AbuAli, N. (2015). Advanced vehicular sensing of road artifacts and driver behavior.

Paper presented at the Computers and Communication (ISCC), 2015 IEEE

Symposium on.

 

AbuAli, N., & Abou-zeid, H. (2016). Driver behavior modeling: Developments and

future directions. International Journal of Vehicular Technology, 2016.

 

Achirul Nanda, M., Boro Seminar, K., Nandika, D., & Maddu, A. (2018). A

comparison study of kernel functions in the support vector machine and its

application for termite detection. Information, 9(1), 5.

 

Ahmed, H., Pierre, S., & Quintero, A. (2017). A flexible testbed architecture for

VANET. Vehicular Communications, 9, 115-126.

 

Aichinger, C., Nitsche, P., Stütz, R., & Harnisch, M. (2016). Using low-cost

smartphone sensor data for locating crash risk spots in a road network.

Transportation Research Procedia, 14, 2015-2024.

 

Al-Sultan, S., Al-Doori, M. M., Al-Bayatti, A. H., & Zedan, H. (2014). A

comprehensive survey on vehicular ad hoc network. Journal of network and

computer applications, 37, 380-392.

 

Alam, K. M., Hariz, M. B., Hosseinioun, S. V., Saini, M., & El Saddik, A. (2016).

MUDVA: A multi-sensory dataset for the vehicular CPS applications. Paper

presented at the Multimedia Signal Processing (MMSP), 2016 IEEE 18th

International Workshop on.

 

Alaybeyoglu, A., & Senel, B. C. (2017). A design of fuzzy logic based android

application for safe driving. Paper presented at the Artificial Intelligence and

Data Processing Symposium (IDAP), 2017 International.

 

Albert, G., Musicant, O., Oppenheim, I., & Lotan, T. (2016). Which smartphone's

apps may contribute to road safety? An AHP model to evaluate experts'

opinions. Transport Policy, 50, 54-62.

 

Alessandroni, G., Carini, A., Lattanzi, E., Freschi, V., & Bogliolo, A. (2017). A study

on the influence of speed on road roughness sensing: the SmartRoadSense

case. Sensors, 17(2), 305.

 

Allamehzadeh, A., de la Parra, J. U., Hussein, A., Garcia, F., & Olaverri-Monreal, C.

(2017). Cost-efficient driver state and road conditions monitoring system for

conditional automation. Paper presented at the Intelligent Vehicles

Symposium (IV), 2017 IEEE.

 

Allamehzadeh, A., & Olaverri-Monreal, C. (2016). Automatic and manual driving

paradigms: Cost-efficient mobile application for the assessment of driver

inattentiveness and detection of road conditions. Paper presented at the

Intelligent Vehicles Symposium (IV), 2016 IEEE.

 

Allouch, A., Koubâa, A., Abbes, T., & Ammar, A. (2017). RoadSense: Smartphone

Application to Estimate Road Conditions Using Accelerometer and

Gyroscope. IEEE Sensors Journal, 17(13), 4231-4238.

 

Aloul, F., Zualkernan, I., Abu-Salma, R., Al-Ali, H., & Al-Merri, M. (2014). iBump:

Smartphone application to detect car accidents. Paper presented at the

Industrial Automation, Information and Communications Technology

(IAICT), 2014 International Conference on.

 

Alvarez, A. D., Garcia, F. S., Naranjo, J. E., Anaya, J. J., & Jimenez, F. (2014).

Modeling the driving behavior of electric vehicles using smartphones and

neural networks. IEEE Intelligent Transportation Systems Magazine, 6(3), 44-

53.

 

Alvear, O., Calafate, C. T., Cano, J.-C., & Manzoni, P. (2015). Validation of a vehicle

emulation platform supporting OBD-II communications. Paper presented at

the Consumer communications and networking conference (CCNC), 2015

12th Annual IEEE.

 

Aly, H., Basalamah, A., & Youssef, M. (2015). Lanequest: An accurate and energyefficient

lane detection system. Paper presented at the Pervasive Computing

and Communications (PerCom), 2015 IEEE International Conference on.

 

Aly, H., Basalamah, A., & Youssef, M. (2016). Robust and ubiquitous smartphonebased

lane detection. Pervasive and Mobile Computing, 26, 35-56.

 

Amarasinghe, M., Kottegoda, S., Arachchi, A. L., Muramudalige, S., Bandara, H. D.,

& Azeez, A. (2015). Cloud-based driver monitoring and vehicle diagnostic

with OBD2 telematics. Paper presented at the Advances in ICT for Emerging

Regions (ICTer), 2015 Fifteenth International Conference on.

 

Amici, R., Bonola, M., Bracciale, L., Rabuffi, A., Loreti, P., & Bianchi, G. (2014).

Performance assessment of an epidemic protocol in VANET using real traces.

Procedia Computer Science, 40, 92-99.

 

An, J.-W., Moon, D., & Cho, D.-S. (2015). Design of a Smartphone-Based Driving

Habit Monitoring System Advances in Computer Science and Ubiquitous

Computing (pp. 861-866): Springer.

 

Antoniou, C., Gikas, V., Papathanasopoulou, V., Danezis, C., Panagopoulos, A. D.,

Markou, I., . . . Perakis, H. (2015). Localization and driving behavior

classification with smartphone sensors in direct absence of global navigation

satellite systems. Transportation Research Record: Journal of the

Transportation Research Board(2489), 66-76.

 

Aras, A. C., & Gocer, I. (2016). Driver Rating based on Interval Type-2 Fuzzy Logic

System. IFAC-PapersOnLine, 49(11), 95-100.

 

Arroyo, C., Bergasa, L. M., & Romera, E. (2016). Adaptive fuzzy classifier to detect

driving events from the inertial sensors of a smartphone. Paper presented at

the Intelligent Transportation Systems (ITSC), 2016 IEEE 19th International

Conference on.

 

Asim, F. (2015). AndroSensor: Fiv Asim. Retrieved from

https://play.google.com/store/apps/details?id=com.fivasim.androsensor&hl=en

 

Astarita, V., Festa, D. C., Giofrè, P., Guido, G., & Mongelli, D. W. E. (2016). Cooperative

ITS: ESD a smartphone based system for sustainability and

transportation safety. Procedia Computer Science, 83, 449-456.

 

Azzuhana Roslan, N. S. M. Z., Nur Zarifah Harun, Akmalia Shabadin, Siti Zaharah

Ishak, Wong Shaw Voon. (2017). Risk of Motorcycle Crashes at Federal

Road. (MRR 221). Malaysian Institute of Road Safety Research: Perpustakaan

Negara Malaysia Retrieved from

http://web.miros.gov.my/1/publications.php?id_page=19&id_event=579.

 

Bahadoor, K., & Hosein, P. (2016). Application for the Detection of Dangerous

Driving and an Associated Gamification Framework. Paper presented at the

Future Internet of Things and Cloud Workshops (FiCloudW), IEEE

International Conference on.

 

Barata, J., Ferro, R., & Ferreira, J. (2014). My Traffic Manager. Procedia

Technology, 17, 209-216.

 

Bi, C., Huang, J., Xing, G., Jiang, L., Liu, X., & Chen, M. (2017). SafeWatch: A

Wearable Hand Motion Tracking System for Improving Driving Safety. Paper

presented at the Internet-of-Things Design and Implementation (IoTDI), 2017

IEEE/ACM Second International Conference on.

 

Birrell, S. A., & Fowkes, M. (2014). Glance behaviours when using an in-vehicle

smart driving aid: A real-world, on-road driving study. Transportation

research part F: traffic psychology and behaviour, 22, 113-125.

 

Birrell, S. A., Fowkes, M., & Jennings, P. A. (2014). Effect of using an in-vehicle

smart driving aid on real-world driver performance. IEEE Transactions on

Intelligent Transportation Systems, 15(4), 1801-1810.

 

Botzer, A., Musicant, O., & Perry, A. (2017). Driver behavior with a smartphone

collision warning application–A field study. Safety science, 91, 361-372.

 

Brezger, F., & Albers, A. (2013). Evaluation of a New Method for Customer-

Orientated Rating of Clutch Systems in Conceptual Hybrid Vehicles. Paper

presented at the ASME 2013 International Mechanical Engineering Congress

and Exposition.

 

Briante, O., Campolo, C., Iera, A., Molinaro, A., Paratore, S. Y., & Ruggeri, G.

(2014). Supporting augmented floating car data through smartphone-based

crowd-sensing. Vehicular Communications, 1(4), 181-196.

 

Bruwer, F. J., & Booysen, M. J. (2015). Comparison of GPS and MEMS support for

smartphone-based driver behavior monitoring. Paper presented at the

Computational Intelligence, 2015 IEEE Symposium Series on.

 

Camlica, Z., Hilal, A., & Kulić, D. (2016). Feature abstraction for driver behaviour

detection with stacked sparse auto-encoders. Paper presented at the Systems,

Man, and Cybernetics (SMC), 2016 IEEE International Conference on.

 

Carvalho, E., Ferreira, B. V., Ferreira, J., de Souza, C., Carvalho, H. V., Suhara, Y., . .

. Pessin, G. (2017). Exploiting the use of recurrent neural networks for driver

behavior profiling. Paper presented at the Neural Networks (IJCNN), 2017

International Joint Conference on.

 

Castignani, G., Derrmann, T., Frank, R., & Engel, T. (2015a). Driver behavior

profiling using smartphones: A low-cost platform for driver monitoring. IEEE

Intelligent Transportation Systems Magazine, 7(1), 91-102.

 

Castignani, G., Derrmann, T., Frank, R., & Engel, T. (2015b). Validation study of

risky event classification using driving pattern factors. Paper presented at the

Communications and Vehicular Technology in the Benelux (SCVT), 2015

IEEE Symposium on.

 

Castignani, G., Derrmann, T., Frank, R., & Engel, T. (2017). Smartphone-based

adaptive driving maneuver detection: A large-scale evaluation study. IEEE

Transactions on Intelligent Transportation Systems, 18(9), 2330-2339.

 

Castignani, G., & Frank, R. (2014). SenseFleet: A smartphone-based driver profiling

platform. Paper presented at the Sensing, Communication, and Networking

(SECON), 2014 Eleventh Annual IEEE International Conference on.

 

Castignani, G., Frank, R., & Engel, T. (2013a). Driver behavior profiling using

smartphones. Paper presented at the Intelligent Transportation Systems-

(ITSC), 2013 16th International IEEE Conference on.

 

Castignani, G., Frank, R., & Engel, T. (2013b). An evaluation study of driver profiling

fuzzy algorithms using smartphones. Paper presented at the Network Protocols

(ICNP), 2013 21st IEEE International Conference on.

 

Cervantes-Villanueva, J., Carrillo-Zapata, D., Terroso-Saenz, F., Valdes-Vela, M., &

Skarmeta, A. F. (2016). Vehicle maneuver detection with accelerometer-based

classification. Sensors, 16(10), 1618.

 

Chaovalit, P., Saiprasert, C., & Pholprasit, T. (2014). A method for driving event

detection using SAX with resource usage exploration on smartphone platform.

EURASIP Journal on Wireless Communications and Networking, 2014(1),

135.

 

Chen, K.-W., Tsai, H.-M., Hsieh, C.-H., Lin, S.-D., Wang, C.-C., Yang, S.-W., . . .

Chou, C.-T. (2014). Connected vehicle safety science, system, and framework.

Paper presented at the Internet of Things (WF-IoT), 2014 IEEE World Forum

on.

 

Chen, L.-B., Li, H.-Y., Chang, W.-J., Tang, J.-J., & Li, K. S.-M. (2015). An intelligent

vehicular telematics platform for vehicle driving safety supporting system.

Paper presented at the Connected Vehicles and Expo (ICCVE), 2015

International Conference on.

 

Chirawichitchai, N. (2015). Developing term weighting scheme based on term

occurrence ratio for sentiment analysis Information Science and Applications

(pp. 737-744): Springer.

 

Chuang, M.-C., Bala, R., Bernal, E. A., Paul, P., & Burry, A. (2014). Estimating Gaze

Direction of Vehicle Drivers Using a Smartphone Camera. Paper presented at

the CVPR Workshops.

 

Creaser, J. I., Edwards, C. J., Morris, N. L., & Donath, M. (2015). Are cellular phone

blocking applications effective for novice teen drivers? Journal of safety

research, 54, 75. e29-78.

 

Crippa, M., Oreggioni, G., Guizzardi, D., Muntean, M., Schaaf, E., Lo Vullo, E., . . .

Vignati, E. (2019). Fossil CO2 and GHG emissions of all world countries.

Luxemburg: Publication Office of the European Union.

 

D'Andrea, E., & Marcelloni, F. (2017). Detection of traffic congestion and incidents

from GPS trace analysis. Expert Systems with Applications, 73, 43-56.

 

Dang, V.-C., Kubo, M., Sato, H., Yamaguchi, A., & Namatame, A. (2014). A simple

braking model for detecting incidents locations by smartphones. Paper

presented at the Computational Intelligence for Security and Defense

Applications (CISDA), 2014 Seventh IEEE Symposium on.

 

Dange, G. R., Paranthaman, P. K., Bellotti, F., Samaritani, M., Berta, R., & De Gloria,

A. (2016). Assessment of driver behavior based on Machine learning

approaches in a social gaming scenario. Paper presented at the International

Conference on Applications in Electronics Pervading Industry, Environment

and Society.

 

Daptardar, S., Lakshminarayanan, V., Reddy, S., Nair, S., Sahoo, S., & Sinha, P.

(2015). Hidden Markov Model based driving event detection and driver

profiling from mobile inertial sensor data. Paper presented at the SENSORS,

2015 IEEE.

 

de Oliveira, L. P., Wehrmeister, M. A., & de Oliveira, A. S. (2017). Systematic

Literature Review on Automotive Diagnostics. Paper presented at the

Computing Systems Engineering (SBESC), 2017 VII Brazilian Symposium

on.

 

Diewald, S., Lindemann, P., Möller, A., Stockinger, T., Koelle, M., & Kranz, M.

(2014). Gamified training for vehicular user interfaces—Effects on drivers'

behavior. Paper presented at the Connected Vehicles and Expo (ICCVE), 2014

International Conference on.

 

Dobbins, C., & Fairclough, S. (2017). A mobile lifelogging platform to measure

anxiety and anger during real-life driving. Paper presented at the Pervasive

Computing and Communications Workshops (PerCom Workshops), 2017

IEEE International Conference on.

 

Domingos Da Cunha, F., Villas, L., Boukerche, A., Maia, G., Carneiro Viana, A.,

Mini, R. A. F., & Loureiro, A. A. F. (2016). Data Communication in

VANETs: Survey, Applications and Challenges. Ad Hoc Networks, 44(C), 90-

103. doi: 10.1016/j.adhoc.2016.02.017

 

Eboli, L., Guido, G., Mazzulla, G., Pungillo, G., & Pungillo, R. (2017). Investigating

Car Users’ Driving Behaviour through Speed Analysis. PROMETTraffic&

Transportation, 29(2), 193-202.

 

Eboli, L., Mazzulla, G., & Pungillo, G. (2016). Combining speed and acceleration to

define car users’ safe or unsafe driving behaviour. Transportation research

part C: emerging technologies, 68, 113-125.

 

Eboli, L., Mazzulla, G., & Pungillo, G. (2017). How to define the accident risk level

of car drivers by combining objective and subjective measures of driving style.

Transportation research part F: traffic psychology and behaviour, 49, 29-38.

 

Eftekhari, H. R., & Ghatee, M. (2016). An inference engine for smartphones to

preprocess data and detect stationary and transportation modes.

Transportation research part C: emerging technologies, 69, 313-327.

 

Ekanayake, H. B., Backlund, P., Ziemke, T., Ramberg, R., Hewagamage, K. P., &

Lebram, M. (2013). Comparing expert driving behavior in real world and

simulator contexts. International Journal of Computer Games Technology,

2013.

 

Engelbrecht, J., Booysen, M. J., van Rooyen, G.-J., & Bruwer, F. J. (2015).

Performance comparison of dynamic time warping (DTW) and a maximum

likelihood (ML) classifier in measuring driver behavior with smartphones.

Paper presented at the Computational Intelligence, 2015 IEEE Symposium

Series on.

 

Engelbrecht, J., Booysen, M. J., van Rooyen, G.-J., & Bruwer, F. J. (2015). Survey of

smartphone-based sensing in vehicles for intelligent transportation system

applications. IET Intelligent Transport Systems, 9(10), 924-935.

 

Environment, D. o. (2019). Environmental Quality Report 2018. Malaysia:

Department of Environment.

 

Fan, X., Liu, J., Wang, Z., Jiang, Y., & Liu, X. (2017a). Crowdsourced Road

Navigation: Concept, Design, and Implementation. IEEE Communications

Magazine, 55(6), 126-128.

 

Fan, X., Liu, J., Wang, Z., Jiang, Y., & Liu, X. S. (2017b). CrowdNavi: Demystifying

Last Mile Navigation With Crowdsourced Driving Information. IEEE

Transactions on Industrial Informatics, 13(2), 771-781.

 

Fang, S.-H., Fei, Y.-X., Xu, Z., & Tsao, Y. (2017). Learning Transportation Modes

From Smartphone Sensors Based on Deep Neural Network. IEEE Sensors

Journal, 17(18), 6111-6118.

 

Feraud, I. S., Lara, M. M., & Naranjo, J. E. (2017). A fuzzy logic model to estimate

safe driving behavior based on traffic violation. Paper presented at the

Ecuador Technical Chapters Meeting (ETCM), 2017 IEEE.

 

Ferris, J. S., & Newburn, D. A. (2017). Wireless alerts for extreme weather and the

impact on hazard mitigating behavior. Journal of Environmental Economics

and Management, 82, 239-255.

 

Fitz-Walter, Z., Johnson, D., Wyeth, P., Tjondronegoro, D., & Scott-Parker, B.

(2017). Driven to drive? Investigating the effect of gamification on learner

driver behavior, perceived motivation and user experience. Computers in

Human Behavior, 71, 586-595.

 

Fitzpatrick, C. D., McKinnon, I. A., Tainter, F. T., & Knodler Jr, M. A. (2016). The

application of continuous speed data for setting rational speed limits and

improving roadway safety. Safety science, 85, 171-178.

 

Geng, Y., & Cassandras, C. G. (2013). New “smart parking” system based on

resource allocation and reservations. IEEE Transactions on Intelligent

Transportation Systems, 14(3), 1129-1139.

 

Günther, M., Rauh, N., & Krems, J. F. (2017). Conducting a study to investigate ecodriving

strategies with battery electric vehicles–a multiple method approach.

Transportation Research Procedia, 25, 2242-2256.

 

Hadiwardoyo, S. A., Patra, S., Calafate, C. T., Cano, J.-C., & Manzoni, P. (2017). An

Android ITS Driving Safety Application Based on Vehicle-to-Vehicle (V2V)

Communications. Paper presented at the Computer Communication and

Networks (ICCCN), 2017 26th International Conference on.

 

Handel, P., Skog, I., Wahlstrom, J., Bonawiede, F., Welch, R., Ohlsson, J., &

Ohlsson, M. (2014). Insurance telematics: Opportunities and challenges with

the smartphone solution. IEEE Intelligent Transportation Systems Magazine,

6(4), 57-70.

 

Hansen, J. H., Busso, C., Zheng, Y., & Sathyanarayana, A. (2017). Driver Modeling

for Detection and Assessment of Driver Distraction: Examples from the

UTDrive Test Bed. IEEE Signal Processing Magazine, 34(4), 130-142.

 

Harding, S., Kandlikar, M., & Gulati, S. (2016). Taxi apps, regulation, and the market

for taxi journeys. Transportation Research Part A: Policy and Practice, 88,

15-25.

 

Harikrishnan, P., & Gopi, V. P. (2017). Vehicle Vibration Signal Processing for Road

Surface Monitoring. IEEE Sensors Journal, 17(16), 5192-5197.

 

Hashimoto, N., Okuma, T., Miyakoshi, S., Tomita, K., Matsumoto, O., Smirnov, A., .

. . Lashkov, I. (2016). Use cases for rider assistant mobile application

evaluation using travelling simulator. Paper presented at the Open Innovations

Association (FRUCT), 2016 19th Conference of.

 

Hawkins, I. (2019). Torque Pro (OBD 2 & Car) (Version 1.10.114): Ian J Hawkins.

Retrieved from

https://play.google.com/store/apps/details?id=org.prowl.torque&hl=en

 

Hlasny, T., Fanti, M. P., Mangini, A. M., Rotunno, G., & Turchiano, B. (2017).

Optimal fuel consumption for heavy trucks: A review. Paper presented at the

Service Operations and Logistics, and Informatics (SOLI), 2017 IEEE

International Conference on.

 

Hsieh, C.-H., Tsai, H.-M., Yang, S.-W., & Lin, S.-D. (2014). Predict scooter's

stopping event using smartphone as the sensing device. Paper presented at the

Internet of Things (iThings), 2014 IEEE International Conference on, and

Green Computing and Communications (GreenCom), IEEE and Cyber,

Physical and Social Computing (CPSCom), IEEE.

 

Hu, J., Shao, Y., Sun, Z., Wang, M., Bared, J., & Huang, P. (2016). Integrated optimal

eco-driving on rolling terrain for hybrid electric vehicle with vehicleinfrastructure

communication. Transportation research part C: emerging

technologies, 68, 228-244.

 

Hu, X., Chiu, Y.-C., Ma, Y.-L., & Zhu, L. (2015). Studying driving risk factors using

multi-source mobile computing data. International journal of transportation

science and technology, 4(3), 295-312.

 

Huang, K.-S., Chiu, P.-J., Tsai, H.-M., Kuo, C.-C., Lee, H.-Y., & Wang, Y.-C. F.

(2016). Redeye: preventing collisions caused by red-light running scooters

with smartphones. IEEE Transactions on Intelligent Transportation Systems,

17(5), 1243-1257.

 

Husnjak, S., Forenbacher, I., & Bucak, T. (2015). Evaluation of Eco-Driving Using

Smart Mobile Devices. PROMET-Traffic&Transportation, 27(4), 335-344.

 

Husnjak, S., Peraković, D., Forenbacher, I., & Mumdziev, M. (2015). Telematics

system in usage based motor insurance. Procedia Engineering, 100, 816-825.

 

Jahangiri, A., & Rakha, H. A. (2015). Applying machine learning techniques to

transportation mode recognition using mobile phone sensor data. IEEE

Transactions on Intelligent Transportation Systems, 16(5), 2406-2417.

 

Jeon, M., Yang, E., Oh, E., Park, J., & Youn, C.-H. (2017). A Deterministic Feedback

Model for Safe Driving based on Nonlinear Principal Analysis Scheme.

Procedia Computer Science, 113, 454-459.

 

Ji, Z., Ganchev, I., O'Droma, M., Zhao, L., & Zhang, X. (2014). A cloud-based car

parking middleware for IoT-based smart cities: Design and implementation.

Sensors, 14(12), 22372-22393.

 

Jiang, L., Chen, X., & He, W. (2016). SafeCam: Analyzing intersection-related driver

behaviors using multi-sensor smartphones. Paper presented at the Pervasive

Computing and Communications (PerCom), 2016 IEEE International

Conference on.

 

Jo, J., Kim, H., Park, H., & Yoon, D. (2015). A Monitoring System to Understand

Postal Motorcyclist's Driving Behavior. Paper presented at the Intelligent

Transportation Systems (ITSC), 2015 IEEE 18th International Conference on.

 

John, G. H., & Langley, P. (2013). Estimating continuous distributions in Bayesian

classifiers. arXiv preprint arXiv:1302.4964.

 

Júnior, J. F., Carvalho, E., Ferreira, B. V., de Souza, C., Suhara, Y., Pentland, A., &

Pessin, G. (2017). Driver behavior profiling: An investigation with different

smartphone sensors and machine learning. PLoS one, 12(4), e0174959.

 

Kaiwartya, O., Abdullah, A. H., Cao, Y., Altameem, A., Prasad, M., Lin, C.-T., &

Liu, X. (2016). Internet of vehicles: Motivation, layered architecture, network

model, challenges, and future aspects. IEEE Access, 4, 5356-5373.

 

Kamalanathsharma, R. K., Rakha, H. A., & Zohdy, I. H. (2015). Survey on in-vehicle

technology use: results and findings. International journal of transportation

science and technology, 4(2), 135-149.

 

Kaplan, S., Guvensan, M. A., Yavuz, A. G., & Karalurt, Y. (2015). Driver behavior

analysis for safe driving: A survey. IEEE Transactions on Intelligent

Transportation Systems, 16(6), 3017-3032.

 

Kar, A., & Corcoran, P. (2017). A Review and Analysis of Eye-Gaze Estimation

Systems, Algorithms and Performance Evaluation Methods in Consumer

Platforms. IEEE Access, 5, 16495-16519.

 

Karaduman, M., & Eren, H. (2017a). Classification of road curves and corresponding

driving profile via smartphone trip data. Paper presented at the Artificial

Intelligence and Data Processing Symposium (IDAP), 2017 International.

 

Karaduman, M., & Eren, H. (2017b). Deep learning based traffic direction sign

detection and determining driving style. Paper presented at the Computer

Science and Engineering (UBMK), 2017 International Conference on.

 

Karaliopoulos, M., Katsikopoulos, K., & Lambrinos, L. (2017). Bounded rationality

can make parking search more efficient: The power of lexicographic

heuristics. Transportation Research Part B: Methodological, 101, 28-50.

 

Karatas, C., Liu, L., Li, H., Liu, J., Wang, Y., Tan, S., . . . Martin, R. (2016).

Leveraging wearables for steering and driver tracking. Paper presented at the

Computer Communications, IEEE INFOCOM 2016-The 35th Annual IEEE

International Conference on.

 

Kato, H., Sakajyo, Y., & Kaneda, S. (2017). Visualization Method for Bicycle Rider

Behavior Analysis Using a Smartphone. Paper presented at the Computer

Software and Applications Conference (COMPSAC), 2017 IEEE 41st Annual.

 

Khanapuri, A. V., Shastri, A., D'souza, G., & D'souza, S. (2015). On road: A car

assistant application. Paper presented at the Technologies for Sustainable

Development (ICTSD), 2015 International Conference on.

 

Khoo, H. L., & Asitha, K. (2016). An impact analysis of traffic image information

system on driver travel choice. Transportation Research Part A: Policy and

Practice, 88, 175-194.

 

Kim, H., Hwang, Y., Yoon, D., & Park, C. H. (2013). Short paper: Study of driver

workload-based smartphone control service. Paper presented at the Vehicular

Networking Conference (VNC), 2013 IEEE.

 

Koesdwiady, A., Soua, R., Karray, F., & Kamel, M. S. (2017). Recent Trends in

Driver Safety Monitoring Systems: State of the Art and Challenges. IEEE

Transactions on Vehicular Technology, 66(6), 4550-4563.

 

Kong, W., Zhou, L., Wang, Y., Zhang, J., Liu, J., & Gao, S. (2015). A system of

driving fatigue detection based on machine vision and its application on smart

device. Journal of Sensors, 2015.

 

Kujala, T., Karvonen, H., & Mäkelä, J. (2016). Context-sensitive distraction

warnings–Effects on drivers ׳ visual behavior and acceptance. International

Journal of Human-Computer Studies, 90, 39-52.

 

Laval, J. A., Toth, C. S., & Zhou, Y. (2014). A parsimonious model for the formation

of oscillations in car-following models. Transportation Research Part B:

Methodological, 70, 228-238.

 

Li, F., Zhang, H., Che, H., & Qiu, X. (2016). Dangerous driving behavior detection

using smartphone sensors. Paper presented at the Intelligent Transportation

Systems (ITSC), 2016 IEEE 19th International Conference on.

 

Liu, M., Ordóñez-Hurtado, R. H., Wirth, F., Gu, Y., Crisostomi, E., & Shorten, R.

(2016). A distributed and privacy-aware speed advisory system for optimizing

conventional and electric vehicle networks. IEEE Transactions on Intelligent

Transportation Systems, 17(5), 1308-1318.

 

Ma, C., Dai, X., Zhu, J., Liu, N., Sun, H., & Liu, M. (2017). DrivingSense: Dangerous

Driving Behavior Identification Based on Smartphone Autocalibration. Mobile

Information Systems, 2017.

 

Magaña, V. C., & Muñoz-Organero, M. (2015). Reducing stress on habitual journeys.

Paper presented at the Consumer Electronics-Berlin (ICCE-Berlin), 2015

IEEE 5th International Conference on.

 

Magaña, V. C., & Muñoz-Organero, M. (2016). Artemisa: A personal driving

assistant for fuel saving. IEEE Transactions on Mobile Computing, 15(10),

2437-2451.

 

Manasseh, C., & Sengupta, R. (2013). Predicting driver destination using machine

learning techniques. Paper presented at the Intelligent Transportation

Systems-(ITSC), 2013 16th International IEEE Conference on.

 

Martinez, C. M., Heucke, M., Wang, F.-Y., Gao, B., & Cao, D. (2018). Driving style

recognition for intelligent vehicle control and advanced driver assistance: A

survey. IEEE Transactions on Intelligent Transportation Systems, 19(3), 666-

676.

 

Meiring, G. A. M., & Myburgh, H. C. (2015). A review of intelligent driving style

analysis systems and related artificial intelligence algorithms. Sensors, 15(12),

30653-30682.

 

Mekki, T., Jabri, I., Rachedi, A., & ben Jemaa, M. (2017). Vehicular cloud networks:

Challenges, architectures, and future directions. Vehicular Communications, 9,

268-280.

 

Melnicuk, V., Birrell, S., Crundall, E., & Jennings, P. (2016). Towards hybrid driver

state monitoring: Review, future perspectives and the role of consumer

electronics. Paper presented at the Intelligent Vehicles Symposium (IV), 2016

IEEE.

 

Meseguer, J. E., Calafate, C. T., Cano, J. C., & Manzoni, P. (2013). Drivingstyles: A

smartphone application to assess driver behavior. Paper presented at the

Computers and Communications (ISCC), 2013 IEEE Symposium on.

 

Meseguer, J. E., Calafate, C. T., Cano, J. C., & Manzoni, P. (2015). Assessing the

impact of driving behavior on instantaneous fuel consumption. Paper

presented at the Consumer Communications and Networking Conference

(CCNC), 2015 12th Annual IEEE.

 

Meseguer, J. E., Toh, C. K., Calafate, C. T., Cano, J. C., & Manzoni, P. (2017).

Drivingstyles: a mobile platform for driving styles and fuel consumption

characterization. Journal of Communications and Networks, 19(2), 162-168.

 

Mihai, D., Dumitru, A., Postelnicu, C., & Mogan, G. (2015). Video-based evaluation

of driver's visual attention using smartphones. Paper presented at the

Information, Intelligence, Systems and Applications (IISA), 2015 6th

International Conference on.

 

Ming, L. J., Tan, I. K., & Hoong, P. K. (2017). Classifying drivers using electronic

logging devices. Paper presented at the Information and Communication

Technology (ICoIC7), 2017 5th International Conference on.

 

Miyajima, C., & Takeda, K. (2016). Driver-behavior modeling using on-road driving

data: a new application for behavior signal processing. IEEE Signal

Processing Magazine, 33(6), 14-21.

 

Monzon, A., Garcia-Castro, Á., & Valdes, C. (2017). Methodology to Assess the

Effects of ICT-measures on Emissions. The Case Study of Madrid. Procedia

Engineering, 178, 13-23.

 

Munoz-Organero, M., & Magaña, V. C. (2013). Validating the impact on reducing

fuel consumption by using an ecodriving assistant based on traffic sign

detection and optimal deceleration patterns. IEEE Transactions on Intelligent

Transportation Systems, 14(2), 1023-1028.

 

MUSICANT, O., & BOTZER, A. (2016). The Safety Benefits Of Collision Warning

Applications–Evidence From On-road Data. International Journal of Safety

and Security Engineering, 6(2), 362-371.

 

Musicant, O., & Lotan, T. (2016). Can novice drivers be motivated to use a

smartphone based app that monitors their behavior? Transportation research

part F: traffic psychology and behaviour, 42, 544-557.

 

Musicant, O., Lotan, T., & Grimberg, E. (2015). Potential of group incentive schemes

to encourage use of driving safety apps. Transportation Research Record:

Journal of the Transportation Research Board(2516), 1-7.

 

Narote, S. P., Bhujbal, P. N., Narote, A. S., & Dhane, D. M. (2018). A review of

recent advances in lane detection and departure warning system. Pattern

Recognition, 73, 216-234. doi: https://doi.org/10.1016/j.patcog.2017.08.014

 

Natpratan, C., & Cooharojananone, N. (2015). Study of Sound and Haptic Feedback

in Smart Wearable Devices to Improve Driving Performance of Elders

Information Science and Applications (pp. 51-58): Springer.

 

Negi, N. S., van Leeuwen, P., & Happee, R. (2019). Differences in driver behaviour

between novice and experienced drivers: A driving simulator study. Paper

presented at the Proceedings of the 5th International Conference on Vehicle

Technology and Intelligent Transport Systems (VEHITS 2019).

 

Nguyen, C., Wang, Y., & Nguyen, H. N. (2013). Random forest classifier combined

with feature selection for breast cancer diagnosis and prognostic.

 

Nkenyereye, L., & Jang, J.-w. (2016). Integration of Big Data for Connected Cars

Applications Based on Tethered Connectivity. Procedia Computer Science,

98, 554-559.

 

Orfila, O., Saint Pierre, G., & Messias, M. (2015). An android based ecodriving

assistance system to improve safety and efficiency of internal combustion

engine passenger cars. Transportation research part C: emerging

technologies, 58, 772-782.

 

Osafune, T., Takahashi, T., Kiyama, N., Sobue, T., Yamaguchi, H., & Higashino, T.

(2017). Analysis of accident risks from driving behaviors. International

Journal of Intelligent Transportation Systems Research, 15(3), 192-202.

 

Ouyang, Z., Niu, J., Liu, Y., & Rodrigues, J. (2016). Multiwave: A novel vehicle

steering pattern detection method based on smartphones. Paper presented at

the Communications (ICC), 2016 IEEE International Conference on.

 

Perera, S. C., & Dias, N. G. (2017). Applying Intelligent Speed Adaptation to a Road

Safety Mobile Application-DriverSafeMode. Paper presented at the

International Conference on Advances in ICT for Emerging Regions (ICTer).

 

Phanama, Y. A., Duthoit, C., & Sari, R. F. (2016). Aware-D: Voice recognition-based

driving awareness detection. Paper presented at the Communications (APCC),

2016 22nd Asia-Pacific Conference on.

 

Phumphuang, P., Wuttidittachotti, P., & Saiprasert, C. (2015). Driver identification

using variance of the acceleration data. Paper presented at the Computer

Science and Engineering Conference (ICSEC), 2015 International.

 

Pozueco, L., Rionda, A., Pañeda, A. G., Sánchez, J. A., Pañeda, X. G., García, R., . . .

Tuero, A. G. (2017). Impact of on-board tutoring systems to improve driving

efficiency of non-professional drivers. IET Intelligent Transport Systems,

11(4), 196-202.

 

Pratama, B. G., Ardiyanto, I., & Adji, T. B. (2017). A review on driver drowsiness

based on image, bio-signal, and driver behavior. Paper presented at the

Science and Technology-Computer (ICST), 2017 3rd International Conference

on.

 

Predic, B., & Stojanovic, D. (2015). Enhancing driver situational awareness through

crowd intelligence. Expert Systems with Applications, 42(11), 4892-4909.

 

Qiao, F., Rahman, R., Li, Q., & Yu, L. (2017). Safe and Environment-Friendly

Forward Collision Warning Messages in the Advance Warning Area of a

Construction Zone. International Journal of Intelligent Transportation

Systems Research, 15(3), 166-179.

 

Rachburee, N., Punlumjeak, W., Rugtanom, S., Jaithavil, D., & Pracha, M. (2015). A

prediction of engineering students performance from core engineering course

using classification Information Science and Applications (pp. 649-656):

Springer.

 

Rai, K., Devi, M. S., & Guleria, A. (2016). Decision tree based algorithm for intrusion

detection. International Journal of Advanced Networking and Applications,

7(4), 2828.

 

Reyes-Muñoz, A., Domingo, M. C., López-Trinidad, M. A., & Delgado, J. L. (2016).

Integration of body sensor networks and vehicular ad-hoc networks for traffic

safety. Sensors, 16(1), 107.

 

Rionda, A., Pañeda, X. G., García, R., Díaz, G., Martínez, D., Mitre, M., . . . Marín, I.

(2014). Blended learning system for efficient professional driving. Computers

& Education, 78, 124-139.

 

Road Facts. from https://www.miros.gov.my/1/page.php?id=17

 

Romera, E., Bergasa, L. M., & Arroyo, R. (2016). Need data for driver behaviour

analysis? Presenting the public UAH-DriveSet. Paper presented at the

Intelligent Transportation Systems (ITSC), 2016 IEEE 19th International

Conference on.

 

Rosolino, V., Teresa, I., Vittorio, A., Carmine, F. D., Antonio, T., Daniele, R., &

Claudio, Z. (2014). Road safety performance assessment: a new road network

Risk Index for info mobility. Procedia-Social and Behavioral Sciences, 111,

624-633.

 

Ruf, M., Ziehn, J., German, L., Rosenhahn, B., Willersinn, D., Beyerer, J., & Gotzig,

H. (2016). Lightweight, non-invasive collection of steering wheel angles and

pedal positions. Paper presented at the Instrumentation, Control and

Automation (ICA), 2016 International Conference on.

 

Ryder, B., Gahr, B., Egolf, P., Dahlinger, A., & Wortmann, F. (2017). Preventing

traffic accidents with in-vehicle decision support systems-The impact of

accident hotspot warnings on driver behaviour. Decision support systems, 99,

64-74.

 

Saiprasert, C., Pholprasit, T., & Thajchayapong, S. (2017). Detection of driving

events using sensory data on smartphone. International Journal of Intelligent

Transportation Systems Research, 15(1), 17-28.

 

Saiprasert, C., Thajchayapong, S., Pholprasit, T., & Tanprasert, C. (2014). Driver

behaviour profiling using smartphone sensory data in a V2I environment.

Paper presented at the Connected Vehicles and Expo (ICCVE), 2014

International Conference on.

 

Seraj, F., Havinga, P. J., & Meratnia, N. (2016). Spinsafe: An unsupervised

smartphone-based wheelchair path monitoring system. Paper presented at the

Pervasive Computing and Communication Workshops (PerCom Workshops),

2016 IEEE International Conference on.

 

Seraj, F., Meratnia, N., & Havinga, P. J. (2017a). An aggregation and visualization

technique for crowd-sourced continuous monitoring of transport

infrastructures. Paper presented at the Pervasive Computing and

Communications Workshops (PerCom Workshops), 2017 IEEE International

Conference on.

 

Seraj, F., Meratnia, N., & Havinga, P. J. (2017b). RoVi: Continuous transport

infrastructure monitoring framework for preventive maintenance. Paper

presented at the Pervasive Computing and Communications (PerCom), 2017

IEEE International Conference on.

 

Simmons, S. M., Caird, J. K., & Steel, P. (2017). A meta-analysis of in-vehicle and

nomadic voice-recognition system interaction and driving performance.

Accident Analysis & Prevention, 106, 31-43.

 

Simonyi, E., Fazekas, Z., & Gáspár, P. (2014). Smartphone application for assessing

various aspects of urban public transport. Transportation Research Procedia,

3, 185-194.

 

Singh, G., Bansal, D., & Sofat, S. (2017). A smartphone based technique to monitor

driving behavior using DTW and crowdsensing. Pervasive and Mobile

Computing, 40, 56-70.

 

Smirnov, A., Kashevnik, A., & Lashkov, I. (2016). Human-Smartphone Interaction

for Dangerous Situation Detection and Recommendation Generation While

Driving. Paper presented at the International Conference on Speech and

Computer.

 

Smirnov, A., Kashevnik, A., Lashkov, I., Baraniuc, O., & Parfenov, V. (2016).

Smartphone-based identification of dangerous driving situations: Algorithms

and implementation. Paper presented at the Proceedings of the 18th

Conference of Open Innovations Association FRUCT.

 

Smirnov, A., Kashevnik, A., Lashkov, I., Hashimoto, N., & Boyali, A. (2015).

Smartphone-based two-wheeled self-balancing vehicles rider assistant. Paper

presented at the Open Innovations Association (FRUCT), 2015 17th

Conference of.

 

Soriguera, F., & Miralles, E. (2016). Driver feedback mobile app. Transportation

Research Procedia, 18, 264-271.

 

Stamatiadis, N., Pappalardo, G., & Cafiso, S. (2017). Use of technology to improve

bicycle mobility in smart cities. Paper presented at the Models and

Technologies for Intelligent Transportation Systems (MT-ITS), 2017 5th IEEE

International Conference on.

 

Statistics on Causes of Death, Malaysia. (2017). from

https://www.dosm.gov.my/v1/index.php?r=column/cthemeByCat&cat=401&b

ul_id=Y3psYUI2VjU0ZzRhZU1kcVFMMThGUT09&menu_id=L0pheU43N

WJwRWVSZklWdzQ4TlhUUT09

 

Suzdaleva, E., & Nagy, I. (2014). Data-based speed-limit-respecting eco-driving

system. Transportation research part C: emerging technologies, 44, 253-264.

 

Sysoev, M., Kos, A., Guna, J., & Pogačnik, M. (2017). Estimation of the Driving

Style Based on the Users’ Activity and Environment Influence. Sensors,

17(10), 2404.

 

Taha, A.-E. M., & Nasser, N. (2015). Utilizing CAN-Bus and smartphones to enforce

safe and responsible driving. Paper presented at the Computers and

Communication (ISCC), 2015 IEEE Symposium on.

 

Tak, S., Woo, S., & Yeo, H. (2016). Study on the framework of hybrid collision

warning system using loop detectors and vehicle information. Transportation

research part C: emerging technologies, 73, 202-218.

 

Tal, I., Olaru, A., & Muntean, G.-M. (2013). eWARPE-Energy-efficient weatheraware

route planner for electric bicycles. Paper presented at the Network

Protocols (ICNP), 2013 21st IEEE International Conference on.

 

Thill, S., & Riveiro, M. (2015). Situation awareness in eco-driving. Paper presented

at the Cognitive Methods in Situation Awareness and Decision Support

(CogSIMA), 2015 IEEE International Inter-Disciplinary Conference on.

 

Tselentis, D. I., Yannis, G., & Vlahogianni, E. I. (2017). Innovative motor insurance

schemes: A review of current practices and emerging challenges. Accident

Analysis & Prevention, 98, 139-148.

 

Turkes, O., Seraj, F., Scholten, H., Meratnia, N., & Havinga, P. J. (2015). An ad-hoc

opportunistic dissemination protocol for smartphone-based participatory

traffic monitoring. Paper presented at the Vehicular Technology Conference

(VTC Fall), 2015 IEEE 82nd.

 

Vacca, A., & Meloni, I. (2015). Understanding route switch behavior: An analysis

using gps based data. Transportation Research Procedia, 5, 56-65.

 

Vaezipour, A., Rakotonirainy, A., Haworth, N., & Delhomme, P. (2017). Enhancing

eco-safe driving behaviour through the use of in-vehicle human-machine

interface: A qualitative study. Transportation Research Part A: Policy and

Practice, 100, 247-263.

 

Vahdat-Nejad, H., Ramazani, A., Mohammadi, T., & Mansoor, W. (2016). A survey

on context-aware vehicular network applications. Vehicular Communications,

3, 43-57.

 

Vaiana, R., Iuele, T., Astarita, V., Caruso, M. V., Tassitani, A., Zaffino, C., & Giofrè,

V. P. (2014). Driving behavior and traffic safety: an acceleration-based safety

evaluation procedure for smartphones. Modern Applied Science, 8(1), 88.

 

Valdemars, A., Atstaja, D., & Vasiljeva, Z. (2015). RESPONSIBLE CHANGE OF

VEHICLE DRIVER’S DRIVING BEHAVIOURS. ECONOMIC SCIENCE

FOR RURAL DEVELOPMENT, 132.

 

Vasconcelos, I., Vasconcelos, R. O., Olivieri, B., Roriz, M., Endler, M., & Junior, M.

C. (2017). Smartphone-based outlier detection: a complex event processing

approach for driving behavior detection. Journal of Internet Services and

Applications, 8(1), 13.

 

Vieira, P., Costeira, J. P., Brandão, S., & Marques, M. (2016). SMARTcycling:

Assessing cyclists' driving experience. Paper presented at the Intelligent

Vehicles Symposium (IV), 2016 IEEE.

 

Vilaça, R. D., Araújo, R., & Araújo, R. E. (2017). A System for Driver Analysis Using

Smartphone as Smart Sensor. Paper presented at the Doctoral Conference on

Computing, Electrical and Industrial Systems.

 

Vlahogianni, E. I., & Barmpounakis, E. N. (2017). Driving analytics using

smartphones: Algorithms, comparisons and challenges. Transportation

research part C: emerging technologies, 79, 196-206.

 

Wahlström, J., Skog, I., & Händel, P. (2015). Detection of dangerous cornering in

GNSS-data-driven insurance telematics. IEEE Transactions on Intelligent

Transportation Systems, 16(6), 3073-3083.

 

Wahlström, J., Skog, I., & Händel, P. (2017). Smartphone-Based Vehicle Telematics:

A Ten-Year Anniversary. IEEE Transactions on Intelligent Transportation

Systems, 18(10), 2802-2825.

 

Walcott-Bryant, A., Tatsubori, M., Bryant, R. E., Oduor, E., Omondi, S., Osebe, S., . .

. Bent, O. (2016). Harsh brakes at potholes in Nairobi: Context-based driver

behavior in developing cities. Paper presented at the Intelligent Transportation

Systems (ITSC), 2016 IEEE 19th International Conference on.

 

Wallace, B., Rockwood, M., Goubran, R., Knoefel, F., Marshall, S., & Porter, M.

(2015). Measurement of vehicle acceleration in studies of older drivers from

GPS position and OBDII velocity sensors. Paper presented at the Medical

Measurements and Applications (MeMeA), 2015 IEEE International

Symposium on.

 

Wang, L., & Ju, D. Y. (2015). Concurrent use of an in-vehicle navigation system and

a smartphone navigation application. Social Behavior and Personality: an

international journal, 43(10), 1629-1640.

 

Whaiduzzaman, M., Sookhak, M., Gani, A., & Buyya, R. (2014). A survey on

vehicular cloud computing. Journal of network and computer applications, 40,

325-344.

 

Wilhelem, T., Okuda, H., Kawashima, A., & Suzuki, T. (2016). Identification of timevarying

parameters in Gipps model for driving behavior analysis. Paper

presented at the Systems, Man, and Cybernetics (SMC), 2016 IEEE

International Conference on.

 

Wilhelem, T., Okuda, H., Levedahl, B., & Suzuki, T. (2017). Energy Consumption

Evaluation Based on a Personalized Driver–Vehicle Model. IEEE

Transactions on Intelligent Transportation Systems, 18(6), 1468-1477.

 

Woo, C., & Kulić, D. (2016). Manoeuvre segmentation using smartphone sensors.

Paper presented at the Intelligent Vehicles Symposium (IV), 2016 IEEE.

 

Wu, X., Freese, D., Cabrera, A., & Kitch, W. A. (2015). Electric vehicles’ energy

consumption measurement and estimation. Transportation Research Part D:

Transport and Environment, 34, 52-67.

 

Xiao, D., & Feng, C. (2016). Detection of drivers visual attention using smartphone.

Paper presented at the Natural Computation, Fuzzy Systems and Knowledge

Discovery (ICNC-FSKD), 2016 12th International Conference on.

 

Xie, J., Hilal, A. R., & Kulić, D. (2017). Driving Maneuver Classification: A

Comparison of Feature Extraction Methods. IEEE Sensors Journal.

 

Xu, X., Gao, H., Yu, J., Chen, Y., Zhu, Y., Xue, G., & Li, M. (2017). ER: Early

recognition of inattentive driving leveraging audio devices on smartphones.

Paper presented at the INFOCOM 2017-IEEE Conference on Computer

Communications, IEEE.

 

Xu, X., Yin, S., & Ouyang, P. (2017). Fast and low-power behavior analysis on

vehicles using smartphones. Paper presented at the Next Generation

Electronics (ISNE), 2017 6th International Symposium on.

 

Xu, Y., Li, H., Liu, H., Rodgers, M. O., & Guensler, R. L. (2017). Eco-driving for

transit: An effective strategy to conserve fuel and emissions. Applied energy,

194, 784-797.

 

Yen, Y.-H., Huo, C.-L., & Sun, T.-Y. (2014). Adaptive lane departure warning

system on Android smartphone. Paper presented at the Consumer Electronics-

Taiwan (ICCE-TW), 2014 IEEE International Conference on.

 

Yu, J., Chen, Z., Zhu, Y., Chen, Y. J., Kong, L., & Li, M. (2017). Fine-grained

abnormal driving behaviors detection and identification with smartphones.

IEEE Transactions on Mobile Computing, 16(8), 2198-2212.

 

Zadeh, R. B., Ghatee, M., & Eftekhari, H. R. (2017). Three-Phases Smartphone-Based

Warning System to Protect Vulnerable Road Users Under Fuzzy Conditions.

IEEE Transactions on Intelligent Transportation Systems.

 

Zaid, S. M., Myeda, N. E., Mahyuddin, N., & Sulaiman, R. (2015). Malaysia’s rising

GHG emissions and carbon ‘lock-in’risk: A review of Malaysian building

sector legislation and policy. Journal of Surveying, Construction and

Property, 6(1), 1-13.

 

Zeeman, A. S., & Booysen, M. J. (2013). Combining speed and acceleration to detect

reckless driving in the informal public transport industry. Paper presented at

the 16th International IEEE Conference on Intelligent Transportation Systems

(ITSC 2013).

 

Zfnebi, K., Souissi, N., & Tikito, K. (2017). Driver behavior quantitative models:

Identification and classification of variables. Paper presented at the Networks,

Computers and Communications (ISNCC), 2017 International Symposium on.

 

Zhang, C., Patel, M., Buthpitiya, S., Lyons, K., Harrison, B., & Abowd, G. D. (2016).

Driver classification based on driving behaviors. Paper presented at the

Proceedings of the 21st International Conference on Intelligent User

Interfaces.

 

Zhao, X., Wu, Y., Rong, J., & Zhang, Y. (2015). Development of a driving simulator

based eco-driving support system. Transportation research part C: emerging

technologies, 58, 631-641.

 

Zhao, Y., Li, S., Hu, S., Su, L., Yao, S., Shao, H., . . . Abdelzaher, T. (2017).

Greendrive: A smartphone-based intelligent speed adaptation system with

real-time traffic signal prediction. Paper presented at the Cyber-Physical

Systems (ICCPS), 2017 ACM/IEEE 8th International Conference on.

 

Zheng, Y., & Hansen, J. H. (2016). Unsupervised driving performance assessment

using free-positioned smartphones in vehicles. Paper presented at the

Intelligent Transportation Systems (ITSC), 2016 IEEE 19th International

Conference on.

 

Zhu, X., Hu, X., & Chiu, Y.-C. (2013). Design of Driving Behavior Pattern

Measurements Using Smartphone Global Positioning System Data.

International journal of transportation science and technology, 2(4), 269-288.

 

Zhu, X., Yuan, Y., Hu, X., Chiu, Y.-C., & Ma, Y.-L. (2017). A Bayesian Network

model for contextual versus non-contextual driving behavior assessment.

Transportation research part C: emerging technologies, 81, 172-187.