Maximizing the Movement of People per Unit of Space & Time

September 26, 2018

The image below illustrates the quantity of people who can travel per hour per lane (PPHPL) via various modes of transportation. The figure presents a scenario in which a stadium is filled with people who traveled there using different modes. The blue lane is for buses, the green lanes are for walking and biking (one lane for each), the orange lane is for cars, and the yellow lane is for taxis and transportation network companies (TNCs) or ride-hailing vehicles. The road type (urban arterial in this case) and other factors play a role in estimating road capacity. The graphic adheres to the following inputs:

  • Vehicles per hour per lane (VPHPL) is calculated based on several factors such as road widths, travel speeds, breaking distances, and traffic signals. Calculations were based on research papers and articles on the topic (for example, this Nature article). As such, I calculated 1,200 VPHPL for cars and taxis/TNCs with average speeds of 30–40 mph, and 800 VPHPL for buses with average speeds of 15–20 mph. Regarding space, I calculated 15 square feet (sf) per person walking at 3 mph, and 40 (sf) per person biking at 10 mph.

  • The mileage-weighted vehicle occupancy for cars is 1.5 (based on National Household Travel Survey data), for taxis/TNCs is 0.9 (based on PhD dissertation, vehicle-miles-traveled publication, and current research), and for buses is 40 (while some buses can hold up to 80 people and rail systems can hold even more than that, I used 40 as a conservative estimate and for consistency).




    While the figure illustrates road capacity in PPHPL per mode, it is important to highlight some additional considerations in such a scenario (i.e., where roads lead to a stadium):


    Parking: Walkers and taxis/TNCs would not require parking spaces. Cars would require 1,200 car-size parking spaces, bikes would require 15,800 bike-size parking spaces, and bus parking requirements would depend on how many buses would be circulating versus parked.


    Drop-off Space: Taxis/TNCs and buses require space for dropping off passengers.


    Additional Time: Walkers do not require additional time for being dropped-off or for parking. People arriving via buses, taxis, or TNCs would spend additional time for disembarking and walking to their destinations. People arriving via bikes and cars would spend additional time parking and walking to their destinations.


    Distance and Locations: Walking (and to a lesser degree, biking) is distance limited. Buses are restricted to certain origins/destinations.


    Mode Dependency: Private cars and private bikes constrain people in terms of using other travel modes. For example, if a person travels to the stadium in a private car, the probability of traveling after the event via the same private car is very high, while other travel modes might not be as constrained. This could make a mode such as ride-hailing more efficient—for example, a person can arrive in a taxi/TNC but take a bus, bike, or walk after-the-event.


    Additional Modes: The graph was limited to four modes for illustration purposes. Other modes could be added (e.g., carsharing, bikesharing, or e-scooters) to illustrate related PPHPL.   


    The figure, produced for illustration purposes only, is intended to generate discussion about mobility prioritization and to help identify and solve the right type(s) of problem(s). The figure shows that the modes with the greatest potential to move the most people per unit of space and time usually receive less consideration and infrastructure investments.


    The U.S. Department of Energy, the U.S. Department of Transportation and cities could make great strides in solving many critical issues—traffic fatalities, budget and infrastructure problems, car dependency, affordability, and energy—by re-shaping transportation systems to better capitalize on emerging mobility and efficiently measures —focusing more broadly—on the movement of people and goods, rather than just vehicles.

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    2018 by Alejandro Henao