Solving Local & Regional Transportation

We can all agree. Traffic sucks. There’s nothing like an unexpected accident to take the wind out of your sails. If it’s not an accident, it’s someone ahead of you driving erratically, causing folks behind them to brake, which propagates back three miles to a point where traffic grinds to a halt.┬áPlus, these days over 75% of cars on the road have one occupant (the driver). The roads are full of nearly empty vehicles.

According to NHTSA, 95% of all crashes are due to human error. That’s an astonishing number. Imagine if all or most of the drivers on the roads were commercially certified, meaning they all passed a more rigorous rules and skills test than the average state driving test. We certainly can’t add more bus routes and hope folks decide to take the bus. We need a radical shift in the public perception of transportation. Instead of a fixed-route, schedule-based system with a relatively small number of high capacity vehicles, we need a larger number of medium capacity vehicles running on-demand passenger pickup and drop-off. More vehicles means more jobs. Plus, we’re taking barely skilled drivers off the road and replacing them with highly skilled drivers.

So, how do we achieve this? What are the key problems, and how might we solve them?

1. Matching Vehicles with Passengers (Technical)

If you visualize the road system as a giant sea of intersections (vertices) with roads between them (directed edges), then a passenger travel request (“take me from here to there”) is simply a polyline (series of vertices and connected edges) through the vertex space. This represents the path, from intersection to intersection on the roadway, this passenger must travel to reach their destination. In the same way, a vehicle has a set of passengers whose collective paths combine to form the vehicle’s path.

When a new request is created, its path segment is matched against those of nearby vehicles. The goal is to successfully transport every passenger from their current location to a given destination, ideally using the least amount of time and fuel. The system can not simply assign the nearest vehicle, as that may not be the best choice. Conversely, the system can not be required to find the best choice every time, as that is computationally unrealistic. Reasonable matches also take other factors into consideration, such as vehicle vacancy, groups of passengers traveling together, and facility requirements, like wheelchair lifts.

With a central system performing all the matching, this problem could easily get out of hand as total number of vehicles and passengers increases. Instead, the proposed system takes advantage of distributed processing to reduce the computational burden on the central dispatcher. Passengers submit requests to a dispatcher, which finds any vehicle within 10mins of the passenger’s current location. Each of these vehicles is then asked to submit a bid to add the passenger to their manifest. The dispatcher chooses a bid (not necessarily the lowest one), assigns the passenger to the winning vehicle, and notifies both by SMS or push notification. Once notified, the vehicle and passenger devices can communicate directly, without any interaction with the dispatcher.

2. Inspiring Passengers to Ride (Social)

This solution is doomed to fail unless there is enough passenger demand in any given region. If folks don’t know about the service, they won’t be able to use it. Building awareness is difficult and expensive. Additionally, if they don’t have smart phones, they won’t have access to the app to tell the system they need a ride. They can not convey their current location or select a destination, nor will they receive notification when their vehicle is nearby. There must be a plan to support people who do not have smart phones.

The best approach to building awareness seems to be targeting event coordinators. These are people already organizing a bunch of attendees in one place, managing caterers, and overseeing venue logistics. If they could hand off the transportation responsibility to an on-demand driving service, that’s a huge value add to their attendees, especially if there is alcohol served at the event. This also has the added benefit of eliminating the parking requirements for the event. After a few successful events in a region, people will begin to naturally advertise the service through social networks. At that point, we approach the taxi and airport shuttle companies to adopt our standards.

3. Convincing Existing Transportation Providers to Join (Political)

The big companies currently serving the bus and taxi transportation sector are going to be quick to dismiss this as a fad or an impossible goal. The politicians’ spending decisions are heavily swayed by influential players, like the companies providing municipal bus service for the area. In fact, most of those companies operate on a subsidized basis, with some of their annual revenue coming directly from local and regional government.

By partnering with existing research initiatives at private and state universities, we gain additional influence that will hopefully lead to buy-in at the government level. That ultimately leads to grant funding and improved liquidity to cover operational expenses, the bulk of which will be driver payroll and new vehicle acquisition.

4. Balancing Service Offering and Price (Financial)

The primary purpose of this system is to improve people’s lives. That means they must achieve their current goals with reduced price or increased convenience, or both. Also, folks who already have made an investment in a car will be apprehensive to spend even more money to use a different system. This could be a cost-per-mile fee or a monthly or annual subscription. It could also be a co-op, where participants offer their vehicles as part of their buy-in, in exchange for a discounted membership fee. Maybe vehicle owners can even go one step further and get paid to drive other passengers around, and/or have those miles count as credits, so the next time they need to go somewhere, they’ve prepaid for that trip.

In the end, there are two primary factors in the operational budget – cost-per-mile and cost-per-hour. Some costs are on a per-mile basis, like vehicle maintenance and fuel. Other costs are on a per-hour basis, like driver salary. With just a little information about operational expenses for existing transportation companies, it should be possible to determine a rough range for per-customer costs. These costs then become a lower bound for the consumer price.


Walking vs Driving a VW XL1 – A Thought Experiment

Allegedly, the Volkswagen XL1 gets up to 300mpg on diesel. I’d like to compare that against a best guess for the average mpg (energy equivalent) of a human. I’m doing this purely on total available energy, not any formal Gibbs free energy analysis. Mostly because I don’t have enough empirical energy on human energy conversion, so I’m going on the USDA 2k calorie daily recommendation.

I’ve heard, though never formally confirmed with an authority I trust, that a dietary calorie is actually a kilocalorie, which is 4.18 megajoules (MJ). So, that’s a general upper bound on the available energy in a human “fuel tank”, assuming we derive energy exclusively from food and we eat an average diet, calorically speaking.

Diesel fuel has an energy density of 45 MJ/kg. That means, at roughly 3kg/gal, 135MJ available in a gallon. Interesting that a gallon of diesel contains over 32 times more energy than a typical American human consumes in a day. If the XL1 can go 300mpg, that’s 2.22 miles/MJ or 450kJ/mi.

The average brisk walking speed is about 4mph. If I were to walk all damn day, breaking only to sleep and eating while I walk, I could theoretically walk 64 miles. Over that distance, I would have used 4.18 MJ, which works out to 15.3 miles/MJ, or 65kJ/mi.

Assuming all this math is right (which is likely dubious), the automobile still has a long way to catch up. But, then I’m not factoring in the well-to-wheels analysis for production and distribution of the fuel, nor a field-to-feet analysis for the production and distribution of the food.