Google Maps to Direct Drivers Through ‘Eco-Friendly’ Routes to Fight Climate Change

Unless users opt out, the default route will be the one estimated to generate the lowest carbon emissions if comparable options take about the same time.

Google’s Maps app will start directing drivers along routes estimated to generate the lowest carbon emissions based on traffic, slopes and other factors, the company announced on Tuesday.

Google, an Alphabet Inc unit, said the feature would launch later this year in the United States and eventually reach other countries as part of its commitment to help combat climate change through its services.

Unless users opt out, the default route will be the “eco-friendly” one if comparable options take about the same time, Google said. When alternatives are significantly faster, Google will offer choices and let users compare estimated emissions.

“What we are seeing is for around half of routes, we are able to find an option more eco-friendly with minimal or no time-cost trade-off,” Russell Dicker, a director of product at Google, told reporters on Monday.

Google said it derives emissions relative estimates by testing across different types of vehicles and road types, drawing on insights from the US government’s National Renewable Energy Lab (NREL). Road grade data comes from its Street View cars as well as aerial and satellite imagery.

Also read: Bill Gates Proposes To Technofix Climate Change but Underplays the Role of Nature

NREL mobility group manager Jeff Gonder said the lab, which developed a tool known as FastE to estimate vehicles’ energy usage, reached a deal this month to get funding from Google and study the accuracy of its estimates.

The potential effect on emissions from the feature is unclear. A study of 20 people at California State University, Long Beach, last year found participants were more inclined to consider carbon emissions in route selection after testing an app that showed estimates.

Google’s announcement included additional climate-focused changes. From June, it will start warning drivers about to travel through low emissions zones where some vehicles are restricted in Germany, France, the Netherlands, Spain and the United Kingdom.

In the coming months, Maps app users will be able to compare car, biking, public transit and other travel options in one place instead of toggling between different sections.

(Reuters)

With Reports of Gloomy Sales Numbers, Auto Industry Woes Continue in July

Maruti Suzuki’s domestic sales drop in July was its largest in over a decade, while Bajaj Auto and M&M also reported poor numbers.

New Delhi: Most of India’s automobile and vehicle companies reported sharp drops in sales in July 2019, continuing a slump that has gone on for a large part of this year.  

Maruti Suzuki, India’s biggest car maker, registered its biggest sales drop yet in 2019, with the company’s domestic sales and exports dropping 33.5% to 1,09 lakh units in July 2019 compared with 1.06 units in the same month last year.

This is the sixth straight month of declining sales for the firm. The automaker also reported a 36.3% year-on-year drop in just domestic sales at 98,210 units in July 2019 compared to 1.54 lakh units in July 2018 – the sharpest decline in over a decade. 

Also read: Auto Slowdown: 286 Dealers Closed Down in 18 Months, 32,000 Jobs Impacted

According to a stock exchange notification put out by the company on Thursday afternoon, sales of mini cars comprising Alto and WagonR were at 11,577 units as compared to 37,710 units in July last year, down 69.3%.

Sales in the compact segment, including models such as Swift, Celerio, Ignis, Baleno and Dzire, were down 22.7% at 57,512 units as against 74,373 units in July last year.

Mid-sized sedan Ciaz sold 2,397 units as compared to 48 units in the same month a year ago.

Utility vehicles, including Vitara Brezza, S-Cross and Ertiga were down 38.1 per cent at 15,178 units as compared to 24,505 in the year-ago month, MSI said.

Exports in July were down by 9.4% at 9,258 units as against 10,219 units in the corresponding month last year, the company said.

M&M, Bajaj Auto too down

Mahindra & Mahindra Ltd.’s auto sales declined 15% to 40,142 units on a yearly basis last month, while its tractor sales fell 12% to 19,992 units, according to its stock exchange filing.

Bajaj Auto, on the other hand, reported its first fall in total sales in nearly two years. The company’s sales, which includes both two-wheelers and three-wheelers, fell 5% to 3.81 lakh units in July 2017, from 4 lakh units in July 2018.

Domestic sales stood at 2,05,470 units as against 2,37,511 units a year ago, down 13 percent, the Pune-based firm said in a statement.

Commercial vehicle sales any better?

The slowdown, which has affected passenger vehicle sales, also appears to have extended to commercial vehicle sales which includes trucks.

For instance, Ashok Leyland’s sales fell 28% on a yearly basis to 10,927 units in July 2018. Sales of domestic medium and heavy commercial trucks fell 47% to 4,668 units.

Also read: Passenger Vehicle Sales Down by 18% in June, Car Sales Decline by 25%

Eicher’s commercial vehicle arm also reported poor numbers, with total sales declining 32.1% on a year-on-year basis to 4,048 units.

According to data collated by Bloomberg, vehicle registrations, a key metric of sales at the dealership level, fell by 1.8% in July 2019 on a month-on-month basis and 8.2% on a yearly basis.

(With inputs from agencies)

Passenger Vehicle Sales Down by 18% in June, Car Sales Decline by 25%

Vehicle sales across categories registered a decline of 12.34% to 19,97,952 units from 22,79,186 units in June 2018.

New Delhi: Domestic passenger vehicle (PV) sales declined by 17.54% to 2,25,732 units in June from 2,73,748 units in the year-ago period.

According to data released by the Society of Indian Automobile Manufacturers (SIAM) on Wednesday, domestic car sales were down 24.97 % to 1,39,628 units as against 1,83,885 units in June 2018.

Motorcycle sales last month took the biggest hit as sale units declined from 9.57 % to 10,84,598 units as against 11,99,332 units a year earlier. In June, specifically, the total two-wheeler sales declined 11.69% to 16,49,477 units compared to 18,67,884 units in the year-ago month.

The downturn in motorcycle sales was followed by the decline in sales of commercial vehicles which were down 12.27% to 70,771 units in June against 80,670 units in the same period a year ago, SIAM said.

Also read: Can India Become the Next China for Carmakers?

In fact, all vehicle categories witnessed a decline in sales during the month.

The overall vehicle sales registered a decline of 12.34% to 19,97,952 units from 22,79,186 units in June 2018.

In the April-June period, PV sales declined 18.42% to 7,12,620 units compared with 8,73,490 units in the year-ago period while vehicles sales across all categories declined by 12.35% to 60,85,406 units against 69,42,742 units sold in the year-ago period.

(PTI)

How Urban Design Can Help Avoid Vehicle Attacks and Protect Pedestrians

Chicanes, steep verges, bollards, decorative planters, bus shelters, signs, statues, water features and high kerbs are all examples of design features that can be used to slow down an oncoming vehicle.

Chicanes, steep verges, bollards, decorative planters, bus shelters, signs, statues, water features and high kerbs are all examples of design features that can be used to slow down an oncoming vehicle.

Australian police stand near a crashed vehicle after they arrested the driver of a vehicle that had ploughed into pedestrians at a crowded intersection near the Flinders Street train station in central Melbourne, Australia December 21, 2017. Credit: Reuters/Luis Ascui

As emergency services rushed to help after a vehicle was driven into pedestrians on Flinders Street in Melbourne, Associate Professor Douglas Tomkin – an expert on how to make pedestrians safer in exactly these situations – passed by in a bus.

His first thought was, “Oh no. Not again.”

The latest attack, which Victorian police say was “not terror-related,” underscores the need for new ways to design city features to reduce risk when these incidents occur, he said.

Tomkin and his team at the Designing Out Crime Research Centre at UTS have been working with NSW Police on finding ways to improve city design to make people safer in a world where any vehicle could be used in a deliberate attack on pedestrians.

“NSW Police have just been conducting some experiments in very similar circumstances, driving an SUV travelling at 80 kilometres an hour into bollards,” he said. Other tests will follow.

“There are lots of different ways to make cities safer in these situations. It’s dependent on the context, these lot of things you can do at some places that you can’t at other places,” he said.

“If you were planning this at the street level, you might have chicanes, which require vehicles to turn corners and deliberately slows them down. There are ways in which you can take pedestrians off dangerous corners but still make it convenient for them.”

Some of these design features are detailed in the Safe Places – Vehicle Management report Tomkin and the team at Designing Out Crime Research Centre helped develop in partnership with the NSW police.

The Flinders Street incident is unlikely to be the last, he said.

“Bizarrely, I was close by when it happened. I was catching the bus back to the airport and I could see all the vehicles. I thought ‘Oh no, not again.’ It’s just dreadful that these sorts of things end up prompting other people to think ‘I can do the same’,” Tomkin said.

“To be honest, the thing concerning a lot of us at the moment is New Year’s Eve and times when you get people massing in certain areas. If you have any incident which even can cause panic and get people running all over the place, it gets more difficult to control in those circumstances.”

We need to change the way we design cities

Dr Pernille Christensen, a senior lecturer at UTS, is conducting research into the role that built environment plays in protecting crowded places.

Chicanes, steep verges, bollards, decorative planters, bus shelters, signs, statues, water features, and high kerbs are all examples of design features that can be used to slow down an oncoming vehicle or absorb impact so a human is not the first thing it hits.

“We’re talking to everybody from architects, urban designers and landscape architects on one end of the spectrum to property management, developers, investors and construction professionals at the other end,” Christensen said.

“We want to achieve an integrated design where security features are considered in the design, planning and pre-construction development stages, rather than being considered as an afterthought. This way, people don’t necessarily say, ‘Oh that’s here to protect me’ but see the solution as just a nice feature of the space. So people feel safe, without feeling afraid,” she said.

“The trend is toward low sophistication attacks with vehicles and easily accessible weapons. As long as this continues to be the case, we need to think about how to protect our crowded places against this strategy. At the same time, we need to make sure our spaces are adaptable, because the mode of attack is always changing and we need to be one step ahead.”

Jordan Fermanis is an editorial intern and Sunanda Creagh is the head digital storytelling at The Conversation

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

Moo Outta the Way: Gujarat Researchers Build ‘Cow Avoidance’ System for Cars

The researchers say their method to detect the presence of cows specifically and other animals generally on or adjacent to Indian roads is something that hasn’t been done before.

The researchers say their method to detect the presence of cows specifically and other animals generally on or adjacent to Indian roads is something that hasn’t been done before.

Moo outta the way. Credit: BANITAtour/pixabay

Credit: BANITAtour/pixabay

In 2015, over 146,000 people were killed in 501,423 road accidents in India, with another 500,279 people injured. Overall, 29.1 people were killed in the country for every 100 road accidents. A number of factors are responsible for these ghastly numbers, including bad roads, rapid urban motorisation as well as a prevalent reluctance to follow traffic rules. However, it isn’t known how often cows are involved in any of these accidents. None of the National Crime Records Bureau, the Ministry of Road Transport and Highways and the World Health Organisation have data on this.

Why would they? The cow isn’t wildlife nor a particularly interesting subject of conservation. At the same time, there have been news reports (here, here and here, for example) documenting a rising incidence of road accidents involving stray animals in the country.

In light of this, a pair of researchers – Sachin Sharma and Dharmesh Shah – have devised an obstacle detection system for vehicle drivers on Indian roads that will “determine whether an object near the vehicle is an on-road cow and whether or not its movements represent a risk to the vehicle”, to quote from a press release. The researchers, from the Gujarat Technological University (GTU), Ahmedabad, add that “a timely audio or visual indicator can then be triggered to nudge the driver to apply the brakes whether or not they have seen the animal”. Finally, the system still needs to be optimised – being currently 80% accurate – and can’t yet work at night. But in the absence of credible numbers on accidents involving cows, it’s unclear how useful this bit of engineering will be.

Then again, this is what the press release – distributed on April 7 by EurekAlert* – says, and it’s a bit of an injustice because it gives the impression that the paper is about a novel configuration of a pre-existing “collision alert system”. The real feat appears to be a novel method with which to detect the presence of cows specifically and other animals generally on or adjacent to Indian roads – something the researchers say hasn’t been done. The method uses “HOG descriptors”, which are “feature descriptors … used in computer vision and image processing” for detecting the presence of cows and “boosted cascade classifiers” for classifying the cows as… well, cows.

But before we proceed: some issues with the paper itself, as well as its publisher, prompt concerns over the legitimacy of its findings. For example, Inderscience, the publisher of the International Journal of Vehicle Autonomous Systems (in which the study was published), claims all its products are peer-reviewed. Its website also states that it doesn’t levy a processing fee unless a paper has to be open-access upon publication, but this fee is suspiciously large: GBP 2,000 (Rs 1.59 lakh). An email to the Inderscience press office about this hasn’t yet elicited a reply.

The paper also contains at least 11 instances of plagiarism. Even if they don’t interfere with the major conclusions, this isn’t to suggest the paper itself be exonerated. Moreover, the authors appear to have published a more detailed version of their thesis in the better-known journal IEEE Access in December 2016. And in this version, their system has an accuracy of 82.5%. According to Sharma, “Calculation of distance of the detected animal from the vehicle as well as speed of the vehicle is also added in the extended version.”

Back to the study: HOG descriptors are used to process images such that the information used to identify them becomes independent of brightness and shadows, apart from acquiring other advantages. The acronym stands for ‘histogram of oriented gradients’. Next, a classifier algorithm is used to ‘identify’ what is there in the image based on what it has been ‘taught’ earlier. But instead of sticking to the judgment of one, a series of classifiers are used in a cascade to ascertain what’s being identified in the image. The ‘boost’ stands for a technique used to improve the learning capabilities of the classifiers. All together, a cow-finder based on this architecture is called the HOG-cascade.

There are some constraints on the conditions in which this system will work optimally. For example, the duo report in their Access paper that the camera can’t pick up on a cow more than 20 metres away. For another, the warning system won’t be able to warn the driver and and allow them sufficient time to act usefully if the vehicle’s moving faster than 35 km/hr. The accuracy of 82.5% isn’t very helpful either: it means that in almost one in five instances, a signal will be sounded too late or not at all. This is particularly problematic for the case of autonomous vehicles as well as drivers who are almost entirely reliant on the system to alert them. Sharma said they’re now trying to ramp the accuracy up to 90% by training the classifiers with more animal images: “it is a very challenging task”.

But overall, notwithstanding the lack of data on the involvement of cows in road accidents: a detection-and-warning system that has to work in India can’t account only for humans, even if in urban settings. Our roads are populated by all kinds of obstacles that can make commuting stressful, ranging from stray animals to uncouth motorcyclists to overloaded trucks. So being able to detect humans alone and then triggering a warning won’t be able to prevent all accidents caused by driver inattention. This in turn can help reduce the number of road accidents that have been blamed on the driver: fully 78% in 2013.

Sharma said that GTU is seeking government support at the moment to have their device (a laptop-camera combo) integrated with vehicles. The current cost of each unit is Rs 45,000, but Sharma says this can be brought down with further optimisation such that an Android smartphone will suffice.

At the same time, let’s not kid ourselves that this will solve much if other solutions don’t fall in place. In the policy sphere, for example, why is road safety not included under public health when it should be?

*EurekAlert has been known to distribute questionable press releases in the past.