Recently I berated a hotel in Shanghai for not welcoming pedestrians from a corner. I have since come across a McDonald’s, shown in the images, which makes an effort to welcome pedestrians from the adjacent intersection, with an opening at the corner, and a clearly delineated and non-circuitous pedestrian path across the driveway to the otherwise typical and un-urban store configuration.
I don’t know the history, I imagine there was once a typical corner hotel/pub that for whatever reason (abandonment, fire, changing market) became a McDonald’s site. The planners insisted on maintaining the semblance of urbanity at the corner, and this was the compromise. One day there will be a real building again. Until that day, I have seen far worse.
Today we have cars. In 30 years we will have cars. But in the meantime, some cars will will driven by humans and others not, and there will be terms to distinguish them.
Today, most people use the terms Autonomous, Automated, Self-Driving, and Driverless as interchangeable. Even wikipedia does not differentiate. Yet some people in the field make a point of the differences (e.g. Alain Kornhauser). If I understand these differences correctly, a self-driving car is not as advanced as driverless, in that driverless doesn’t have the back-up of a person taking control, and self-driving might. Driverless taxis are not merely self-driving, they pick up passengers and may be personless. In SAE terms, driverless is Level 5, while self-driving is Level 4 or below.
Generally, the difference between automatic (or automated) and autonomous is the degree of human intervention. An automated car does not have the level of intelligence or independence that an autonomous car has. So driverless and autonomous are nearer to synonyms, as are self-driving and automated. A truly autonomous car would decide on destination and route as well as control within the lanes. An automated car would follow orders about destination and route, and may only adopt some lane-keeping or car-following guidance.
Nevertheless, I do not believe these differences can be preserved linguistically, even within the profession, the broad misuse and confusion will drown small differences of meaning.
Etymology online gives the following:
autonomous (adj.)1800, “pertaining to autonomy;” 1804, “subject to its own laws,” from Greek autonomos “having one’s own laws,” of animals, “feeding or ranging at will,” from autos “self” (see auto-) + nomos “law” (from PIE root *nem- “assign, allot; take”). Compare privilege. Used mostly in metaphysics and politics; see autonomic. Related: Autonomously.
The most unique aspect of the transport scenery of Shanghai is the famous Maglev, providing service between Longyang Road, somewhere in Pudong, and the Shanghai-Pudong airport. Operating since 2003, it is a technological, if not economic, proof of concept that Maglev can function in revenue service. The ride is smooth, as can be seen on this video I shot looking out the side window. Because of the double paned glass and reflectivity, you can see some of me, and some of the iPhone camera reflected back, but you get the idea. The speeds steadily increase, and than decrease, with no passenger discomfort. It is not especially loud.
On a Sunday afternoon, the train was far from full. And though I did not get to ride at the highest speed offered (430 m/h) (which would have required taking an earlier train), it was plenty fast at 300 km/h. The fare was a reasonable 50 yuan ($AU 10), though taxi would have been cheaper, and probably faster door-to-door given the ticketing and waiting times. The station is in the middle of nowhere (i.e. in the middle of future redevelopment), across from a big box shopping center. It runs parallel to a conventional metro line, which is slower, with stops, but more frequent. It does land you conveniently in the middle of the airport, between the terminals, so is useful from that perspective.
The first adventure was taking the taxi from my hotel to the Maglev station. The taxi driver spoke no English, I spoke no Chinese, but he moved his arm really fast and said zoom-zoom, so he understood.
The second was actually finding where to be let out. This is not at all obvious, and we wound up spiralling into a place that sort of resembled a taxi drop-off point. I am not clear how passengers actually arrive, this could not have been it. I am guessing public transport, but the ‘landside’ layout of this airport was odd.
Otherwise, it was more like a small train station than an airport, except it required special ticketing. The ticketing vending machines had an English option, so that was straight-forward. The security was on par with the Metro, requiring a scan of bags you are carrying.
While undoubtedly there were a few transport tourists like myself, my sense is that some of the riders were regulars, finding it slightly more convenient than the alternative. Given that it was a slow time at the airport, the lack of demand on the MagLev may just reflect peaking patterns rather than avoidance.
All in all, a smooth convenient ride, akin to a monorail, which casual empiricism suggests will not be the technological path selected for fast surface transport. Even though it works, it has not been much replicated. If you are interested in transport, and in Shanghai, and it seems to be an option to go to or from the airport, you should try it. However in all likelihood, you will still need another mode of transport to get you to your destination or from your origin.
We have long had inter-vehicle connectivity. The means are slow and loud: the horn and the turn signal, as well as eye contact between nearby drivers. But they are widely used despite their minimal effectiveness.
Horns have a variety of purposes. In the US, the horn is most commonly used to express the following sentiments:
“Move you idiot“, for instance, when the light changed colour.
“You are cutting me off,” we might get in a collision, and my pressing the horn, while pressed far too late to avert said collision, releases some frustration.
“You bastard, you are in my right-of-way and I am too lazy to tap the brakes, but not too lazy to hit the horn” (Alternatively “I’m an asshole, and I want the world to know it”)
In developing countries, horns have other uses.
I’m changing lanes … not merely, “I am requesting permission to change lanes,” but the more active, “I’m changing lanes and you have been forewarned.”
“I’m coming around the sharp corner with little visibility, but sufficient audibility, at too high a speed to safely brake, and don’t care to reduce my speed to a safe speed, you have been forewarned.”
Turn Signals also have their uses. In developed countries, the turn signal indicates
“I’m would like to change lanes, if a gap opens up, I might take it.”
In developing countries, I have observed the turn signal, particularly at steep uphill grades indicating, as near as I can tell:
“You should change lanes. Really, I won’t be offended, I have a heavy load I am carrying up this hill and my vehicle cannot maintain speed, and there don’t seem to be any. oncoming cars right now, though I am not liable should there be one”
This dual usage of turn signals is analogous to the awful Minnesota expression “Can you borrow me some money” which is normatively incorrect ( with a clear enough meaning) and just grates on the ears. I borrow, you lend. I lend, you borrow.
It is sometimes argued that Connected Vehicles, with a real-time broadcast of a here-I-am message could replace the horn (HEAR! I AM!) and turn signal (see me! I am!, vocalised in a quiet Horton Hear’s a Who voice no louder than a clicking turn signal contact)., But this assumes CVs were universal, and pedestrians and bicyclists were connected too (or have simply been eliminated, Wall-E style). Short of that, the horn particularly, which is almost sure-fire in annoying walkers and bikers, remains relevant as a way of forewarning.
Now of course, an automated vehicle wouldn’t be (shouldn’t be) going around sharp corners at too high a speed, so AVs could eliminate excess noise through better behaviour. Horns in retrospect would also be eliminated. AVs could possibly infer the dual meaning of turn signals from context and vehicle behaviour. After visiting China, it is clear AVs would not work in the Wild West of Wuhan, but are much more feasible in modern Shanghai, where pedestrians and bicyclists are much more likely to be rule abiding. Certainly over time, as developing areas are civilised into the ways of modern motordom, this issue will diminish. But it needs to be kept in mind that the context shapes the effectiveness.
While urban noise levels will likely decrease with advances in technology, this is due to the automation, not connectivity.
I have long felt the solution to much noise in urban environments is to blast the horn inside the vehicle. That way, whenever someone slammed the horn, they would internalise much of the noise externality they create, leading to less noise production in the first place.
I rented a Toyota Corolla with a local “carsharing” operator GoGet on Saturday. This was for the sole purpose of driving on the wrong side of the road. I figured it was time to get some behind the wheel experience, with no family members sharing the car with me. I managed to live in London for 10 months, and Sydney for over 2 months without getting behind the wheel on the wrong side, but I plan a road trip next week, so practice helps.
I didn’t turn into the wrong lane, killed no one, so overall it was probably a success. But I still had two issues with driving that I had not thought about before.
I kept hitting the windshield wiper instead of the turn signal. The turn signal is on the right side of the steering wheel (as opposed to the left in a car with left side steering like in the US). So the steering wheel is on the opposite side, and the turn signal is reversed as you might think it should be. It is thus operated with the right rather than left hand which requires unlearning. Note gas and brakes are on the same position (gas on the right, brake to its left). So it is an imperfect mirror experience.
I cut left turns too sharp, and the tire might have touched the curb. As far as I could tell, I was properly in my lane when driving, though cutting the curb indicates I may have been too far to the left on multi-lane roads, no-one honked at me.
The difficulty is learning to drive while also learning to navigate, in a car you quickly leave the area that you are familiar with from walking about, and are in new areas. I drove down to La Perouse, mostly via the Anzac Parade (where the second LRT in Sydney is being constructed) just as some place to go, though I had never been there. I strongly believe learning to drive and learning to navigate should not be done simultaneously. (Just as learning to drink should occur before learning to drive). Yes I had my cell phone map and the silky navigation voice telling me what to do. Unfortunately the car did not have an in-vehicle navigation system, which as bad as they are, at least display a map. Since Sydney is not a grid system, directionality is not obvious.
Aside from the GoGet sign-up experience (they required an Australian mobile phone number to sign up, and I didn’t get one til a few weeks ago since my US plan worked fine for everything else, and was better for international roaming in places like China), everything else seemed to work fine. GoGet is more of a station-based, Zipcar like experience, but it is far more popular than Zipcar was in Minneapolis, so there was a car a block away rather than a mile and a half. Rental durations are determined in advance, though can be extended. So 2 hours was about $21 + $0.40/km (rates depend on the plan you choose, which trade off fixed costs of membership for variable cost per trip), which at 25 km round trip gives a driving lesson cost of $31. These rates seem high, and requires careful planning of trip duration, so I suspect carsharing will be a rare occurrence, and transit and taxi (Uber/ridehailing) more frequent.
Some intersections are riskier to cross than others, but looking at the number of pedestrian injuries alone doesn’t tell the whole story. A new study from Minneapolis combines crash data with pedestrian counts to deliver a more nuanced picture of traffic dangers for people on foot. Among the findings: There’s safety in numbers for pedestrians.
Using data from the city government, University of Minnesota researcher Brendan Murphy and his co-authors looked at 448 intersections where both pedestrian counts and automobile counts were available, then cross-referenced that data with the city’s crash reports. They found a strong negative correlation between the number of pedestrians and the risk of being hit by a car.
While the study found people are less likely to be struck by a driver at locations where lots of people walk, it does not establish causation, Murphy says. “We don’t have good statistical evidence to show that if a place is safe, people will walk — or in the other direction, that if people are walking, they make the place safer,” he says. “I personally think it’s a bit of both.”
Per person, pedestrian-rich areas downtown and near the University of Minnesota pose a low risk for people walking, though they have a high absolute number of pedestrian crashes. Quieter intersections in more residential neighborhoods also pose a lower risk.
A few streets jump off the map as high-risk areas, like Lake Street, which runs east-west across South Minneapolis, and Penn Avenue in North Minneapolis. Both are used by a steady if not enormous number of pedestrians, but are meant first and foremost to move lots of cars. “We can ask, ‘How are those roads designed?’” Murphy says. “They are two lanes each way, no shoulder or bike lane.”
The study looked at all crashes involving pedestrians, not just injuries and fatalities, in order to include enough data points to reach reliable conclusions. It also looked at the stats from 2000 to 2013 in aggregate, rather than year-by-year, so it doesn’t take into account intersection redesigns or major changes like the opening of a light rail line. If there were enough data, Murphy says, “it would be really nice to do a year-by-year analysis.”
The study did not consider the relationship between pedestrian risk and income or race, but the authors say that needs attention. “Equity is a very big problem in terms of pedestrian safety and poor and minority people are getting killed by cars at much higher rates,” Murphy said.
The authors hope their research will lead to better measurements of pedestrian safety and methods to improve it. In 2016, the U.S. Department of Transportation’s four-year strategic plan set a goal of reducing fatalities for pedestrians and cyclists to 0.15 per 100 million vehicle miles traveled by 2016. But that’s the wrong way to look at the problem.
“If we frame pedestrian deaths in terms of VMT, we’re really framing it in terms of automobiles themselves and car traffic,” said Murphy. “We should be focused on reducing pedestrian deaths as a percentage of the pedestrian population.”
There’s also a need for better data collection. Cities and states regularly collect standardized data on car and truck traffic, but there’s no standard for non-motorized users. This data is often collected manually and its reliability varies from city to city. In Minneapolis, three counts throughout the day at each intersection were added together to create a six-hour total. Other cities have different methods.
“Ideally we would like to have our cities wired up and know how many pedestrians are crossing each intersection,” Murphy says. “We need to focus in on the pedestrian population and really ask ourselves, where are they really experiencing undue burdens of risk and what can we do about it?”
Transportation System Analysis for Better Policy-Making
The rise of shared mobility, manifested by services such as car-sharing, ridesourcing, bike-sharing and crowdsourcing delivery, is fundamentally changing the landscape of travel and transport. As the vehicle automation and connectivity technology matures, these shared mobility services could eventually evolve into a powerful alternative to the current model of car ownership. Moreover, the collective ownership, being more rational and having a greater bargaining power for infrastructure improvement, may favor electricity as the primary fuel due to much lower operating and environmental costs. These three trends, namely sharing, automation and electrification, have occupied much of the ongoing research efforts in the field of transportation in recent years. As researchers begin to engineer the next generation of analytical tools tailored to these emerging conditions, a daunting challenge is how to apply these tools to properly inform public policies pertinent to design, operations and management of the future transportation systems. Because policies typically aim to achieve certain societal goals by influencing human behaviors, policy making processes must anticipate complex policy-human interaction and take their effects into account. It is this particular challenge that the present Special Issue of Transportation is focused on. Specifically, submissions that broadly fit the following profile are most welcome:
Addressing a system application related to one (or more) of the following themes as explained above: sharing, automation and electrification;
Employing a quantitative system analysis tool. Network models is probably the most obvious example, although other system analysis tools may be accepted as the editors see fit; and
Considering policy-behavior interactions in the tool and/or exploring policy implications in the analysis.
Special issue article type becomes available in EES: October 1, 2017
Submission deadline – December 1st, 2017
Author notification of first round of reviews – March 1st, 2018
Author notification of second round of reviews (if needed) – September 1st, 2018
Candace Lightner, founder of Mothers Against Drunk Drivers recently published a counter-intuitive op-ed against lowering the blood alcohol content (BAC).
Hopefully everyone agrees that if there were fewer drunk drivers on the road, there would be fewer deaths from drunk driving. Hopefully everyone also agrees that BAC is correlated with impairment. The blood alcohol content limit, currently 0.08 in the US, is 0.05 in many other countries of the world. Should the US lower the BAC?
The argument against is that pulling over safe drivers (say in a police screenline, where all drivers on a road are pulled over and briefly tested) takes police resources that could be better spent pulling over observed dangerous drivers. Lightner writes: “Every dollar spent enforcing DUI laws against sober drivers is one not spent on getting the worst offenders off our roads.” Perhaps 2 drivers at 0.05 BAC are less dangerous than 1 driver at 0.10, so spend the time finding that driver.
But such police screenlines have the effect not just immediately about arresting people in violation of the law, and also as warning, reminder, and deterrent against future alcohol (and drug) impaired driving. To say the resources are a waste misses a major point.
International experience shows most other developed countries have significantly lower crash and fatality rates than the US, and they have 0.05 or lower BAC. Perhaps the US should just copy their traffic laws lock, stock, and barrel. Researchers have estimated ‘an additional 538 lives could be saved each year if the United States reduced the limit to 0.05,’ (Wagenaar et al. 2007)
Casual drinkers are a problem. Social drinking is a problem. I don’t care if you drink at home and don’t bother anyone (aside from the health insurance claims you impose on society from the damage you do to yourself), but when you drive a car, you endanger others. And because you are impaired, you don’t have the reasoning abilities to realise this.
The rules of the road should not only punish, but also provide a strong deterrent, which includes arrest and punishment even if you didn’t actually kill someone this time. Until robots fully rule the roads in 25 years, possibly another million Americans will be killed in car crashes. We can avoid tens of thousands of them with lower BAC limits.
This scientific review provides a summary of the evidence regarding the benefits of reducing the illegal blood alcohol concentration (BAC) limit for driving and providing a case for enacting a .05 BAC limit.
Fourteen independent studies in the United States indicate that lowering the illegal BAC limit from .10 to .08 has resulted in 5–16% reductions in alcohol-related crashes, fatalities, or injuries. However, the illegal limit is .05 BAC in numerous countries around the world. Several studies indicate that lowering the illegal per se limit from .08 to .05 BAC also reduces alcohol-related fatalities. Laboratory studies indicate that impairment in critical driving functions begins at low BACs and that most subjects are significantly impaired at .05 BAC. The relative risk of being involved in a fatal crash as a driver is 4 to 10 times greater for drivers with BACs between .05 and .07 compared to drivers with .00 BACs.
There is strong evidence in the literature that lowering the BAC limit from .10 to .08 is effective, that lowering the BAC limit from .08 to .05 is effective, and that lowering the BAC limit for youth to .02 or lower is effective. These law changes serve as a general deterrent to drinking and driving and ultimately save lives.
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