Uber released a report providing information about user safety in the United States of America in 2018. The report revealed that 3,045 cases of sexual assaults happened during Uber travels in 2018 [4]. Additionally, Uber reported that nine individuals had been murdered during Uber rides and 58 died in car accidents. The figures are the first publicly available data on Uber's e-hailing platform's safety and how it compares to national US averages. Uber reported that of the 3,045 sexual assault instances reported in 2018 (up from 2,936 in 2017), 235 were rapes and the remaining were varied degrees of assaults [4]. According to Uber, the great majority of assaults included unwanted kissing or groping [4].
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General Overview
Type of stakeholder
EICS Framework
Region of Reference
- Africa
- Asia
- Australia
- Europe
- North-America
- South-America
- World
Description
This intervention involves having access to beneficial driver information. Access to this information instils a sense of security in passengers who use e-hailing (or public transport) services. The primary source of danger in ridesharing is from their drivers, and to a lesser extent, from other passengers [6]. Not all ride-sharing services use real-time authentication, leaving fraudsters and criminals with loopholes. E-hailing services have created rapid business potential by enabling individuals to partner with other persons (drivers) to provide trips to clients [6]. However, the riders' safety and security are always at risk. Due to the ease of access and profitability of on-demand trips and e-hailing services, they can attract persons with criminal backgrounds to become driver-partners under fraudulent identities. Currently, e-hailing companies rely on government-issued credentials, such as passports and driver's licenses, to verify the identity and eligibility of their drivers. However, this verification is often conducted only once during the registration process [3].
Other public transportation services face comparable issues when it comes to passenger safety, particularly in non-government-regulated informal public transportation systems. Traffic cops are required to conduct vehicle verification on a regular basis and stopping a driver and personally validating each document is a time-consuming operation [8]. It takes a lot of time and work and determining the legitimacy of the documents is challenging.
Face recognition biometric verification is a widely used technique for real-time identification verification internationally. Artificial intelligence-based solutions for identity verification and geo-location screening assist in mitigating the danger of onboarding illegal drivers, who could jeopardize the service’s credibility. Comprehensive driver screening is critical, and a single test is insufficient in this profession.
Continuous verification by biometric screening is a viable method of mitigating fraud risk in the e-hailing market. This type of intervention would reduce crime if both drivers and riders were required to use the biometric to identify themselves prior to accessing the service; consequently, passengers would be needed to produce their government-issued IDs or biometrics as well [4].
Certain e-hailing companies have introduced selfie check-ins for drivers to verify their identities before they begin picking up passengers, buttons for reporting rides that appear to be deviating from the route, and options for rapidly contacting authorities in the event of an emergency [5]. Uber has enhanced its safety mechanisms to protect drivers from criminally prosecuted riders in South Africa, while also beefing up security measures to safeguard riders against shady drivers who may access the platform via 'rented profiles' [1]. Uber's general manager for Sub-Saharan Africa stated that the company had implemented a rider authentication function that requires new cash riders to link their rider profile to an existing Facebook account [1].
The usage of QR codes is another method for authenticating driver identification. QR codes are two-dimensional barcodes that are simple to use and create. They can link a limitless amount of data, allowing you to easily encrypt the driver's information [8]. The pandemic fuelled a surge in the use of QR codes to cut down on possible transmission [9]. They're simple to scan with a smartphone camera. As a result, QR Code technology can aid in the vehicle certification procedure [8]. You can add important information to the QR Code to improve the verification process. This information could contain the driver's contact information as well as their registration certificate.
Facts/Illustrations/Case studies
Types of Impact
Area Impacted
- To/from the stop/station/rank✕
- Waiting for train/bus/paratransit✕
- In the vehicle✓
- At interchanges✕
Time of Day of Impact
- Day-time travel✓
- Night-time travel✓
- Peak-time travel✓
- Off peak-time travel✓
Mode Impacted
- Bus✓
- Train✕
- Rideshare✓
- 4 wheelers informal✓
- 3 wheelers informal✓
- 2 wheelers informal✓
- Cycling✕
- Walking✕
Demographic impacted
- Girls✓
- Boys✓
- Adult Women✓
- Men✓
- Elderly Women✓
- LGBTQI+✓
Resources
SWOT Analysis
Convenient and fast to use
Improvement in user experience: information makes it possible for users to feel secure when using the service
Non-transferrable. Everyone has access to a unique set of biometrics.
Potential for data breaches
Invasiveness and privacy concerns
The existing research on Mobile e-ID implementation barriers is limited.
To aid in apprehending more offenders
Technology is constantly evolving, making implementation simpler, quicker and cheaper
Bias – Machine learning algorithms must be very advanced to minimize biometric demographic bias
Unproven performance factors of false acceptance and rejection rates
Database needs to be updated frequently
Scammers are building their own dangerous QR codes to trick unsuspecting customers into divulging their banking or personal information.
Effectiveness
Based on the significant amount of literature reviewed, there is the confidence that this intervention can be very effective, as users’ perception of safety increases after implementation.
- Perception by (female) passengers
- Perception by governing bodies
- Level of confidence in these ratings
Implementation
Implementing this intervention initially takes time, as consumers require a grace period to register new biometric information, especially when the service is first provided. The benefits are instantaneous, but this is partly contingent on how quickly users begin reporting their biometrics following implementation. The QR code is simple to use and implement and it provides immediate benefits, depending on how quickly it is implemented.
Implementation timeframe
- 0-1 year✓
- 1-3 years✓
- >3 years✕
Timeframe to realise benefits
- 0-1 year✓
- 1-3 years✓
- >3 years✕
Scale of Implementation
This intervention can be implemented at a station/suburb or city level.
Suburb
Ease of Implementation
This intervention takes a moderate amount of effort to implement, as it requires a moderate amount of time and some political backing.
List of References
Africa
1. Mlambo S. How e-hailing platforms are using technology to make trips safer for riders, drivers. IOL News.
Asia
2. Tang Y, Guo P, Tang CS, Wang Y. Gender-Related Operational Issues Arising from On-Demand Ride-Hailing Platforms: Safety Concerns and System Configuration. Prod Oper Manag. 2021;30(10):3481-3496. doi:10.1111/poms.13444
Europe
3. Gupta S, Buriro A, Crispo B. DriverAuth: A risk-based multi-modal biometric-based driver authentication scheme for ride-sharing platforms. Comput Secur. 2019;83:122-139. doi:10.1016/j.cose.2019.01.007
North America
World
7. World Bank. Understanding Cost Drivers of Identification Systems. Underst Cost Drivers Identif Syst. 2018. doi:10.1596/31065
8. Bhatia, S. (2021, December 30). QR Codes For Vehicle Verification: A Detailed Guide. QR Batch Blog.