Forever a Student Driver? Data Monitoring in the Trucking Industry

This blog explores the future of data mining in the trucking industry. Although at first glance, monitoring the brain activity of a driver might appear to be a gross violation of privacy, it may be a better alternative than current regulatory standards.

Over time, society has become increasingly comfortable with employers leveraging technology to monitor the quality of their employees.  In a world riddled with subconscious biases, the idea of an employer utilizing objective metrics such as emails sent, meetings attended, words typed, etc. appears enticingly politically correct to an employer wishing to proactively mitigate human resources scandal. However, what happens if one does not have a regular desk job? How should society think about the ethics of leveraging biological metrics if one occupies a blue-collar, physical job? One interesting case study investigates the introduction of technology in the trucking industry.

Unless you are somebody who prefers isolation and long hours, being a long-haul trucker is quite a grueling job. Although hourly pay is not a common occurrence, long-haul drivers are typically paid overtime. The maximum allowable overtime is capped by United States regulations.  Currently, truckers are only allowed to drive a maximum of 14 hours before taking a required 10-hour break. Additionally, truckers are not allowed to drive more than 70 hours in an eight-day period [1]. This incentive structure results in many truckers pushing their bodies to drive up to the maximum allowable hours per eight days.

Being human, the truckers have their biological limits and need sleep. Being businesspeople, the employers of these truckers want to monitor the drive time of their drivers in order to minimize costs incurred (in the form of overtime payment and fines incurred should a driver attempt to work longer hours than required). This led to a law passing in 2015 and being implemented in 2017 requiring all drivers to equip their truck with Electronic Logging Devices (ELDs). In short, these devices provide an objective measurement of a driver’s productivity and risk by logging things like hours driven and speed [2].

Although it is generally accepted than more data can lead to a more efficient operation, in this case, it has created a tricky situation in which two parties have conflicting opinions of the true intention behind requiring ELDs. Employers view their implementation as mutually beneficial. On one hand, they will have certainty that their drivers are not lying on their logbooks or working too many hours thus risking fines. Additionally, they believe that they have their drivers’ best interests in mind as they can now ensure they are taking an adequate amount of rests. On the other hand, drivers see ELDs as an invasion of privacy that limits their ability to perform on the job. By forcing a time limitation, drivers may feel the need to speed in order to make up for any loss of time due to unforeseen circumstances. In the case of one driver, Trevor, “I was five minutes short on time, and I was trying to make up five minutes so I could see my family…” [3]. This resulted in Trevor making the decision to speed through a turn and ultimately crashing his truck.

How can the data collected, and the data collection process, be refined to mitigate against this risk? After all, drivers are people and people have different thresholds for when they are too tired to safely perform their job. One potential solution is the SmartCap. The SmartCap is fitted with EEG monitoring to detect signs of sleepiness or fatigue [3].

While I acknowledge that technology like the SmartCap appears to be a huge overstep in data privacy, I feel that it is ultimately necessary in the case of long-haul trucking. I feel that having no firm regulation incentivizes employers to abuse their truck drivers by demanding unrealistic delivery times. At the same time, I feel that as the regulation stands, incentives are still not aligned. However, careful thought must go into the creation of the regulation. Given the sensitivity of the data, I feel it should be limited to use only while the driver is in the truck and on-the-job.


[1]: “Truck Driving per Hour Salary.”

[2]: “ELD Facts.”

[3]: “The Quantified Employee: How Companies Use Tech to Track Workers.”


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Student comments on Forever a Student Driver? Data Monitoring in the Trucking Industry

  1. Agreed to your point about limiting data collection to when the driver is on-the-job – but I also think that access and use has to be limited. I worry about any employer having access to data that could potentially uncover a health problem or condition; this opens up so many opportunities for discrimination (especially when employers are providing health insurance). For this reason, I think that SmartCap needs to take on the data monitoring themselves, rather than ever giving the employer access to the data.

  2. I have no doubt that there are enormous benefits to this technology (fewer accidents, driver wellbeing, etc.); however, I agree with TFD that SmartCap must take on data monitoring themselves. If I were SmartCap management, I’d take this one step further and develop our own set of regulations for how we treat privacy and security. I’m of the mindset that if you don’t regulate yourself, you’ll eventually get regulated. With that in mind, I’d publish these principles to the general public and solicit feedback from various stakeholders, most specifically labor unions that represent truck drivers.

  3. Thanks for an interesting post, John! I agree with the points above SmartCap controlling the data and working with various stakeholders to determine the best way balance effective data use with privacy. In addition, I think that SmartCap could work with employers and drivers to use the data even more proactively. They could use anonymized SmartCap data across drivers (and even companies) along with other data sources to identify patterns that may explain or predict driver fatigue before it happens. For example, are there certain routes that are take longer than planned? Is training or intervention x useful in reducing the number of drivers that stretch beyond their limits? Can we nudge this driver to consider whether they are too tired to make this journey? Though the misaligned incentives will persist, and are certainly strong counterforces, these kinds of predictions may help both companies and drivers make safer decisions.

  4. Thank you for sharing, John! My uncle drives trucks and it always made me sad when I learned about the tricks of the trade for helping yourself stay awake during long hours on the road (one trick is to tickle the top of your mouth with your tongue). Though the invasion of privacy of SmartCap does seem more severe than the ELD technology given the introduction of biometrics, I do think it is the more responsible option in this case. The initial intent of the ELDs was to make sure drivers were taking the proper amount of rest in order to adhere to proper levels of safety. We also saw from drivers like Trevor that this can backfire, putting that very safety on the line. With SmartCap, we get right to the initial intent of putting any measure in place- to make sure the driver is alert and rested enough to drive safely. It reminds me of ignition interlock devices that prevent a driver from starting their car depending on what they blow into a built-in breathalyzer. What I find interesting is the question of how to act on SmartCap data. If the SmartCap detects a driver too sleepy to drive, what should happen? Should the truck not start? What if a driver changes from being alert to sleepy while driving? Should an alarm sound urging the driver to pull over? Or should it be up to the driver to change their behavior based on SmartCap readings, and just be subjected to fines if they drive while below a certain alertness level?

  5. Great article John!

    There’s a tension between being efficient and being safe. From employers’ perspectives, they want to keep pushing efficiency to the limit, given the competitive environment.

    If we take a perspective of how truck drivers process, they would have to give in the input (driving time, driving behavior, rest time, etc) through the process (driving, speeding, following regulations) to generate the outcome (efficiency, being on time, etc.) . Traditionally, drivers were given flexibility in their inputs and processes, and employes measured outcomes only. This method leaves rooms to the drivers to manage their driving behavior, speeding, and following regulations. Once the tracking machine has been introduced, now we measure process and outcome at the same time, which could cause backlash to what input they have to innovate. As a result, we have witness a sad example of the driver you mentioned.

    Now, my bigger question to this is … the more we push for efficiency, the more privacy and risky lines we are crossing. How far, as a future business leader, should we cross? Or at least make the society push back. Is it the regulator job? I hope the regulator could act on our behalf.

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