2015-04-01T22:18:59Z

Mgarrett:

==Introduction==

Americans have an expectation that their private information will not be subject to collection and disclosure by government entities, including public transportation providers. The Fourth Amendment to the US Constitution prohibits "unreasonable searches and seizures" and this includes not just evidence of criminal activity but any information for which there is a "reasonable expectation of privacy." Generally speaking, activities undertaken in public, in plain view of others, such as riding on public transit is not entitled to the expectation that one's conduct is private. However, the increasing development of Intelligent Transportation Systems (ITS) capable of collecting large amounts of data about individual passengers raises questions whether some degree of privacy protection may be not only warranted but expected by the public at large.<ref>TRCP Legal Research Digest 14, March 2000</ref>

==Use of Smart Cards==
A Smart Card is a credit card-sized piece of plastic that contains an automatic identification system such as a bar code, magnetic strip, optical character recognition system, or radio frequency identification (RFID) chip, that can be used as a fare payment media or to otherwise access transit services. It may need to be inserted into a reader, though newer versions are "contactless" and can be read as long as they are in proximity to the interface device. The card may contain only limited information, such as a monetary balance, or have saved information about the user including credit information used to purchase the card, or other personal, financial, and biometric data, or provide a link to other data sources containing such information. This could include a person's name, address, phone number, age, gender, social security number, or other identifying information. The more personally identifiable information (PII) that is either stored on the card or that can be accessed using it, the greater potential that privacy concerns may be raised.<ref> TCRP Legal Research Digest 25.</ref>

Information from Smart Cards can be used for fare collection, billing, marketing and planning, and security purposes. The most significant factor for privacy purposes is that Smart Cards can provide location data on where the card, and by implication the card's user, is located at any particular time. This data may be collected when the card it used to access transit services, or it may eventually be possible to link the card with Global Positioning System (GPS) technology to track its whereabouts at any time (like cellphone data) or at least within a transit venue or vehicle.<ref> TCRP Legal Research Digest 25, p. 5.</ref> If this location information can be linked to other personal information about the user privacy concerns may increase. Highly detailed information about individual travel patterns can be extremely useful for transit planning and programming purposes, but those needs should be balanced against individuals' right to privacy. The key issues will include what type of information is being collection, whether the individual has reasonable expectation of privacy in that information, the reasonableness of the government's purpose in collecting the information, who will have access to it, and how long it will be stored. Courts will give greater latitude where public safety and security are involved, but transit agencies should consider adopting policy guidelines governing the collection, use and storage of personal information. Some states have adopted statutes that may affect information gathering by transit agencies.<ref>TCRP Legal Research Digest 25, pp. 17-23.</ref> A 2006 survey conducted by the Transportation Research Board found few agencies that had adopted Smart Cards but many which were considering it, and of those which had most limited the type of personal information collected and whether it could be correlated with outside information.<ref>TCRP Legal Brief 15, pp. 20-21.</ref> Caltrans has privacy guidelines that may be useful to transit agencies in developing appropriate policies.<ref>http://www.dot.ca.gov/privacy.html</ref>

==Further Reading==

Transit Cooperative Research Program, Legal Research Digest 14, [http://onlinepubs.trb.org/onlinepubs/tcrp/tcrp_lrd_14.pdf "Treatment of Privacy Issues in the Transit Industry,"] March 2000.

: This report discusses various privacy issues that may arise within the public transportation industry both in the workplace and involving customers and their private information.

Transit Cooperative Research Program, Legal Research Digest 25, [http://onlinepubs.trb.org/onlinepubs/tcrp/tcrp_lrd_25.pdf "Privacy Issues with the Use of Smart Cards,"] April 2008.

: This report examines basic privacy issues associated with the collection, use, and storage of financial and trip data associated with the use of transit smart cards.

==References==
<references/>

[[Category:Managing transit]]

2015-03-28T00:09:50Z

Mgarrett:

==Introduction==
One strategy to reduce travel times and provide more reliable transit service is through bus prioritization strategies. These can take a number of forms including dedicated bus-only lanes, [[bus rapid transit]], [[Bus-on-shoulder|bus bypass shoulders]], [[transit signal priority (TSP)]] which shortens the traffic signal's red phase or extends the green phase for an approaching bus, or by queue jump treatments that permit buses and other vehicles in the far right turn or bus-only lane to proceed ahead of traffic in adjacent lanes.

==Transit Signal Priority==
TSP can either be pretimed, triggered by an approaching bus, or the signal can be adjusted based on real time monitoring of traffic patterns. This strategy is appropriate for intersections operating under LOS C or D and with a volume/capacity ratio less than 1.0, otherwise the longer queues can prevent buses from clearing the intersection. The additional time allotted for buses is achieved through slight reductions in green phases for other traffic movements so that overall signal coordination is not affected. Another option, known as a queue jump, is to give buses dropping off passengers at [[bus stop spacing and location|near-side stops]] a green light a few seconds before the adjacent lanes to allow it to merge into traffic at the far side of the intersection before the following traffic can cross.<ref name=rodriguezanddanaher>Adriana Rodriguez and Alan R. Danaher, [http://trb.metapress.com/content/v761533070312217/fulltext.pdf “Operational Comparison of Transit Signal Priority Strategies,”] Transportation Research Record No. 2418, 2014, pp. 84-91.</ref> One drawback of conventional TSP (CTSP) strategies is that they are typically based on sensors that may not provide accurate bus arrival time information to decide whether to shorten the red phase or extend the green. As a result, there could be a waste of extra green time and unnecessary delays affecting side streets.<ref name=huetal>Jai Hu, Byungkyu (Brian) Park, and A. Emily Parkany, [http://trb.metapress.com/content/t54ku7636511k6p8/fulltext.pdf “Transit Signal Priority with Connected Vehicle Technology,”] Transportation Research Record No. 2418, 2014, pp. 20-29.</ref>

===Measuring Benefits===
Travel time savings from TSP can be measured by the number of minutes of reduced delay per mile of operation or per person. Predicting bus arrival times can be done using a variety of techniques including linear models, neural networks, vector regression, and k nearest neighbors regression. A recent study using linear models to estimate interstop travel times combined with real-time GPS information on current vehicle location produced a flex schedule that performed better and faster than other machine learning models and made collecting additional GPS data unnecessary.<ref>Tony Hernandez, [http://trb.metapress.com/content/e0281525127w4087/fulltext.pdf “Flex Scheduling for Bus Arrival Time Prediction,”] Transportation Research Record No. 2418, 2014, pp. 110-115.</ref>Even if detailed simulation modeling is not practical, simple sketch planning tools can be used to evaluate the optimal strategy for specific corridors. Cost benefit analysis can then be conducted to determine it the necessary capital improvements, such as lengthening auxiliary lanes to reduce queuing, are warranted.<ref name=rodriguezanddanaher></ref>

===Intelligent TSP===
One proposal to improve bus operations is to combine CTSP with emerging connected vehicle technology (CVT) which allows two way communications between buses and traffic signal facilities and can collect more accurate information based on [[automatic vehicle location]] (AVL) systems. This TSP with CV (TSPCV) environment can supplement existing data with measurements of vehicle speed, position, acceleration and deceleration, queue lengths, arrival time, dwell time and number of passengers. In addition to simple red signal truncation and green light extension, intelligent TSPCV can reallocate green time to when it will most benefit bus movement rather than just adding time, and thus minimize adverse impacts on non-transit vehicle travel especially on intersecting side streets. Selective priority can be granted or withheld depending on factors such as whether buses are running on time or delayed, and the number of onboard passengers, in order to minimize total person delay across all modes. Bus speeds can also be adjusted to take better advantage of TSP. A recent study by the University of Virginia simulating traffic at a selected intersection found that TSPCV improves the reliability of bus service and can reduce bus delay by nearly 90% compared to less than 13% for CTSP. Benefits decline as traffic volume approaches capacity since the proposed algorithm is designed to reduce the amount of green time granted to buses to prevent extra delay to other travel, but this minimizes overall person delay.
The authors conclude that this next-generation TSP could greatly reduce bus delay at signalized intersections without causing negative effects on other traffic.<ref name=huetal>Jai Hu, Byungkyu (Brian) Park, and A. Emily Parkany, “Transit Signal Priority with Connected Vehicle Technology,” Transportation Research Record No. 2418, 2014, pp. 20-29.</ref>

==Exclusive and Intermittent Bus Lanes==
Another alternative to improve bus speed and reliability is to allow buses either exclusive or preferential use of a travel lane. This allows the bus to skip the car queues and minimizes delays experienced at traffic signals from car queuing. However, especially in areas where bus traffic is light, this approach can result in under use of valuable roadway space and lead to longer car queues at signalized intersections. As a result, even though bus passengers may enjoy reduced travel times, the total amount of delay in the system can increase as fewer cars are able to cross intersections on green lights.<ref name=gulerandmenendez>S. Ilgin Guler and Monica Menendez, [http://trb.metapress.com/content/277h85w255497224/fulltext.pdf "Evaluation of Presignals at Oversaturated Signalized Intersections,"] Transportation Research Record No. 2418, 2014, pp. 11-19.</ref> Bus lanes may also interfere with cars executing right turns. However, bus only lanes also allow for use of queue jump signal operation.<ref name=rodriguezanddanaher></ref>

===Use of Presignals===
One way that has been proposed that gives buses priority but still utilizes the full capacity of green signals is the use of a presignal placed upstream of the main signal.<ref name=gulerandmenendez>S. Ilgin Guler and Monica Menendez, "Evaluation of Presignals at Oversaturated Signalized Intersections," Transportation Research Record No. 2418, 2014, pp. 11-19.</ref> The signal is located so that there is enough space ahead of the presignal that all cars queued up at the main signal will be able to clear the intersection when the light turns green, the same as when all lanes are in mixed use. The presignal then releases the traffic to proceed to the main light which turns green; the presignal then holds further traffic to allow the traffic ahead ahead to clear. Any arriving bus is then free to move up, discharge passengers and proceed through the intersection. Automobile drivers should not experience any delays when buses are not present. A study by Guler and Menendez found that this strategy consistently performs better than dedicated bus lanes at oversaturated intersections (greater than 105% of signal capacity) by reducing total person hours of delay (bus and car) without affecting bus service reliability. At traffic levels between 85% and 105% of capacity, the system still reduced bus delays compared to mixed-use lanes. The authors note that additional benefits could be obtained if use of presignals were combined with TSP.

===Optimizing Priority Lanes===
While dedicated bus lanes can improve system reliability, isolated priority lanes often experience bottlenecks when buses reenter unrestricted traffic. A better approach is to consider a network of connected priority lanes that links lane segments together to create a series of uninterrupted routes. Hadas and Ceder identify eight ways buses can be given preferential treatment on street lanes: exclusive curb lane; semi-exclusive curb lane, lane shared with turning cars only; exclusive median lane with stop island; exclusive center lane; bus malls; exclusive freeway and highway lanes; highway ramp bypasses; and exclusive lanes to bypass traffic bottlenecks.<ref name=hadasandceder>Yuval Hadas and Avishai (Avi) Ceder, [http://trb.metapress.com/content/kw11g5x448787441/fulltext.pdf "Optimal Connected Urban Bus Network of Priority Lanes,"] Transportation Research Record No. 2418, 2014, pp. 49-57.</ref> Building on the work of Mesbah et al.,<ref>See notes 5-8 in Hadas and Ceder, supra.</ref> the authors have developed an innovative systemwide approach for designing a set of continuous priority bus lanes that considers all eight options, balances all bus route starts, stations, and ends, and maximizes travel time savings. They suggest that such a network will allow for "faster vehicle movement with fewer interruptions, increased reliability of transfers, and better schedule adherence related to performance."<ref>Hadas and Ceder, supra, p. 56.</ref>

==References==
<references/>

==Further Reading==

Jai Hu, Byungkyu (Brian) Park, and A. Emily Parkany, [http://trb.metapress.com/content/t54ku7636511k6p8/fulltext.pdf “Transit Signal Priority with Connected Vehicle Technology,”] Transportation Research Record No. 2418, 2014, pp. 20-29.
:This study proposes a new logic to overcome adverse effects of TSP using connected vehicle technology, including two-way communications between buses and the traffic signal controller, to generate accurate bus location information and data on number of passengers. The key feature is green time reallocation, which moves green time instead of adding extra green time, in response to overall person delay on the system. The proposal is then evaluated using both analytical and microscopic simulation approaches. Results showed that the proposed TSP logic reduced bus delay between 9% and 84% compared with conventional TSP and between 36% and 88% compared with the no-TSP condition, with no significant negative effects.

Tony Hernandez, [http://trb.metapress.com/content/e0281525127w4087/fulltext.pdf “Flex Scheduling for Bus Arrival Time Prediction,”] Transportation Research Record No. 2418, 2014, pp. 110-115.
:This study used three weeks of Chicago, Illinois, Transit Authority bus route GPS data to compare the performance of several commonly used methods and algorithms for predicting bus arrival times, concluding that the use of computationally intensive machine learning algorithms, such as support vector regression, k nearest neighbor regression, and neural networks, is unnecessary. Simpler linear models combined with the real-time GPS bus location information could be used to determine explicitly the approximate historical interstop travel times for any time of the day and any day of the week, resulting in a flex schedule that was independent of scheduled departure or arrival times, and obviating the need for additional data collection.

Adriana Rodriguez and Alan R. Danaher, [http://trb.metapress.com/content/v761533070312217/fulltext.pdf “Operational Comparison of Transit Signal Priority Strategies,”] Transportation Research Record No. 2418, 2014, pp. 84-91.
:General traffic can interfere with buses operating in mixed traffic and cause reductions in travel speed and system capacity. This paper presents a methodology for evaluating the impacts of TSP treatments on transit operations at a specific intersection by comparing various TSP options to determine which would give the highest travel time savings for signalized intersections along the study corridor.

S. Ilgin Guler and Monica Menendez, [http://trb.metapress.com/content/277h85w255497224/fulltext.pdf "Evaluation of Presignals at Oversaturated Signalized Intersections,"] Transportation Research Record No. 2418, 2014, pp. 11-19.
:This paper quantifies the benefits on traffic flow of using presignals in terms of reducing systemwide total person hours of delay, specifically for oversaturated intersections. Results showed that presignals provided the lowest delay compared with a dedicated lane or mixed lane strategy, and that for oversaturated intersections, presignals were better for the system than dedicated bus lanes. Moreover, presignals could decrease the total person hours of delay compared with mixed lanes for large car demands.

Yuval Hadas and Avishai (Avi) Ceder, [http://trb.metapress.com/content/kw11g5x448787441/fulltext.pdf "Optimal Connected Urban Bus Network of Priority Lanes,"] Transportation Research Record No. 2418, 2014, pp. 49-57.
:This paper presents a new model for selecting an optimal network of public transport (PT) priority lanes that would increase the reliability of transfers and provide better adherence to schedule performance. The study model was designed to maximize total travel time savings and, at the same time, maintain balanced origin and destination terminals, given budget constraints. It was used successfully in a case study of Petah Tikva, a midsize city in Israel, to produce an optimal network of priority lanes.

A Guide for Implementing Bus on Shoulder (BOS) Systems

Transit Cooperative Research Program (TCRP) Report 151, [http://onlinepubs.trb.org/onlinepubs/tcrp/tcrp_rpt_151.pdf "A Guide for Implementing Bus on Shoulder (BOS) Systems,"] 2012.
:This TRB report provides guidelines for the planning, design, and implementation of BOS operations along urban freeways and major arterials.

[[Category:Managing transit]]
[[Category:operating effectiveness]]

Bus prioritization

2015-03-28T00:09:06Z

Mgarrett:

2015-03-27T23:54:29Z

Mgarrett: /* Introduction */

[[Category:Technology]]
==Introduction==

Near field communication (NFC) is the technology that enables smart cards to be ‘contactless.’ They use an unpowered chip that communicates with the on-board or in-station fare collection system and deducts value when used. Smart cards or cell phones using NFC only need to be waved over the fare payment machine aboard the transit vehicle or before going through the turnstile leading to the vehicles. This is in contrast to ‘contact’ smart cards, which need to be inserted into the machine. NFC is a specific type of [[radio frequency identification (RFID)]] technology that limits the communication distance to four inches or less.

NFC technology is already in use in mobile phones for other applications, such as transferring files between phones or computers, but it has only been applied for transit payments in a few places (there is a pilot project in New Jersey using Google Wallet).

[[Image:TapFarebox.jpg|right|thumb|350px|This Los Angeles Metro TAP farebox uses NFC to read users' fare cards. Photo by Flickr user fredcamino]]

==Advantages of NFC==

Contactless smart cards with NFC technology may be easier to use than contact cards for people who have difficulties with fine motor skills. Contactless smart cards also speed the boarding process and are convenient for passengers who prefer to pre-pay for transit service. They also reduce some of the problems associated with cash systems, such as the cost of transporting and guarding cash. However, because of the popularity of cash payment with customers it will likely need to remain a payment option. For this reason, a study in Los Angeles showed that a financial incentive for using a smart card helped to boost its use.<ref>Transit Cooperative Research Project. [http://www.trb.org/main/blurbs/153815.aspx “TCRP Report 32: Multipurpose Transit Payment Media.”] 1998.</ref>

Because the financial services industry offers NFC-enabled contact-less bank cards, an NFC reader may be configured to accept cash payment in addition to accepting automated fare media.

==Challenges in Application==
Smart cards and NFC technology face some challenges to being applied to transit fare payment. Choosing an open or closed system will determine how much partnership or collaboration will be needed for managing the system. More information on open and closed systems can be found in the article on [[automated fare media]]. Open systems will require more collaboration, but the burden of managing the system can be shared with other merchants or transit providers. Open systems in NFC technology also offer the advantage of giving riders the choice of using their cards for a variety of purchases and uses. For example, in Japan, smart cards are used to pay for transit, as well as public telephones and parking.<ref>Iseki, Hiroyuki, Alexander Demisch, Brian D. Taylor, and Allison C. Yoh. [[media:Evaluating_Smart_Cards.pdf|“Evaluating the Costs and Benefits of Transit Smart Cards.”]] 2008.</ref> In general, though, benefits and costs can vary widely and, according to one recent study, the costs of deployment and implementation are primarily borne by the system provider, while the benefits are enjoyed by passengers and individual operators.<ref>Iseki, Hiroyuki, Alexander Demisch, Brian D. Taylor, and Allison C. Yoh. [[media:Evaluating_Smart_Cards.pdf|“Evaluating the Costs and Benefits of Transit Smart Cards.”]] 2008.</ref>

==References==

<references />

==Additional Reading==

Transit Cooperative Research Project. [http://www.trb.org/main/blurbs/153815.aspx “TCRP Report 32: Multipurpose Transit Payment Media.”] 1998.
: Sponsored by the Federal Transit Administration, this report outlines the benefits of and challenges of implementing a wide variety of fare media, including near field communications and other smart card technologies.

Smart Card Alliance. [http://www.smartcardalliance.org/pages/publications-near-field-communication-and-transit “Near Field Communication (NFC) and Transit: Applications, Technology and Implementation Considerations.”] 2012.
: This white paper, published by an industry group, discusses the potential to expand NFC technology in transit fare payment. In includes the possibility of using NFC-enabled smart cards for open bank payment, as well as the more common smart cards, as well as a detailed description of the full NFC ecosystem necessary. The appendix provides a comprehensive list of transit systems that currently use NFC technology.

Keitel, Philip. Federal Reserve Bank of Philadelphia.[http://www.philadelphiafed.org/consumer-credit-and-payments/payment-cards-center/publications/discussion-papers/2011/D-2011-April-Chase-Transit.pdf "The Electronification of Transit Fare Payments: Examining the Case for Partnerships Between Payments Firms and Transit Agencies."] 2011.
: This Federal Reserve Bank Payment Cards Center discussion paper examines alternatives for accepting cash fare payment from contact-less bank cards. The report discusses fees levied by financial institutions, avoided ticket vending machine infrastructure and maintenance, and consumer experiences with contact-less bank cards.