Abstract : We worked on a QR scanner based vehicle-sharing system which allows riders to post real time ride requests from smart phones and drivers to accept those ride requests sent from smart phones. When another rider on the same route, sees the ride request, he/she can join the ride according to the rides available on the route via ridesharing. Carpooling is an activity in which riders, instead of their individual means of transport, opt to share a single vehicle for traveling. This contributes in sustainable development by reducing the pollution and fuel consumption levels and also, in reducing vehicular congestion on roads. To this end, we devise a QR based vehicle-sharing system. Taxi riders and taxi drivers use the taxi-sharing service provided by the system via a Mobile Application. The system first lets users post ride requests along with their pickup and drop location. The interested ride sharing users nearby can see the details and join. details. The driver has the ability to accept/deny the requests as per availability in the vehicle. Each user, passenger as well as driver has a unique QR Code generated at the time of registration. Driver\'s QR has the details of the driver, vehicle details and its geographical location at the moment. User\'s QR has the user details. The given QR Codes can be used to fetch the details of the ride given/taken by the users of the app and the travel details with itinerary is credited/debited to the user account after every ride. We built mobile application using GPS Services and QR Code scanner in order to provide this service. This system is also extended to share autos which follow a fixed path with n number of stops on the most common routes.
Keywords: Vehicle-sharing, GPS Trajectory, ridesharing, urban computing, intelligent transport systems, sustainable transportation, QR codes, Cost sharing
Taxi has been a popular means of public transport ever since a long time. There has been a significant change in the taxi service mechanisms over the last decade. Today modern taxi are equipped with GPS services, automatic booking apps and what not. This mode of transport was popular in the urban areas since a long time, however in the recent years, it has gradually gained popularity in the suburban as well as rural areas. However, the number of taxi is much less than its demand in peak hours, due to this, waiting time is needed. The Service Providers use this fact to their advantage and impose a surge pricing technique, according to which, you need to pay more fare in hours of peak demand. To overcome the problem one optimal solution is to increase the number of taxis. But it gives rise to a number of problems, which include causing additional traffic on the road surface, more energy consumption, and decreasing taxi driver’s income. To address this issue, we introduce a carpooling system that accepts passengers’ real-time ride requests sent from smart phones and schedules proper taxis to pick up them via taxi sharing with time, capacity, and monetary constraints. Alternative means of transportation like share autos can also be implemented using this system.
Ridesharing is a mode of transportation in which individual travelers share a vehicle for a trip and split travel costs incurred during the travel. Carpooling is nothing, but recurrent ridesharing practiced by people who follow similar routes regularly, for example, home to work carpooling is very common in colleagues in urban cities. By effectively using new communication capabilities, including mobile technology and global positioning system, i.e., GPS, there are several attempts to enable dynamic or real-time ridesharing systems. This is particularly important in the times we live in, to promote sustainable development. Measures like ridesharing control the pollution and fuel consumption levels by ensuring a reduction in them and also relieves the road of heavy vehicular congestion. This concept has been popular since a long time in countries like U.S.A and Canada. However, with the advent of cab service aggregators like OLA, UBER, MERU etc in our country, the concept of cab sharing and car pooling has slowly entered into our socio-economic scenarios. There have been some moderately successful examples of the same which include OLA SHARE, UBERPOOL, BLA-BLA CARS, TRIPDA, etc.
The contributions made by this paper are:
• A QR Code Scanner based vehicle sharing system which allows ride posting/joining using QR scanning and ride sharing mechanisms. The system works for drivers as well as riders using the service.
• The system overcomes monetary constraints in using taxi services by splitting the fare, and hence provides incentive for more users to practice ridesharing.
• Ridesharing is effective and scalable, and it provides a number of benefits. Riders have to pay lesser fare and a huge amount of fuel can be conserved which facilitates sustainable development.
2. LITERATURE REVIEW:
2.1 EXISTING SYSTEMS:
• OLA SHARE
Ola Share is a Ride Sharing option by the widely popular cab service provider in India, Ola. There is an option in the app by which a driver can offer their ride for pooling and the riders can join in. Ola Share uses advanced algorithms to match users who plan to travel on the same route in real-time.
Uber, an International Cab Aggregator also provides the option of pooling. “Share your car” is uberPOOL where according to your pickup and drop locations, the split fare is calculated and you have to pay on joining. The fare for Uber pool will always be less than uberGO, which is the normal cab fare. Uber pool also uses algorithms similar to those used in Ola share.
• BLA-BLA CARS
It is a French company which provides the platform for Ride Sharing and Car Pooling. People who have offered rides post ride details along which includes start and end points, destination, price to be paid by each rider. We can view the Ride details posted, request for information about the car owner, their reasons for travelling and other journey details. You can also sign up to offer a ride. For every ride that you offer, there is a suggested price based on the distance travelled and the estimated fuel consumption.
• DIDI CHUXING
Didi Chuxing is an application where taxis, private cars and designated drivers can be hired via smart phone.. It uses highly advanced algorithms and offers a wide range of services apart from the cab-sharing services.
2.1.1 DISADVANTAGES OF EXISTING SYSTEMS:
• Determination of fare is non-uniform and is not divided according to the distance travelled by each passenger in the vehicle. Existing systems offer a fare waiver up to 35% only irrespective of the number of passengers in the car.
• The existing systems often cause a delay in pickup due to detour from the current path.
• The existing systems have not been extended to any other mode of transport other than cabs.
2.2 RELATED WORKS:
• Real-time Taxi Ridesharing:
Several previous works have studied the topic of real-time taxi sharing , , , , et al. However, the assumptions and constraints mentioned in these works is obsolete and not up to date. We live in a world that is constantly changing and hence, these attributes tend to change very quickly.
We introduce the concept of QR Codes which provides a quick, hassle free and secure way of storing a retrieving dynamic data of ridesharing.
2.3 PROPOSED SYSTEM:
We propose a QR scanner based vehicle-sharing system that posts passengers’ real-time ride requests sent from smart phones and the interested ride sharing candidates can join in. We devise a vehicle-sharing system on android and web platforms.
Each user, passenger as well as driver has a unique QR Code generated at the time of registration. Driver’s QR has the details of the driver, vehicle details and its geographical location at the moment. User’s QR has the user details. The given QR Codes can be used to fetch the details of the ride given/taken by the users of the app and the travel details with itinerary is credited/debited to the user account after every ride.
2.3.1 ADVANTAGES OF PROPOSED SYSTEM:
• We propose a system where all data is stored and retrieved in the form of QR Codes, which can be scanned directly on the phone.
• We extend this system for use by the share taxis as well, which form an integral part of our transportation system.
• Allotment of vehicle will be done using an algorithm such that minimum or no detour is required and the fare distribution is uniform according to the distance travelled and number of passengers.
2.4 SCOPE OF QR BASED SYSTEMS:
• QR Code stands for Quick Response Code.
• It is a two-dimensional barcode which was first designed for the automotive industry in Japan.
• A QR Code is a machine-readable optical label which uses four standardized encoding modes to efficiently store data.
• The QR code is very popular due to its fast readability and greater storage capacity.
• Product tracking, item identification, time tracking, document management, and general marketing are some of the applications of QR Codes.
• A QR code consists of white background on top of which black squares arranged in a square, which can be read by an imaging device such as a camera, and processed.
Figure 1: Sample QR Code
• QR based systems are slowly gaining popularity in many information systems as well as payments portals due to safe and hassle-free quick access.
3. MATERIALS AND METHODS:
The real-time vehicle sharing problem consists of a data model, constraints and an objective function:
3.1 Data Model:
• User Database:
Each user is given a unique QR Code which stores the personal information about the user as well as the details of his/her rides.
• Ride Request:
Each ride request R has the following attributes, R.t indicating when R was posted, an origin point, R.o, a destination R.d, a time window R.pw and R.dw which defines the time interval of pickup and drop respectively. The nearby drivers are sent a request for a new rider to join, and whichever driver accepts it first, gets the rider.
• Taxi Status:
A taxi status T represents the instantaneous state of taxi and has the following attributes:
T.id which identifies the taxi, T.t which is the timestamp associated with the status, T.l which is the geographical location as per the GPS, T.s which is the current schedule of pickups and drops. It is a dynamic variable and changes with every booking.
• An Android and Web application system based on scanning QR Codes and retrieving dynamic data, which enables real-time taxi-sharing in a practical setting.
• Each user of the application, driver as well as rider has a unique QR Code which is used to fetch the real time data.
• Passengers submit real-time ride requests using the same App. Each ride request is scanned as a QR Code which consists of the user/driver details, origin and destination of the trip, time windows constraining when the passengers want to be picked up and dropped off.
• On receiving a new request, the system will search for the taxi which minimizes the travel distance increased for the ride request and satisfies both the new request and the trips of existing passengers who are already assigned to the taxi, subject to time, capacity, and monetary constraints.
The System Architecture is as shown in fig. 2
• Registration Module is used to signup new users and generates their QR codes for identification. Once the registration is completed, the user can sign in to his/her account and proceed with the App.
• The User location and time stamp will be automatically updated in the database once the user scans his/her QR in the driver’s App.
• The selection and scheduling of journey is done while minimizing detour and delays.
An example of Ride Sharing:
• The Ride can be commenced by scanning the QR Code of the rider on the App of the driver of the vehicle.
• The System calculates the trip fare according to the distance travelled and the number of passengers in the vehicle. The amount is automatically debited from riders’ account and when he/she ends the trip by scanning the QR Code once again.
We can say that a Taxi Status T satisfies a ride request R if the given constraints are met:
• Vehicle capacity:
Depending on the size and type of the vehicle, the vehicle capacity is determined. It should be one lesser than the total number of seats to accommodate the driver.
• Time Window:
The riders should be informed beforehand about the time window of pickup and it should be feasible for the driver as well as the other riders.
• Monetary Constraints:
The ridesharing allows riders to pay lesser than ordinary cab ride by splitting the fare between the co-riders. However, the driver should not incur any loss in this process.
3.3 RIDE SHARING PATTERNS:
A driver’s original route is the route he or she would have taken if driving alone; when participating in a ride sharing, it can be called as a ridesharing route. A passenger’s origin can differ from their pick-up location; the same is true for the destination and drop-off location.
We can classify ridesharing patterns into four as illustrated in Figure 2.
• Pattern 1 (identical ridesharing): Both the origin and destination of driver and passenger are same.
• Pattern 2 (inclusive ridesharing): Both the origin and destination of passenger is on the way of original route of the driver. All the trips are carried out by a single driver, but a passenger does not have an identical trip with the driver.
• Pattern 3 (partial ridesharing): Both the pick-up location and drop-off location of passenger are on the way of an original route of driver, but either the origin or the destination of the passenger is not on the way. Ridesharing is only a part of passenger’s trip and he has completed the remaining part of his journey on his own.
• Pattern 4 (detour ridesharing): Either the pick-up location or drop-off location or both of passenger b are not on the way of an original route of driver a. Thus, taking a detour, ridesharing route covers both the pick-up and drop-off locations.
3.4 RIDE SHARING:
The process of ride sharing can be in two possible scenarios:
Scenario 1, Cab Sharing:
Suppose there is a route from P to S, and the ride is posted by a user A. On boarding the cab, user A scans his unique QR Code, which validates and starts the trip. Later another user B, who has to go along the route (from Q to R) views the ride details and decides to join in at point Q. He / She joins in by scanning his/her QR the details of the journey are noted in the database and the split fare is calculated.
(Let the rate of cab fare be r per km).
At Pick up Location P and Drop Location Q:
Generate Time stamp and store the location.
Fare Calculation Algorithm:
(P to S )*r : Single customer (without cab sharing)
Cab Sharing fare for Customer 1:
(P to Q) *r +((Q to S)*r)/2
Cab Sharing fare for Customer 2:
((Q to S)*r)/2
Flow of events:
1. If ride is started, an event is triggered.
2. This event will stay on till another event, i.e stop occurs.
3. With every new passenger boarding, the count increases by 1. Depending of the type of vehicle, the number of maximum passengers is determined.
4. Amount for each passenger is calculated as:
P1,P2,P3 and D1,D2,D3 are the pickup and drop points of customer 1,2 and 3 respectively, and r be the rate per km.
Amount.P1= ((Distance between P1&P2)*r)+((Distance between P2 and D2)*r)/2+(Distance between D2 & D1) *r)
Amount.P2=((Distance between P2 & D2)*r)/2
And so on. This can be extended to n users where n is the maximum seating capacity of the vehicle.
Scenario 2- Sharing Autos/Cabs along common routes (for example: from a station to marketplace, where a lot of people go frequently):
On-boarding: (Start Point)
• Customer scans his/her QR Code on driver’s phone which triggers event on.
• This event sends the current location, customer id, date and timestamp to the database server.
Disembarking: (Stop Point)
• Customer scans QR again which triggers event off.
• This event sends the location, customer id date and time and calculates the fare for the customer.
Fare = (Stop point - Start point)*basic fare.
Working of QR Codes:
QR Code Generation:
The process of QR Code generation can be carried out using ZXing library. ZXing (\"zebra crossing\") is an open-source, multi-format 1D/2D barcode image processing library implemented in Java, with ports to other languages.
We can use the module zxing.appspot.com which is the source behind web-based barcode generator for the process.
The symbol versions of QR Code range from Version 1 to Version 40. Each version has a different module configuration or number of modules. The module refers to the black and white dots that make up QR Code.
\"Module configuration\" refers to the number of modules contained in a symbol, commencing with Version 1 (21 × 21 modules) up to Version 40 (177 × 177 modules). Each higher version number comprises 4 additional modules per side.
Each QR Code symbol version has the maximum data capacity according to the amount of data, character type and error correction level. In other words, as the amount of data increases, more modules are required to comprise QR Code, resulting in larger QR Code symbols.
QR Code Scanning:
A QR Code scanner is composed of three parts: the illuminator, the decoder, and the sensor/convertor. The scanner widget provided by ZXing library provided by Android provides the complete scanning module. The process of scanning involves the following steps: It first illuminates the barcode with red light using the illuminator system. The sensor/convertor part of the scanner then detects the reflected light. Once the light is detected, an analog signal is generated. This signal contains varying voltage based on the intensities of the light reflection. The analog signal is converted by the sensor into a digital signal. The digital signal is then interpreted by the decoder. The decoder then sends the information to the mobile/computer attached to the scanner.
4. RESULTS AND DISCUSSIONS:
The services sector of Indian economy is one of the most dominant sectors in India’s GDP. The advent of taxi aggregator services such as Ola, Uber et.al. In the past five years has contributed significantly in the economy which can be seen by their growth in the Cost factor in the GDP over four quarters of a financial year.
India’s current vehicle population can be expressed by the following pie-chart
According to the report by Planning Commission of India on Transport in India, for passenger traffic, rail and roadways are the dominant modes in India, and this continues to increase rapidly. The share of roads in passenger traffic (in billion passenger kilometers bpkm) in the total passenger traffic altogether has increased from 32% in 1951 to 90% in 2012. The total passenger traffic is expected to grow by a factor of almost 16 over the next 20 years. Overall these projections provide an idea of the challenge facing overall transport investment in our country in order to achieve a sustainable and continuous development. Carpooling is a small step towards the cause, as it saves fuel and vehicular congestion.
4.2 EFFECTIVENESS OF RIDESHARING:
As is common in less-wealthy countries, many Indian cities have poor transport infrastructure, and have significant room to improve public transport options. The addition of ridesharing as a transport alternative could lead to a revolution in the country’s transport industry.
Ridesharing can be more a convenient, fast, and cost-effective form of transport than its alternatives. For many, ridesharing may already be cheaper than owning a car. It can also be an important part of multi-modal journeys by addressing first-and-last mile connectivity to bus, train, or other public transit services, fueling the demand for these already established transport modes. Many cities in India still face heavy traffic congestion. Ridesharing may help connect users to these mass transport systems, making them more accessible. It may also shed light on the deficiencies of existing public transport systems in many lower-income cities in India and worldwide, prompting increased investment to improve these services.
Ridesharing has the potential to revolutionize transport in places like India and other lower- and middle-income countries that are in dire need of more organized and efficient transport systems. It can provide a cost-effective and more environmentally friendly alternative to car ownership, and an ideal extension to existing public transit systems.
We did a sample population survey on ridesharing and existing systems and concluded the following:
The above graphs illustrate the reach of cab services in India. About 92.3 % of metropolitan and suburban population are aware of cab services and have used it at least once.
The various cab service providers Ola, Uber, Meru, Fasttrack and others are popular in various areas. However, Ola and Uber dominate the cab service market.
Ridesharing Services however, are not as popular as the cab services. Only 36.6% of the total cab service users have ever used a ridesharing service.
The ride sharing services offered by the widely popular Ola and Uber are preferred by most of the users as compared to the exclusive ride sharing service providers such as Tripda and Bla bla cars.
There are various motivations for ridesharing, which include cost saving, fuel saving, eco-friendly, company or just for once. Most people prefer payment through prepaid wallets. The pie chart below shows the percentage of preference.
4.3 EFFECTIVENESS OF QR BASED SYSTEM:
QR code based systems leverage mobile usage on the consumer side as well. Being asset-light, they become easy to use. The aim of this QR (Quick Response) code based effective employee maintenance system is to automate the ridesharing process in cab services. The ease of usage of QR codes motivates more users
The process of booking, joining and bill calculation can be carried out by means of QR Code scanning. Today, QR codes are omnipresent in all industries. Hence it is sure to find its way into these services as well.
This research was partially supported by Department of Computer Science and Engineering, SRM University, Chennai, India. It would not have been possible to complete this paper without the infrastructure and facilities provided by the University. We would like to express heartfelt gratitude to Mr.M.Arulprakash, Assistant Professor, Department of Computer Science and Engineering, SRM University, Chennai for his consistent support and continuous improvisation on the paper. We would also like to thank Dr.M.Pushpalatha, Professor, Department of Computer Science and Engineering,SRM University, Chennai for the feedback and constructive criticisms
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