Free public transport won’t work – unless we get rid of the drivers

Gissa lift mate. Image: Fraser Elliott/creative commons.

The idea of free public transport has clear appeal. Cities in France; and Germany; are already considering such proposals, to reduce traffic and air pollution. And in the UK, Labour party leader Jeremy Corbyn declared that he would introduce free bus travel for under-25s, to complement the passes already available to senior citizens.

But the evidence suggests that offering free public transport causes headaches for local authorities – and may not be an effective way of getting commuters to stop driving cars. Tallinn, capital of Estonia, introduced free public transport for residents in 2013. But a 2014 survey showed that most of the people who switched to public transport had previously walked or cycled, rather than driven. A further survey in 2017 showed that patronage had increased by only 20 per cent over four years.

The April 2018 edition of German trade publication Stadtverkehr claims that the only cost effective way to get car drivers to switch to public transport is to couple reasonably priced transit with severe traffic restraints. For example, in the English city of Sheffield, attractive bus fares and timetables used to keep cars out of the city centre. From the 1970s, until the service was deregulated in 1986, there was simply no need for residents to drive into Sheffield.

Finding the funds

The biggest drawback to free public transport schemes is the lack of funds from fares to cover maintenance and upgrades. In Tallinn, for example, the city’s inadequate tram system will eventually require capital for a complete renewal – or face closure. Hasselt, a Belgian town with a population of 70,000, offered free bus travel for 16 years until 2013, but eventually scrapped it when costs became unsustainable.

Paris, meanwhile, has already banned the most polluting vehicles and offered free public transport for a few days each year when pollution has reached dangerous levels due to atmospheric conditions. But according to an article in the June 2018 edition of Today’s Railways EU, traffic is rarely reduced more than 10 per cent on these days, and the long term shift to other forms of transport is minimal.

In the UK, free bus travel for senior citizens has hastened the demise of many rural and intercity services. Many local authorities have diverted support away from rural, evening and weekend services, to the concessionary fares budget. During interviews with BBC Radio 4, younger people – who rely on buses to get to work or go out on the evenings and weekends – complained that services had been axed to offer senior citizens free travel during daytime on weekdays.

But irrespective of your age, health or prosperity, there is no point in having a free bus pass if there are no buses to use it on. As bus services are further deregulated in the UK, there will continue to be pointless oversupply on some corridors, while other areas struggle to see more than a few buses per week – if any at all.


Driverless minibuses

The development of autonomous electric minibuses could be a game changer, especially if a manufacturer is prepared to lease them on favourable terms. Local authorities could pilot a scheme whereby the bus is “hailed” by smart phone 15 to 30 minutes before departure. Indeed, tests for autonomous on-demand services are already underway in cities across the US, UK; and Europe;.

Once the expensive and restrictive labour element is removed from the operating costs, there is no reason why such services could not be offered free of charge to all users. In the urban core – within a 10km radius of a city centre – these services could run 24/7. Further afield, in the suburbs, a daily service from 6am until midnight would probably be sufficient to compete with the private car.

Autonomous minibuses could automatically connect with city buses and trains, which would continue to be staffed and paid for by fares. The minibuses would provide a “last mile” service, taking people within easy walking distance of their destination. In urban areas, all residential and business premises would be within 200m of a minibus stop, extending to 500m in suburban areas and 1km in rural areas.

At off peak times, the minibuses could replace some conventional bus services to avoid the inefficiencies created when a 70 passenger bus is used to transport only ten people on an evening or Sunday service.

To prevent abuse of the minibuses, passengers would scan their phones on boarding to confirm the booking. If they didn’t, a penalty could be collected automatically from their phone. CCTV could identify any disruptive passengers and refuse further bookings. Meanwhile, taxis would continue to prosper from those people willing to pay for a personal door-to-door service.

Public transit systems, as we know them today, would struggle to deliver a sustainable free service. But there’s a real possibility that the autonomous vehicles of tomorrow could do just that.

John Disney, Senior Lecturer, Nottingham Business School, Nottingham Trent University.

This article was originally published on The Conversation. Read the original article.

 
 
 
 

Just like teenagers, self-driving cars need practice to really learn to drive

A self-driving car, of unknown level of education. Image: Grendelkhan/Flickr/creative commons.

What do self-driving cars and teenage drivers have in common?

Experience. Or, more accurately, a lack of experience.

Teenage drivers – novice drivers of any age, actually – begin with little knowledge of how to actually operate a car’s controls, and how to handle various quirks of the rules of the road. In North America, their first step in learning typically consists of fundamental instruction conveyed by a teacher. With classroom education, novice drivers are, in effect, programmed with knowledge of traffic laws and other basics. They then learn to operate a motor vehicle by applying that programming and progressively encountering a vast range of possibilities on actual roadways. Along the way, feedback they receive – from others in the vehicle as well as the actual experience of driving – helps them determine how best to react and function safely.

The same is true for autonomous vehicles. They are first programmed with basic knowledge. Red means stop; green means go, and so on. Then, through a form of artificial intelligence known as machine learning, self-driving autos draw from both accumulated experiences and continual feedback to detect patterns, adapt to circumstances, make decisions and improve performance.

For both humans and machines, more driving will ideally lead to better driving. And in each case, establishing mastery takes a long time. Especially as each learns to address the unique situations that are hard to anticipate without experience – a falling tree, a flash flood, a ball bouncing into the street, or some other sudden event. Testing, in both controlled and actual environments, is critical to building know-how. The more miles that driverless cars travel, the more quickly their safety improves. And improved safety performance will influence public acceptance of self-driving car deployment – an area in which I specialise.

Starting with basic skills

Experience, of course, must be built upon a foundation of rudimentary abilities – starting with vision. Meeting that essential requirement is straightforward for most humans, even those who may require the aid of glasses or contact lenses. For driverless cars, however, the ability to see is an immensely complex process involving multiple sensors and other technological elements:

  • radar, which uses radio waves to measure distances between the car and obstacles around it;
  • LIDAR, which uses laser sensors to build a 360-degree image of the car’s surroundings;
  • cameras, to detect people, lights, signs and other objects;
  • satellites, to enable GPS, global positioning systems that can pinpoint locations;
  • digital maps, which help to determine and modify routes the car will take;
  • a computer, which processes all the information, recognising objects, analysing the driving situation and determining actions based on what the car sees.

How a driverless car ‘sees’ the road.

All of these elements work together to help the car know where it is at all times, and where everything else is in relation to it. Despite the precision of these systems, however, they’re not perfect. The computer can know which pictures and sensory inputs deserve its attention, and how to correctly respond, but experience only comes from traveling a lot of miles.

The learning that is occurring by autonomous cars currently being tested on public roads feeds back into central systems that make all of a company’s cars better drivers. But even adding up all the on-road miles currently being driven by all autonomous vehicles in the U.S. doesn’t get close to the number of miles driven by humans every single day.

Dangerous after dark

Seeing at night is more challenging than during the daytime – for self-driving cars as well as for human drivers. Contrast is reduced in dark conditions, and objects – whether animate or inanimate – are more difficult to distinguish from their surroundings. In that regard, a human’s eyes and a driverless car’s cameras suffer the same impairment – unlike radar and LIDAR, which don’t need sunlight, streetlights or other lighting.

This was a factor in March in Arizona, when a pedestrian pushing her bicycle across the street at night was struck and killed by a self-driving Uber vehicle. Emergency braking, disabled at the time of the crash, was one issue. The car’s sensors were another issue, having identified the pedestrian as a vehicle first, and then as a bicycle. That’s an important distinction, because a self-driving car’s judgments and actions rely upon accurate identifications. For instance, it would expect another vehicle to move more quickly out of its path than a person walking.


Try and try again

To become better drivers, self-driving cars need not only more and better technological tools, but also something far more fundamental: practice. Just like human drivers, robot drivers won’t get better at dealing with darkness, fog and slippery road conditions without experience.

Testing on controlled roads is a first step to broad deployment of driverless vehicles on public streets. The Texas Automated Vehicle Proving Grounds Partnership, involving the Texas A&M Transportation Institute, University of Texas at Austin, and Southwest Research Institute in San Antonio, Texas, operates a group of closed-course test sites.

Self-driving cars also need to experience real-world conditions, so the Partnership includes seven urban regions in Texas where equipment can be tested on public roads. And, in a separate venture in July, self-driving startup Drive.ai began testing its own vehicles on limited routes in Frisco, north of Dallas.

These testing efforts are essential to ensuring that self-driving technologies are as foolproof as possible before their widespread introduction on public roadways. In other words, the technology needs time to learn. Think of it as driver education for driverless cars.

People learn by doing, and they learn best by doing repeatedly. Whether the pursuit involves a musical instrument, an athletic activity or operating a motor vehicle, individuals build proficiency through practice.

The ConversationSelf-driving cars, as researchers are finding, are no different from teens who need to build up experience before becoming reliably safe drivers. But at least the cars won’t have to learn every single thing for themselves – instead, they’ll talk to each other and share a pool of experience.

Johanna Zmud, Senior Research Scientist, Texas A&M Transportation Institute, Texas A&M University .

This article was originally published on The Conversation. Read the original article.