical model of human performance with the complexity level of tasks. The modeling of human performance with different levels of uncertainty is integrated to propose the warning message notification model in the CVS settings. The warning message notification models were proposed to model the CVSs parameters including maximum available message notification delay, the maximum available machine processing time, the minimum acceptable message notification range, and the designed message display delay. Results: The optimal designs of CVSs parameters were presented in general and for specific conditions by applying the modeling of human performance with different CIs (i.e., 95% and 99% CI) and the warning message notification model with human in the loop. A software interface with the message notification model implemented was presented to discuss the practical benefits of the current work in the design of CVSs.

[1]  Baher Abdulhai,et al.  Assessing the Potential Impacts of Connected Vehicles: Mobility, Environmental, and Safety Perspectives , 2016, J. Intell. Transp. Syst..

[2]  Bart De Schutter,et al.  IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS Editor-In-Chief , 2005 .

[3]  J Lockhart,et al.  The effects of practice with MP3 players on driving performance. , 2008, Accident; analysis and prevention.

[4]  Y I Noy,et al.  Human factors in modern traffic systems. , 1997, Ergonomics.

[5]  Elsevier Sdol Transportation Research Part F: Traffic Psychology and Behaviour , 2009 .

[6]  Christoph F. Mecklenbräuker,et al.  Performance evaluation of IEEE 802.11p infrastructure-to-vehicle tunnel measurements , 2011, 2011 7th International Wireless Communications and Mobile Computing Conference.

[7]  Yili Liu,et al.  Integration of Physical and Cognitive Human Models to Simulate Driving With a Secondary In-Vehicle Task , 2012, IEEE Transactions on Intelligent Transportation Systems.

[8]  Pourang Irani,et al.  Effect of Auditory Road Safety Alerts on Brake Response Times of Younger and Older Male Drivers , 2008 .

[9]  Subir Biswas,et al.  Vehicle-to-vehicle wireless communication protocols for enhancing highway traffic safety , 2006, IEEE Communications Magazine.

[10]  Jun Luo,et al.  A Survey of Inter-Vehicle Communication , 2004 .

[11]  Yili Liu,et al.  Modeling the Influences of Cyclic Top-Down and Bottom-Up Processes for Reinforcement Learning in Eye Movements , 2009, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[12]  Panagiotis Papadimitratos,et al.  Vehicular communication systems: Enabling technologies, applications, and future outlook on intelligent transportation , 2009, IEEE Communications Magazine.

[13]  Yili Liu,et al.  Queuing Network Modeling of a Real-Time Psychophysiological Index of Mental Workload—P300 in Event-Related Potential (ERP) , 2008, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[14]  John Richardson,et al.  The effect of alarm timing on driver behaviour: an investigation of differences in driver trust and response to alarms according to alarm timing , 2004 .

[15]  Changxu Wu,et al.  Mathematical Modeling of Driver Speed Control With Individual Differences , 2013, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

[16]  Sidi-Mohammed Senouci,et al.  Experimental Assessment of V2V and I2V Communications , 2007, 2007 IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems.

[17]  Luzheng Bi,et al.  Inferring driver intentions using a driver model based on queuing network , 2013, 2013 IEEE Intelligent Vehicles Symposium (IV).

[18]  Girma S. Tewolde Sensor and network technology for intelligent transportation systems , 2012, 2012 IEEE International Conference on Electro/Information Technology.

[19]  Changxu Wu,et al.  Queuing Network Modeling of a Real-Time Psychophysiological Index of Mental Workload—P300 Amplitude in Event-Related Potential (ERP) , 2006 .

[20]  S. Roy,et al.  V2V Wireless Communication Protocol for Rear-End Collision Avoidance on Highways , 2008, ICC Workshops - 2008 IEEE International Conference on Communications Workshops.

[21]  Ji-Liang Doong,et al.  Driving performance assessment: effects of traffic accident location and alarm content. , 2008, Accident; analysis and prevention.

[22]  Dot Hs,et al.  Crash Warning System Interfaces: Human Factors Insights and Lessons Learned , 2007 .

[23]  Jinde Cao,et al.  Introduction to Computational Neuroscience , 2016 .

[24]  Farouk Kamoun,et al.  Cooperative infrastructure discovery through V2X communication , 2010, 2010 The 9th IFIP Annual Mediterranean Ad Hoc Networking Workshop (Med-Hoc-Net).

[25]  Changxu Wu,et al.  Optimization in Brain? - Modeling Human Behavior and Brain Activation Patterns with Queuing Network and Reinforcement Learning Algorithms , 2010 .

[26]  Biplab Sikdar A Broadcasting Scheme for Infrastructure to Vehicle Communications , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[27]  Marco Dozza,et al.  What factors influence drivers' response time for evasive maneuvers in real traffic? , 2013, Accident; analysis and prevention.

[28]  Yili Liu,et al.  Queuing network modeling of the psychological refractory period (PRP). , 2008, Psychological review.

[29]  Jin Cao,et al.  The effects of on-street parking on the service rate of nearby intersections , 2016 .

[30]  Yi-Li Liu,et al.  Modeling driver car-following based on the queuing network cognitive architecture , 2009, 2009 International Conference on Machine Learning and Cybernetics.

[31]  Chunming Qiao,et al.  A Mathematical Model for the Prediction of Speeding with its Validation , 2013, IEEE Transactions on Intelligent Transportation Systems.

[32]  Changxu Wu,et al.  Modeling the Effect of Loudness and Semantics of Speech Warnings on Human Performances , 2014 .

[33]  Haris N. Koutsopoulos,et al.  Evaluation of the effect of cooperative infrastructure-to-vehicle systems on driver behavior , 2012 .

[34]  Suzanne E. Lee,et al.  Investigation of Driver-Infrastructure and Driver-Vehicle Interfaces for an Intersection Violation Warning System , 2007, J. Intell. Transp. Syst..

[35]  Raja Sengupta,et al.  Vehicle-to-vehicle safety messaging in DSRC , 2004, VANET '04.

[36]  Changxu Wu,et al.  The Effect of Lead Time of Collision Warning Messages on Driver Performance , 2014 .

[37]  Zhaohui Wu,et al.  Intelligent Transportation Systems , 2006, IEEE Pervasive Computing.

[38]  Yili Liu,et al.  Queuing Network Modeling of Driver Lateral Control With or Without a Cognitive Distraction Task , 2012, IEEE Transactions on Intelligent Transportation Systems.

[39]  Joshua D. Hoffman,et al.  A Dynamic Programming Algorithm for Scheduling In-Vehicle Messages , 2008, IEEE Transactions on Intelligent Transportation Systems.

[40]  Theodore L. Willke,et al.  A survey of inter-vehicle communication protocols and their applications , 2009, IEEE Communications Surveys & Tutorials.

[41]  Ivan Stojmenovic,et al.  Reliable and Efficient Broadcasting in Vehicular Ad Hoc Networks , 2009, VTC Spring 2009 - IEEE 69th Vehicular Technology Conference.

[42]  Luca Delgrossi,et al.  IEEE 1609.4 DSRC multi-channel operations and its implications on vehicle safety communications , 2009, 2009 IEEE Vehicular Networking Conference (VNC).

[43]  Katsuya Matsunaga,et al.  Differences of drivers' reaction times according to age and mental workload. , 2008, Accident; analysis and prevention.

[44]  Arthur F. Kramer,et al.  Influence of Age and Proximity Warning Devices on Collision Avoidance in Simulated Driving , 2007, Hum. Factors.

[45]  Jessica Edquist,et al.  The effects of on-street parking and road environment visual complexity on travel speed and reaction time. , 2012, Accident; analysis and prevention.

[46]  Lucia Lo Bello,et al.  Automotive communications-past, current and future , 2005, 2005 IEEE Conference on Emerging Technologies and Factory Automation.

[47]  Paolo Santi,et al.  Vehicle-to-Vehicle Communication: Fair Transmit Power Control for Safety-Critical Information , 2009, IEEE Transactions on Vehicular Technology.

[48]  Christopher D. Wickens,et al.  Examining the Impact of Cell Phone Conversations on Driving Using Meta-Analytic Techniques , 2006, Hum. Factors.

[49]  Yili Liu,et al.  Using Queuing Network and Logistic Regression to Model Driving with a Visual Distraction Task , 2014, Int. J. Hum. Comput. Interact..

[50]  Yili Liu,et al.  Queueing Network-Model Human Processor (QN-MHP): A computational architecture for multitask performance in human-machine systems , 2006, TCHI.

[51]  Daniel Aguayo,et al.  Architecture and Evaluation of an , 2007 .

[52]  Hui Chen,et al.  Opportunistic Wireless Internet Access in Vehicular Environments Using Enhanced WAVE Devices , 2007, Future Generation Communication and Networking (FGCN 2007).

[53]  N. Challa,et al.  Adaptive Multicasting using Common Spreading Codes in Infrastructure-to-Vehicle Communication Networks , 2007, 2007 Mobile Networking for Vehicular Environments.

[54]  John D. Lee,et al.  Preface to the Special Section on Driver Distraction , 2004, Hum. Factors.

[55]  Antonio F. Gómez-Skarmeta,et al.  Architecture and evaluation of a unified V2V and V2I communication system based on cellular networks , 2008, Comput. Commun..

[56]  Douglas C. Schmidt,et al.  WreckWatch: Automatic Traffic Accident Detection and Notification with Smartphones , 2011, Mob. Networks Appl..

[57]  Hirozumi Yamaguchi,et al.  Cooperative Vehicle Positioning via V2V Communications and Onboard Sensors , 2011, 2011 IEEE Vehicular Technology Conference (VTC Fall).