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Development and Opportunity of Facial Recognition Technology in Transport Industry

  • Report

  • 30 Pages
  • January 2018
  • Region: Global
  • Market Intelligence & Consulting Institute (MIC)
  • ID: 4450615

Demand for Driverless Cars and Smart Driver Assistance Systems Expands Facial Recognition Applications

The public transportation and infrastructure sectors in the transport industry are characterized with a constant crowd flow and a large number of foreign visitors. In order to smooth out the flow of crowds and protect national security and tourists, biometric recognition technology that can shorten immigration inspection time and track suspects is increasingly needed, especially after the 911 terrorism attack. The biometric recognition technology currently employed by the transport industry for identification relies on biometric traits such as fingerprint, iris, and facial data. This report looks into a variety of application cases to analyze the use of facial recognition technology in the transport industry and the potential of the technology.

In line with the megatrend towards smarter and informative vehicles, automakers have aggressively developed new technologies and solutions to address three major issues: the connection between the driver and the road conditions like driving safety and traffic jams, the vehicle conditions such as the theft protection feature, and the connection between the driver and the vehicle. "Facial recognition technology can solve all these issues," says Chung-yu Yang, industry analyst.

List of Topics:

  • Development of facial recognition technology in the transport industry, touching on three purchases of the technology which are ID verification, attribute analysis, and human-machine interface
  • Application cases associating with transport management systems, which are mainly used for immigration inspection and crime tracking, and includes the detailed view of two cases: automated gate at Japanese Narita Airport, and security system at China's Hohhot Railway Bureau.
  • Application cases in the air transport industry and land transport industry, where facial recognition technology is mainly used for crime prevention and permission management, and includes the detailed view of three cases: KLM's boarding system, Uber's driver verification system in the United States, and Chinese Didi Chuxing's car rental system.
  • Application cases in the car and automotive electronics industries where the facial recognition technology is mainly used for driver alerts and behavior analysis, and includes the detailed view of two cases: Japanese Omron's driver concentration sensing technology and German Bosch's concept car.
  • Analysis of the application cases of facial recognition, touching on how the technology has been employed in public transport, online car hailing services, and the car industry
  • Outlook for financial recognition in the transport industry, touching on opportunities in the areas of public transport and smart car.

Table of Contents

1. Introduction to Facial Recognition Technology
2. Application Cases of Facial Recognition Technology in Transport Industry
2.1 Transport Management System
2.1.1 Immigration Inspection: Automated Gate System at Japanese Narita Airport
2.1.2 Crime Tracking: Security System at China’s Hohhot Railway Bureau
2.2 Air Transport Industry
2.2.1 Passage Management: KLM’s Boarding System
2.3 Land Transport Industry
2.3.1 Crime Prevention: Uber’s Driver Verification System in the US
2.3.2 Permission Management: Chinese Didi Chuxing’s Car Rental System
2.4 Car and Automotive Electronics Industries
2.4.1 Driver Alerts: Japanese Omron Driver Concentration Sensing Technology
2.4.2 Behavior Analysis: German Bosch Concept Car

3. Application of Facial Recognition in the Transport Industry
3.1 Mainly Used in Public Transport and Infrastructure for ID Authentication Purposes
3.2 Online Car Hailing Service Providers Use Facial Recognition to Prevent Crimes
3.3 Car Industry Widely Use Facial Recognition for Car Design

4. Opportunities of Facial Recognition in the Transport Industry
4.1 National Policies Accelerate the Adoption of Facial Recognition in Public Transport Worldwide
4.1.1 Facial Recognition Leapfrogs Ahead as Iris and Fingerprint Recognition Fail to Meet Expectations
4.1.2 ICAO’s Implementation Ensures Facial Recognition Development
4.1.3 Adoption of Facial Recognition from Passports to e-Gate Systems is Progressively Done
4.2 Smart Cars Create New Opportunity for Facial Recognition

5. Conclusion
5.1 Demand for Driverless Cars and Smart Driver Assistance Systems Expands Facial Recognition Applications
5.2 Emergence of Service-oriented Business Model Spurs Verification Demand

List of Tables
Table 1 Facial Recognition Applications in the Transport Industry Worldwide
Table 2 National Policies and Programs for Biometric Identification Systems
Table 3 Automotive Product Manufactures and Their Biometric Technology

List of Figures
Figure 1 Applications of Facial Recognition Technology
Figure 2 Renting Process of DiDi Car Rental
Figure 3 Omron’s Driver Concentration Sensing Technology



Companies Mentioned (Partial List)

A selection of companies mentioned in this report includes, but is not limited to:

  • Advicy Drive
  • Affectiva
  • Alibaba
  • Apple
  • Beijing Xiaoju Technology
  • BMW
  • Bosch
  • British Airway
  • Careem
  • Craft Silicon
  • Denso
  • Didi Chuxing
  • Empatica
  • Fiat Chrysler Automobiles
  • Ford
  • Gentex
  • Gestigon
  • Grab
  • Honda
  • Jaguar Land Rover
  • KLM Royal Dutch Airlines
  • Lexus
  • Media Lab
  • Omron
  • Outerspace Design
  • Panasonic
  • Sober Steering
  • Softbank
  • Synaptics
  • Tencent
  • Thanko
  • Uber
  • Vigo
  • VoicalZoo


Primary research with a holistic, cross-domain approach

The exhaustive primary research methods are central to the value that the analyst delivers. A combination of questionnaires and on-site visits to the major manufacturers provides a first view of the latest data and trends. Information is subsequently validated by interviews with the manufacturers' suppliers and customers, covering a holistic industry value chain. This process is backed up by a cross-domain team-based approach, creating an interlaced network across numerous interrelated components and system-level devices to ensure statistical integrity and provide in-depth insight.

Complementing primary research is a running database and secondary research of industry and market information. Dedicated research into the macro-environmental trends shaping the ICT industry also allows the analyst to forecast future development trends and generate foresight perspectives. With more than 20 years of experience and endeavors in research, the methods and methodologies include:


  • Component supplier interviews
  • System supplier interviews
  • User interviews
  • Channel interviews
  • IPO interviews
  • Focus groups
  • Consumer surveys
  • Production databases
  • Financial data
  • Custom databases


  • Technology forecasting and assessment
  • Product assessment and selection
  • Product life cycles
  • Added value analysis
  • Market trends
  • Scenario analysis
  • Competitor analysis