As Part 1 of this series explained, the dramatic difference between service that a horse (with no driver) can provide compared to what a shared-ride taxi or paratransit service can provide is the latter’s complexity. To be truthful, I was not born with this understanding. But I learned it – possibly before almost anyone in our country – by virtue of a USDOT-funded project I was lucky to direct – the first nationwide study of special transportation systems for elderly and disabled individuals, resulting in my authorship of a three-volume manual about “paratransit service,” two volumes of which the USDOT published in 1981. (The third volume – actually Volume 1 – was not published because the USDOT’s publishing budget dried up before it could print the last 22 documents written for it. Volume 1 of my study (case studies of the 30 systems in 18 cities that we examined) among them.
The study found that two of the 30 systems we examined (Ft. Lauderdale, FL and Portland, ME) had at least discovered some rationale to use in actually designing a system, while only one – Tulsa, Oklahoma – had the good fortune of having been designed by a single brilliant individual who managed to identify those factors that related to efficiency in demand-responsive service, and to structure his system in accordance with them. One can find the essay I wrote identifying these principles and explaining why they led to Tulsa’s extraordinary efficiency – 10.8 passenger trips per hour – on my website, transalt.com (see https://transalt.com/principles-paratransit-system-design/) – which also includes a nasty section about Uber and Lyft, noting them and part of the largest, most extensive and diverse criminal enterprise this country has ever seen (see https://transalt.com/uber-lyft-and-other-tncs-are-part-of-the-largest-most-extensive-and-diverse-criminal-enterprise-this-country-has-ever-seen/). To be fair, Uber has managed to enter roughly 70 additional countries, with roughly 200 million users per month in 2025. In contrast, Lyft – operating similarly, but evidently with a smaller budget, operates in only 11 countries, following its acquisition of FREENOW in July 2025. (Before then, Lyft was effectively a domestic U.S. entity.)
Uber spun off a relatively popular, thick book, Super Pumped: The Battle for Uber, by NYTimes writer Mike Isaac, published in 2019. Mostly about the exploits of Uber’s initial entrepreneur, Travis Kalanick, I recall finding two sentences in the entire 408-page book that bore any relation to anything in transportation. The single exception was occasional references to “response time” – the time between which a would-be user summoned a vehicle (through an app) and the arrival of the nearest vehicle to the location of the party summoning it. Where that vehicle had to go was another story: Because this system was only about making money and had little regard for either its passengers or its drivers, the driver of the vehicle summoned was not informed of the customer’s destination until the vehicle arrived and the customer boarded. In contrast, taxi drivers ask about destinations, and for any number of reasons, may decline a trip. But the percentage of pedestrians run over by Uber and Lyft drivers pushing the envelope by the uncontrolled greed to make as much money as possibly appears to greatly exceed mowed down by taxis.
While the owner of the Uber empire, and his crackerjack staff of coders who understood nothing whatsoever about public transportation (other than some rudiments like the fact that the “system” required vehicles, drivers, fuel and maintenance), they did understand one factor about their service – a factor that differed little from that of any other product or service: The quicker the vehicle arrived after it was summoned, the more its users would value it.
Perhaps not understanding the concept of density, Uber (and perhaps Lyft) stumbled on the fact that the more vehicles it had in a given service area, the quicker the nearest one to a customer who summoned one could get to him or her. Where density comes in is (to me at least) the fact that a service area with the greatest number of vehicles – which I refer to as fleet density – the most popular it would become.
Of course, Uber benefitted by a characteristic unfortunately responsible for the success of countless U.S. enterprises, and I’m sure for many in other countries: Corruption. At the time Uber first entered New York City, in 2010, the value of a taxi medallion. on the open market, lay between $600,000 and $800,000. Because at that time, the number of additional vehicles one would buy to enter the market was stifled by the fact that there was only enough of a demand to keep the City’s 13,000+ taxis in business – without beginning to starve the overall fleets’ owners by exceeding the demand for vehicles. But this dynamic was of no interest to either Uber’s CEO at the time, Travis Kalanack, or former New York Mayor Bill DeBlasio. So, by 2015, when the value of taxi medallions had increased only moderately from their value in 2010, Mayor DeBlasio had allowed 15,000 Ubers into the City. Yet while their service was almost indistinguishable from that of taxi service (with the single exception that one could summon one with an app whereas calling for one by phone – in a country where getting the telephone live had largely died, as a custom, in the late 1980s and early 1990s — at least in major cities). But the real differences were significant:
- Uber drivers did not have to siphon off much of their profits to pay off the balance of the exorbitant taxi medallion fee – so they could survive, handsomely, even with the lesser profits available as the combined number of taxis and Ubers (and a few other less companies like Lyft, and a few short-lived start-ups like Juno and Gett had only tiny fleets in New York City – if they had any at all)
- Decimating the City’s own taxi fleet by swamping the City with vehicles whose drivers kept 80% of their income (although they had to use their own vehicles, and pay for the insurance, maintenance, fuel and everything else that came with operating such a vehicle), the City’s taxi fleet had not expanded. Worse still, the number of taxi riders plummeted by about 10% that year, but by lesser but still substantial percentages since 2010.
- Uber drivers did not have to lease their vehicles from taxi owners (although a small number of drivers owned their own vehicles). Instead, all Uber driver simply used their own personal vehicles – while when providing rides to Uber customers (this was known as “being on the platform”), Uber paid for their insurance.
Beyond these advantages, the greatest advantage came from outnumbering the City’s taxis. For this increased density translated into increased super-fast “response times” – and faster response times gradually translated into a preference for Ubers over taxis. And Uber drivers soon learned that newer, shinier, cleaner and fresher-smelling vehicles were also preferable to the most used policy cars most typical of the City’s taxi fleet, devoid of competition with these variables. Of course, when recent mayor Eric Adams was in power, he finally capped the number of Ubers in the City. Yet he capped it at 60,000 – when the number of vehicles needed was closer to the 13,000+ taxis operating in 2015. Traffic congestion, and lower salaries (especially for taxi drivers) were the true costs of this “open entry” – more accurately a lack of planning which I suspect, but cannot prove, may be documented by the revelation of some swollen bank account in Bill DeBlasio’s name. But I have no evidence of this, and it is only a suspicion, not an accusation, and not even worthy of a rumor. Just a sloppy guess. But a sloppy guess from someone who read the countless stories in the New York Times and The New Yorker documenting the huge number of taxi drivers whose lives, and families’ lies were ruined by the open-ended deluge of Ubers into the City – a phenomenon that lowered the value of taxi medallions (often purchased by a large, extended family pooling all their resources) from nearly $1M to not much more than $100K – for those foolish enough buy one.
So little by little the density of the Uber fleet increased, and similarly the density of taxis began to decrease. In turn, these differences continued to improve the response time of Ubers, while increasing it for taxis. At some point, these dynamics had to have sunk into at least some of Uber’s thin layer of mid-level management – although it began abundantly clear to all or most of the City’s taxi drivers. A resident of Manhattan during these years, and user of only taxis (for reasons that will be covered in subsequent installments), I asked most of the taxi drivers with whom I traveled what percent of their ridership they felt they lost to Uber. Not usually answering this question directly, most told me that their deadhead time had shrunk from about 60 percent to between 30 and 40 percent. Living “on the margins,” as it were, by having to amortize their taxis’ medallion fees – usually in the form of splitting the “take” with the unfortunate owners of most of the vehicles (also forced to pay the medallion fees) – taxi drivers began starving to death, although more often they were merely forced to operate for more hours, increasing fatigue and placing passengers and fellow motorists and pedestrians at great risk. The old model of working 12-hour shifts six days a week (likely a Federal violation of the FMCSA rules designed mostly for motor coach drivers who could only operate 10 hours a day within a 15-hour span of time [separated by eight hours off duty]) likely changed, unavoidably translating into more carnage.
#ubersafety #uberaccidents #ubercorruption #ustransportatoincorruption #transalt