Mobile Systems applied to Traffic Management and Safety: a state of the art

Abstract Mobile systems applied to traffic management and control and traffic safety have the potential to shape the future of road transportation. The following innovations, that will be deployed on a large scale, could reshape road traffic management practices: – the implementation of connected vehicles with global navigation satellite (GNSS) system receivers; – the autonomous car revolution; – the spreading of smartphone-based systems and the development of Mobile Cooperative Web 2.0 which is laying the base for future development of systems that will also incorporate connected and autonomous vehicles; – an increasing need for sustainability of transportation in terms of energy efficiency, traffic safety and environmental issues. This paper intends to provide a state of the art on current systems and an anticipation of how mobile systems applied to traffic management and safety could lead to a completely new transportation system in which safety and congestion issues are finally properly addressed.

[1]  Mehdi Ghatee,et al.  A context aware system for driving style evaluation by an ensemble learning on smartphone sensors data , 2018 .

[2]  Franco Davoli,et al.  Road traffic estimation from location tracking data in the mobile cellular network , 2000, 2000 IEEE Wireless Communications and Networking Conference. Conference Record (Cat. No.00TH8540).

[3]  D E Boyce,et al.  IN-VEHICLE NAVIGATION REQUIREMENTS FOR MONITORING LINK TRAVEL TIMES IN A DYNAMIC ROUTE GUIDANCE SYSTEM , 1991 .

[4]  Carlos Carmona,et al.  Travel Time Forecasting and Dynamic Origin-Destination Estimation for Freeways Based on Bluetooth Traffic Monitoring , 2010 .

[5]  Vittorio Astarita,et al.  A Mobile Application for Road Surface Quality Control: UNIquALroad , 2012 .

[6]  Giuseppe Guido,et al.  Estimation of Safety Performance Measures from Smartphone Sensors , 2012 .

[7]  Alexandre M. Bayen,et al.  Incorporation of Lagrangian measurements in freeway traffic state estimation , 2010 .

[8]  Jiaqi Ma,et al.  Field Evaluations of an Adaptive Traffic Signal—Using Private-Sector Probe Data , 2016 .

[9]  Helmut Hlavacs,et al.  The Cellular Network as a Sensor: From Mobile Phone Data to Real-Time Road Traffic Monitoring , 2015, IEEE Transactions on Intelligent Transportation Systems.

[10]  Peter Händel,et al.  Process Innovation with Disruptive Technology in Auto Insurance: Lessons Learned from a Smartphone-Based Insurance Telematics Initiative , 2015, BPM.

[11]  Isaac Skog,et al.  Indirect Instantaneous Car-Fuel Consumption Measurements , 2014, IEEE Transactions on Instrumentation and Measurement.

[12]  Isaac Skog,et al.  Smartphone-Based Measurement Systems for Road Vehicle Traffic Monitoring and Usage-Based Insurance , 2014, IEEE Systems Journal.

[13]  Keemin Sohn,et al.  Space-Based Passing Time Estimation on a Freeway Using Cell Phones as Traffic Probes , 2008, IEEE Transactions on Intelligent Transportation Systems.

[14]  Giuseppe Guido,et al.  Using Smartphones as a Tool to Capture Road Traffic Attributes , 2013 .

[15]  Hillel Bar-Gera,et al.  Evaluation of a Cellular Phone-Based System for Measurements of Traffic Speeds and Travel Times: A Case Study from Israel , 2007 .

[16]  Carlo Ratti,et al.  Real-Time Urban Monitoring Using Cell Phones: A Case Study in Rome , 2011, IEEE Transactions on Intelligent Transportation Systems.

[17]  Vincenzo Pasquale Giofrè,et al.  Driving Behavior and Traffic Safety: An Acceleration-Based Safety Evaluation Procedure for Smartphones , 2014 .

[18]  Mumbai,et al.  Internet of Things (IoT): A Literature Review , 2015 .

[19]  Isaac Skog,et al.  Smartphone-based Vehicle Telematics - A Ten-Year Anniversary , 2016, ArXiv.

[20]  Wai Chong Chia,et al.  A Smart Parking and Reservation System for QR-Code-Based Car Park , 2013 .

[21]  Daniel G. Aliaga,et al.  Urban sensing: Using smartphones for transportation mode classification , 2015, Comput. Environ. Urban Syst..

[22]  Csaba Csiszár,et al.  Development Stages of Intelligent Parking Information Systems for Trucks , 2013 .

[23]  Giuseppe Guido,et al.  Treating uncertainty in the estimation of speed from smartphone traffic probes , 2014 .

[24]  Daniel Álvarez Mántaras,et al.  A smartphone application to extract safety and environmental related information from the OBD-II interface of a car , 2012 .

[25]  Gys Albertus Marthinus Meiring,et al.  A Review of Intelligent Driving Style Analysis Systems and Related Artificial Intelligence Algorithms , 2015, Sensors.

[26]  Alexandre M. Bayen,et al.  Evaluation of traffic data obtained via GPS-enabled mobile phones: The Mobile Century field experiment , 2009 .

[27]  Rui Esteves Araujo,et al.  Driving coach: A smartphone application to evaluate driving efficient patterns , 2012, 2012 IEEE Intelligent Vehicles Symposium.

[28]  Giuseppe Guido,et al.  A co-operative methodology to estimate car fuel consumption by using smartphone sensors , 2015 .

[29]  Sanjay Srivastava,et al.  Multi-Modal Design of an Intelligent Transportation System , 2017, IEEE Transactions on Intelligent Transportation Systems.

[30]  A. Bayen,et al.  A traffic model for velocity data assimilation , 2010 .

[31]  Mehdi Ghatee,et al.  Three-Phases Smartphone-Based Warning System to Protect Vulnerable Road Users Under Fuzzy Conditions , 2018, IEEE Transactions on Intelligent Transportation Systems.

[32]  Joy Dahlgren,et al.  Using Vehicles Equipped with Toll Tags as Probes for Providing Travel Times , 2001 .

[33]  Mark Weiser.  The computer for the 21st century , 1991 .

[34]  Robert L. Bertini,et al.  Motorway traffic parameter estimation from mobile phone counts , 2006, Eur. J. Oper. Res..

[35]  Darcy M. Bullock,et al.  Real-Time Travel Time Estimates Using Media Access Control Address Matching , 2008 .

[36]  Rajkumar Buyya,et al.  A survey on vehicular cloud computing , 2014, J. Netw. Comput. Appl..

[37]  Abhijit Mukherjee,et al.  Characterisation of road bumps using smartphones , 2016 .

[38]  Darcy M. Bullock,et al.  Signalized Intersection Performance Measures for Operations Decision-Making , 2008 .

[39]  Geoff Rose,et al.  Mobile Phones as Traffic Probes: Practices, Prospects and Issues , 2006 .

[40]  Bernhard Friedrich,et al.  Evaluation of a Signal State Prediction Algorithm for Car to Infrastructure Applications , 2014 .

[41]  Giuseppe Guido,et al.  Co-operative ITS: Smartphone based Measurement Systems for Road Safety Assessment , 2014, EUSPN/ICTH.

[42]  Baher Abdulhai,et al.  Fusing a Bluetooth Traffic Monitoring System With Loop Detector Data for Improved Freeway Traffic Speed Estimation , 2013, J. Intell. Transp. Syst..

[43]  David J. Lovell,et al.  ACCURACY OF SPEED MEASUREMENTS FROM CELLULAR PHONE VEHICLE LOCATION SYSTEMS , 2001, J. Intell. Transp. Syst..

[44]  Bernhard Friedrich,et al.  Level of Service Estimation based on Low-frequency Floating Car Data☆ , 2014 .

[45]  Jacopo Biancat,et al.  Review of Transportation Mode Detection techniques , 2014, EAI Endorsed Trans. Ambient Syst..