Browsing by Author "Liao, Chen-Fu"

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Auto accessibility measures to non-work destinations for the period of 1995, 2000, and 2005 for the Twin Cities region
(2018-11-09) Levinson, David M; Liao, Chen-Fu; david.levinson@sydney.edu.au; Levinson, David M
Highway-based accessibility measures to jobs and labor for the Twin Cities region were previous computed. The data here give the auto accessibility measures (TAZ level) to other destination types such as retail, entertainment, food/restaurant and recreation for the period of 1995, 2000 and 2005. The resulting access measures to different destinations will provide a comprehensive evaluation of accessibility in the Twin Cities region, which can help in operational planning and in public involvement activities of transportation agencies to ascertain how investments, transportation strategies, market conditions, and land use policies affect the performance of the transportation-land use system.
Bus Signal Priority Based on GPS and Wireless Communications Phase I - Simulation Study
(2006-07-01) Liao, Chen-Fu; Davis, Gary A.
The Minneapolis-St. Paul metropolitan transit agency has installed Global Positioning System (GPS) equipment in transit vehicles for the purpose of monitoring vehicle locations and schedules in order to provide more reliable transit services. This research project evaluates the potential use of vehicle-mounted GPS to develop a Transit Signal Priority system that improves the efficiency of transit.
Transit Signal Priority (TSP) for transit has been proposed as an efficient way to improve transit travel & operation. Bus signal priority has been implemented in several US cities to provide more reliable travel and improve customer ride quality. Current signal priority strategies implemented in various US cities mostly utilized sensors to detect buses at a fixed or at a preset distance away from the intersection. Signal priority is usually granted after a preprogrammed time offset after detection. The proposed study would take advantage of the GPS system on the buses in Minneapolis and develop a signal priority strategy which could consider the bus' timeliness with respect to its schedule, its number of passengers, location and speed.
A Bus Signal Priority System Using Automatic Vehicle Location / Global Position Systems and Wireless Communication Systems
(University of Minnesota Center for Transportation Studies, 2008-12) Liao, Chen-Fu; Davis, Gary A.; Iyer, Priya
Current signal priority strategies implemented in various US cities mostly utilize sensors to detect buses at a fixed or preset distance away from an intersection. Traditional presence detection systems, ideally designed for emergency vehicles, usually send signal priority request after a preprogrammed time offset as soon as transit vehicles were detected without the consideration of bus readiness. The objective of this study is to integrate the already equipped Global Positioning System/Automated Vehicle Location (GPS/AVL) system on the buses in Minneapolis and develop an adaptive signal priority system that could consider the bus schedule adherence, its number of passengers, location and speed. Buses can communicate with intersection signal controllers using wireless technology to request for signal priority. Similar setup can also be utilized for other transit-related Intelligent Transportation Systems (ITS) applications. The City of Minneapolis recently deployed wireless technology to provide residents, businesses and visitors with wireless broadband access anywhere in the city. Communication with the roadside unit (e.g., traffic controller) for signal priority may be established using the readily available 802.11x WLAN or the Dedicated Short Range Communication (DSRC) 802.11p protocol currently under development for wireless access in vehicular environment. This report documents the development, verification and validation of the embedded signal priority prototype systems, field testing results and limitations of using the City of Minneapolis Wi-Fi network for Transit Signal Priority (TSP).
Data-Driven Support Tools for Transit Data Analysis, Scheduling and Planning
(Intelligent Transportation Systems Institute Center for Transportation Studies, 2011-07) Liao, Chen-Fu
Many transit agencies in the U.S. have instrumented their fleet with Automatic Data Collection Systems (ADCS) to monitor the performance of transit vehicles, support schedule planning and improve quality of services. The objective of this study is to use an urban local route (Metro Transit Route 10 in Twin Cities) as a case study and develop a route-based trip time model to support scheduling and planning while applying different transit strategies. Usually, timepoints (TP) are virtually placed on a transit route to monitor its schedule adherence and system performance. Empirical TP time and inter-TP link travel time models are developed. The TP-based models consider key parameters such as number of passengers boarding and alighting, fare payment type, bus type, bus load (seat availability), stop location (nearside or far side), traffic signal and volume that affect bus travel time. TP time and inter-TP link travel time of bus route 10 along Central Avenue between downtown Minneapolis and Northtown were analyzed to describe the relationship between trip travel time and primary independent variables. Regression models were calibrated and validated by comparing the simulation results with existing schedule using adjusted travel time derived from data analyses. The route-based transit simulation model can support Metro Transit in evaluating different schedule plans, stop consolidations, and other strategies. The transit model provides an opportunity to predict and evaluate potential impact of different transit strategies prior to deployment.
Deploy and Test a Smartphone-Based Accessible Traffic Information System for the Visually Impaired
(Minnesota Department of Transportation, 2020-10) Liao, Chen-Fu; Davis, Brian
An increasing number of Accessible Pedestrian Signals (APS) have been installed at new or upgraded intersections to assist people with vision impairment to navigate streets. For un-signalized intersections and intersections without APS, people with vision impairment have to rely on their own orientation and mobility skills to gather necessary information to navigate to their destinations. Previously, a smartphone-based accessible pedestrian system was developed to support wayfinding and navigation for people with vision impairment at both signalized and un-signalized intersections. A digital map was also created to support the wayfinding app. This system allows a visually impaired pedestrian to receive signal timing and intersection geometry information from a smartphone app for wayfinding assistance. A beacon using Bluetooth Low Energy (BLE) technology helps to identify a pedestrian's location when he or she travels in a GPS-unfriendly environment. A network of Bluetooth beacons ensures that correct traffic information is provided to the visually impaired at the right location. This project leverages the previous work by installing the system at a number of intersections in downtown Stillwater, Minnesota, where MnDOT operates the signalized intersections. In this study, researchers interface with the traffic controllers to broadcast traffic signal phasing and timing (SPaT) information through a secured and private wireless network for visually impaired users. The aim is to test the smartphone-based accessible system and evaluate the effectiveness and usefulness of the system in supporting wayfinding and navigation while the visually impaired travel through signalized and un-signalized intersections.
Development of a Navigation System Using Smartphone and Bluetooth Technologies to Help the Visually Impaired Navigate Work Zones Safely
(Minnesota Department of Transportation, 2014-02) Liao, Chen-Fu
According to statistics from the Federal Highway Administration (FHWA), each year approximately 17% of all work zone fatalities are pedestrians. People who are visually impaired often encounter physical and information barriers that limit their accessibility and mobility. A survey was conducted among 10 visually impaired participants as a starting point to understand their challenges and what types of information are helpful in providing bypass or routing instructions to them around work zones. The survey results were incorporated into development of guiding documents in determining information elements that are essential and useful for providing routing instructions to the visually impaired around work zones. Building on our previous efforts to provide geometry and signal timing to the visually impaired at signalized intersections, a smartphone-based navigation system was developed and integrated with navigational audible information to alert pedestrians at decision points prior to their arrival at a work zone. The recommended message elements from survey results were implemented in a smartphone app that uses GPS and Bluetooth technologies to determine a user’s location. When a work zone is detected, the smartphone will vibrate to alert users and the app will then announce a corresponding audible message to users. The visually impaired users can perform a single tap on the smartphone to repeat the messages, if needed. Functionality testing and system validation of the smartphone app were performed by attaching four Bluetooth beacons to light posts near a construction site in St. Paul, MN. Additional research is needed to conduct experiments with visually impaired users and evaluate system reliability and usefulness.
Development of Driver Assistance Systems to Support Snowplow Operations
(Center for Transportation Studies, University of Minnesota, 2018-08) Liao, Chen-Fu; Morris, Nichole L.; Achtemeier, Jacob; Alexander, Lee; Davis, Brian; Donath, Max; Parikh, Gordon
Snowplow operators are often tasked with numerous monitoring and operational activities that they need to do simultaneously while removing snow and spreading deicing agents on the road. Driver assist systems were considered for 3 applications: gang plowing, backup assist, and lane boundary guidance. We evaluated the system performance and position accuracy of commercially available Dedicated Short Range Communication (DSRC) Onboard Units (OBU) for gang plowing. Our results indicated that the positioning accuracy of the OBUs was inadequate for providing the plow operator with sufficient information to maintain spacing between two vehicles. The backup assist system and lane boundary guidance system were developed and successfully deployed to support snowplow operations. Human factors studies were also conducted using a driving simulator to better understand the needs prior to designing an appropriate Human Machine Interface (HMI) for these plow operations. The radar-based backup assist system was installed on a snowplow that operates on Highway 169. The backup assist system provides an audio warning to the operator to look at the display from a rear-view camera when an object is detected. The Global Navigation Satellite System (GNSS)-based lane boundary guidance system was developed to assist plow operations when visibility is poor and lane boundary cues are limited. The lane boundary guidance system was installed on a second snowplow operating on MN-25 running between Belle Plaine and Green Isle. The lane boundary guidance received the most positive feedback from operators and is recommended for further development.
Field Testing and Evaluation of a Wireless-Based Transit Signal Priority System
(Intelligent Transportation Systems Institute, Center for Transportation Studies, 2011-10) Liao, Chen-Fu; Davis, Gary A.
Most signal priority strategies implemented in various U.S. cities used sensors to detect buses at a fixed or preset distance away from an intersection. Traditional presence detection systems, ideally designed for emergency vehicles, usually send a signal priority request after a pre-programmed time offset as soon as transit vehicles are detected without the consideration of bus readiness. As part of the Urban Partnership Agreement, Metro Transit, Minnesota Department of Transportation (MnDOT), and the City of Minneapolis have implemented Transit Signal Priority (TSP) along Central Avenue from north Minneapolis (2nd Street SE) to south of I-694 (53rd Avenue NE) with total of 27 intersections. Transit performance before and after the deployment of a TSP strategy was examined through the data analysis process to evaluate the effectiveness and benefit of a TSP strategy. The objective of this study is to deploy and validate a wireless-based TSP strategy developed from earlier studies by considering bus schedule adherence, location and speed. A TSP onboard system using embedded computer was developed to interface with EMTRAC radio modules to bypass the EMTRAC TSP algorithm on current buses. Field experiments were performed by installing University of Minnesota (UMN) TSP units on four RTE10 buses for two weeks. The EMTRAC algorithm was temporary disabled on the test vehicles. Link travel time and node dwell time on the TSP-equipped route segments are compared. The results indicated the UMN TSP algorithm gain additional 3-6% of travel time reduction as compared to other RTE10 buses operating during the two-week test period.
Implementation of Traffic Data Quality Verification for WIM Sites
(Center for Transportation Studies University of Minnesota, 2015-05) Liao, Chen-Fu; Chatterjee, Indrajit; Davis, Gary A.
Weigh-In-Motion (WIM) system tends to go out of calibration from time to time, as a result generate biased and inaccurate measurements. Several external factors such as vehicle speed, weather, pavement conditions, etc. can be attributed to such anomaly. To overcome this problem, a statistical quality control technique is warranted that would provide the WIM operator with some guidelines whenever the system tends to go out of calibration. A mixture modeling technique using Expectation Maximization (EM) algorithm was implemented to divide the Gross Vehicle Weight (GVW) measurements of vehicle class 9 into three components, (unloaded, partially loaded, and fully loaded). Cumulative Sum (CUSUM) statistical process technique was used to identify any abrupt change in mean level of GVW measurements. Special attention was given to the presence of auto-correlation in the data by fitting an auto-regressive time series model and then performing CUSUM analysis on the fitted residuals. A data analysis software tool was developed to perform EM Fitting and CUSUM analyses. The EM analysis takes monthly WIM raw data and estimates the mean and deviations of GVW of class 9 fully loaded trucks. Results of the EM analyses are stored in a file directory for CUSUM analysis. Output from the CUSUM analysis will indicate whether there is any sensor drift during the analysis period. Results from the analysis suggest that the proposed methodology is able to estimate a shift in the WIM sensor accurately and also indicate the time point when the WIM system went out-of-calibration. A data analysis software tool, WIM Data Analyst, was developed using the Microsoft Visual Studio software development package based on the Microsoft Windows .NET framework. An open source software tool called R.NET was integrated into the Microsoft .NET framework to interface with the R software which is another open source software package for statistical computing and analysis.
Improving intersection safety through variable speed limits for connected vehicles
(Center for Transportation Studies, University of Minnesota, 2019-05) Levin, Michael; Chen, Rongsheng; Liao, Chen-Fu; Zhang, Tab
Autonomous vehicles create new opportunities for innovative intelligent traffic systems. Variable speed limits, which is a speed management systems that can adjust the speed limit according to traffic condition or predefined speed control algorithm on different road segments, can be better implemented with the cooperation of autonomous vehicles. These compliant vehicles can automatically follow speed limits. However, non-compliant vehicles will attempt to pass the moving bottleneck created by the compliant vehicle. This project builds a multi-class cell transmission model to represent the relation between traffic flow parameters. This model can calculate flows of both compliant and non-compliant vehicles. An algorithm is proposed to calculate variable speed limits for each cell of the cell transmission model. This control algorithm is designed to reduce the stop-and-go behavior of vehicles at traffic signals. Simulation is used to test the effects of VSLs on an example network. The result shows that VSL is effective at reducing the energy consumption of the whole system and reduce the likelihood of crash occurrence.
An Integrated Assistive System to Support Wayfinding and Situation Awareness for People with Vision Impairment
(2016-05) Liao, Chen-Fu
People with vision impairment usually use a white cane as their primary tool for wayfinding and obstacle detection. Environmental cues, though not always reliable, are used to support the decision making of the visually impaired at various levels of navigation and situation awareness. Due to differences in spatial perception as compared to sighted people, they often encounter physical as well as information barriers along a trip. In order to improve their mobility, accessibility and level of confidence in using our transportation system, it is important to remove not only the physical barriers but also the information barriers that could potentially impede their mobility and undermine safety. Many assistive systems have been developed in the past for visually impaired users to navigate and find their way. However, most of these systems were not adopted by users mostly due to the inconvenience of using such systems. In this research, we developed a mobile accessible information system that allows people with vision impairment to receive transportation information at key locations where decision making is necessary. A smartphone-based personal assistive system, called MAPS (Mobile Accessible Pedestrian System), was developed to provide intersection geometry and signal timing information, not available from other apps in the market for people with vision impairment. In addition, the MAPS incorporates a geospatial database with Bluetooth beacon information that allows the MAPS to provide navigation assistance, situation awareness, and wayfinding to users even when a GPS solution is not available. The MAPS app communicates with the traffic signal controller through a secured wireless link to obtain real-time Signal Phasing and Timing (SPaT) information, which together then inform visually impaired pedestrians with their current locations and when to cross streets. A self-monitoring infrastructure using a network of Bluetooth Low Energy (BLE) beacons was developed to ensure the information integrity of the network. The key contributions of this dissertation include the development of: • A smartphone-based navigation and decision support system that incorporates intersection geometry and traffic signal information for people with vision impairment, • A simple user’s interface (using a single or double-tap on a smartphone screen) that is easy for the visually impaired to learn and use, • Standardized message elements for an audible work zone bypass routing information system, • A self-monitoring infrastructure using a network of commercial off-the-shelf (COTS) low-cost BLE beacons, (including customized firmware allowing BLE beacons to monitor each other), • A crowdsourcing approach using users’ smartphones to monitor the status of BLE beacons and update messages associated with beacons, • A cloud-based geospatial database to support navigation by incorporating BLE beacon localization information when a GPS solution is not available, • A Singular Value Decomposition (SVD) based Multivariable Regression (MR) algorithm together with an Extended Kalman Filter (EKF) technique using beacon localization to provide a positioning solution by the smartphone even if a GPS solution is unavailable, and • Statistical methodologies and wireless signal fingerprinting techniques to monitor BLE beacons in a network in order to determine when a beacon is moved, removed or disappears. The intent of the MAPS is not to undermine the maintenance of skills and strategies that people with vision impairment have learned for navigation and wayfinding. Instead, the system aims to support their wayfinding capability, extend mobility and accessibility, and improve safety for the blind and visually impaired. This self-monitoring infrastructure ensures that correct information is provided to users at the right location when needed. This thesis also introduces the idea of using the same system to warn sighted pedestrians about approaching an intersection when they are distracted by looking at their smartphone.
Investigating inductive loop signature technology for statewide vehicle classification counts
(Minnesota Department of Transportation, 2018-10) Liao, Chen-Fu
An inductive loop signature technology was previously developed by a US Department of Transportation (DOT) Small Business Innovation Research (SBIR) program to classify vehicles along a section of the roadway using existing inductive loop detectors installed under the pavement. It was tested and demonstrated in California that the loop signature system could obtain more accurate, reliable and comprehensive traffic performance measures for transportation agencies. Results from the studies in California indicated that inductive loop signature technology was able to re-identify and classify vehicles along a section of roadway and provide reliable performance measures for assessing progress, at the local, State, or national level. This study aimed to take advantage of the outcomes from the loop signature development to validate the performance with ground truth vehicle classification data in the Twin Cities Metropolitan Area (TCMA). Based on the results from individual vehicle class verification, class 2 vehicles had the highest match rate of 90%. Possible causes of classification accuracy for other vehicle classes may include types of loops, sensitivity of inductive loops that generates a shadow loop signal on neighboring lanes, and classification library that was built based on California data. To further understand the causes of loop signature performance and improve the classification accuracy, the author suggests performing additional data verification at a permanent Automatic Traffic Recorder (ATR) site. There is also an opportunity to investigate the classification algorithm and develop an enhanced pattern recognition methodology based on the raw loop signature profile of various types of vehicles in Minnesota.
Investigating the Effectiveness of Using Bluetooth Low-Energy Technology to Trigger In-Vehicle Messages in Work Zones
(Minnesota Department of Transportation, 2016-12) Liao, Chen-Fu; Donath, Max
In order to reduce risky behavior around workzones, this project examines the effectiveness of using invehicle messages to heighten drivers’ awareness of safety-critical and pertinent workzone information. This investigation centers around an inexpensive technology based on Bluetooth low-energy (BLE) tags that can be deployed in or ahead of the workzone. A smartphone app was developed to trigger nondistracting, auditory-visual messages in a smartphone mounted in a vehicle within range of the BLE workzone tags. Messages associated with BLE tags around the workzone can be updated remotely in real time and as such may provide significantly improved situational awareness about dynamic conditions at workzones such as: awareness of workers on site, changing traffic conditions, or hazards in the environment. Experiment results indicate that while travelling at 70 mph (113 km/h), the smartphone app is able to successfully detect a long-range BLE tag placed over 410 feet (125 meters) away on a traffic barrel on a roadway shoulder. Additional experiments are being conducted to validate the system performance under different roadway geometry, traffic, and weather conditions.
Measure of Truck Delay and Reliability at the Corridor Level
(Minnesota Department of Transportation, 2018-04) Liao, Chen-Fu
Freight transportation provides a significant contribution to our nation’s economy. A reliable and accessible freight network enables business in the Twin Cities to be more competitive in the Upper Midwest region. Accurate and reliable freight data on freight activity is essential for freight planning, forecasting and decision making on infrastructure investment. A report entitled “Twin Cities Metropolitan Region Freight Study” published by MnDOT and the Metropolitan Council in 2013, suggested a need to understand where and when trucks are most affected by congestion. A framework for truck data collection and analysis was recommended to better understand the relationships between truck traffic and congestion in rush hours. Building upon our previous study to measure freight mobility and reliability along 38 key freight corridors in the Twin Cities Metropolitan Area (TCMA), this study leveraged our previous effort to implement the performance measures using the National Performance Measurement Research Dataset (NPMRDS) from the USDOT. The researcher team first worked with stakeholders to prioritize a list of key freight corridors with recurring congestion in peak periods in the TCMA. We used 24 months of NPMRDS data to measure travel time reliability and estimate truck delay at the corridor level and to identify system impediments during the peak hours. The objective is to use performance measures for assessing impact of truck congestions and identifying operational bottlenecks or physical constraints. Trucking activity nearby a congested area is examined to analyze traffic pattern and investigate possible causes of recurring congestions.
Metro Transit Service Reliability Measures Assessment
(2017-04) Liao, Chen-Fu
The objectives of this project are to expand the definitions of transit service reliability, determine which ones are applicable to Metro Transit's services, and provide a proof of concept of how these measures could be applied using available operations data. We first reviewed common service reliability measures that are used for bus and light rail services both in the United States and internationally. We identified 18 common service reliability measures and categorized them into four groups (see Appendix A). Four service reliability measures, On-Time Performance (OTP), Excess Wait Time (EWT), Gap Assessment (GA), and the 90th percentile of lateness (LA90), were finalized for further evaluation. We applied the finalized service reliability measure on 13 high frequency routes (route 2, 4, 5, 6, 10, 17, 18, 19, 21, 54, 64, 84, and 515) and 2 LRT lines (901-blue and 902 - green lines) using transit operations data from Jan. 2014 to Apr. 2016. The following selection criteria are applied to evaluate how the 4 selected measures are applicable to transit services and how they might be used most effectively by Metro Transit. 1. Is the service reliability measure easy to interpret? 2. Is data available for both historical reporting and real-time applications? 3. Can the metric provide a different perspective as compared to current OTP? 4. Can the metric support best operational practices? OTP is the current key performance index used by the Metro Transit. It will continue to be used as a baseline measure for service reliability. In addition to OTP, GA, and LA90 were selected for implementation. GA is a customer focused headway adherence measure. It could be easily implemented based on existing transit operations data. In addition to the OTP, the LA90 measure describes the typical late range of a transit service. It indicates 'how badly' the transit services are not meeting the OTP threshold. The excess wait time (EWT) is not recommended for implementation because it is difficult to interpret and the computed results are unable to provide a clear indication of operations performance. This study demonstrates how the identified measures could be applied using available operations data currently collected by Metro Transit to improve quality of service.
A Positioning and Mapping Methodology Using Bluetooth and Smartphone Technologies to Support Situation Awareness and Wayfinding for the Visually Impaired
(Center for Transportation Studies, University of Minnesota, 2018-11) Liao, Chen-Fu
People with vision impairment often face challenges while traveling in an unfamiliar environment largely due to uncertainty and insufficient accessible information. To improve mobility, accessibility, and the level of confidence the visually impaired experience in using the transportation system, it is important to remove information barriers that could potentially impede their mobility. A "condition aware" infrastructure using Bluetooth low-energy (BLE) technology was developed to provide up-to-date and correct audible information to users at the right location. A Multivariable Regression (MR) algorithm using the Singular Value Decomposition (SVD) technique was introduced to model the relationship between Bluetooth Received Signal Strength (RSS) and the actual ranging distance in an outdoor environment. This methodology reduced the environmental uncertainty and dynamic nature of RSS measurements in a Bluetooth network. The range output from the MR-SVD model was integrated with an extended Kalman filter to provide positioning and mapping solutions. Using 6 BLE beacons at an intersection in St. Paul, Minnesota, our approach achieved an average position accuracy of 2.5 m and 3.8 m in X and Y directions, respectively. A few statistical techniques were implemented and were able to successfully detect whether the location of one or multiple BLE beacons in a network changed based on Bluetooth RSS indications. With the self-monitoring network, information associated with each Bluetooth beacon can be provided to the visually impaired at the right location to support their wayfinding in a transportation network.
Refining Inductive Loop Signature Technology for Statewide Vehicle Classification Counts
(Minnesota Department of Transportation, 2021-12) Liao, Chen-Fu
Transportation agencies in the U.S. use devices such as loop detectors, automatic traffic recorders (ATR), or weigh-in-motion (WIM) sensors to monitor the performance of traffic network for planning, forecasting, and traffic operations. With a limited number of ATR and WIM sensors deployed throughout the state roadways, temporary double tubes are often deployed to get axle-based vehicle classification counts. An inductive loop signature technology previously developed by a Small Business Innovation Research (SBIR) program sponsored by the US Department of Transportation is used to classify vehicles using existing loops. This technology has the potential to save time and money while providing the state, counties or cities more data especially in the metro area where loop detectors have already been installed. This research leveraged the outcomes from previous development to validate the classification accuracy with video data. A loop signature system was initially installed at a traffic station in Jordan, MN, to evaluate its performance. The system was later moved to another location on US-52 near Coates, MN, to validate its classification accuracy with more heavy- vehicle traffic. Individual vehicle records were manually verified and validated with ground-truth video data using both the 13 and 7-bin classification schemes from the Federal Highway Administration (FHWA) and the Highway Performance Monitoring System (HPMS). The combined results from both test sites indicated that the loop signature technology had an overall classification accuracy of 93% and 96% using the FHWA and HPMS schemes, respectively. The classification performance can be further improved by including additional vehicle signatures from the state to the classification library.
Smartphone-Based Interventions for Sustainable Travel Behavior: The University of Minnesota Parking Contract Holder Study
(Center for Transportation Studies, University of Minnesota, 2020-10) Fan, Yingling; Becker, Andy; Ryan, Galen; Wolfson, Julian; Guthrie, Andrew; Liao, Chen-Fu
Innovative mobility apps have the power to transform the relationship between transportation networks and travelers. Capitalizing on the recent advancement in smartphone technology, this project develops a smartphone-based behavior intervention tool—named Daynamica—to provide customized, user-centered messages and graphics for promoting travel mode shifts from driving to more sustainable modes. The project tests the effectiveness of the intervention tool among University of Minnesota (UMN) parking contract holders. For each car trip made by a participant, the tool provides a mode shift plan based on the exact trip origin and destination. The tool also provides information describing the environmental impacts of the specific car trip and the personal benefits of switching to the alternative mode. The findings show that although 92 percent of participants are interested in trying alternative modes, in general, when it comes to specific trip considerations, only 36 percent of the car trips are considered reasonable alternative modes. There is ample interest among the most car-dependent population—parking contract holders—to explore alternative mode options; however, their interest is tempered by the limited alternative mode offerings in the region. Thus, it is recommended that transportation practitioners and policy makers improve these offerings. Furthermore, this research generates useful data to identify factors influencing mode shifting. Housing ownership, being male, making stops during the trip, and a late departure time for the morning commute are negatively associated with participants' receptiveness toward mode shifting. Finally, the report includes a novel analysis exploring the activity/trip chaining behaviors of the study participants.
Smartphone-Based Travel Experience Sampling and Behavior Intervention among Young Adults
(Intelligent Transportation Systems Institute, Center for Transportation Studies, University of Minnesota, 2012-05) Fan, Yingling; Chen, Qian; Liao, Chen-Fu; Douma, Frank
This research project aims to develop a data collection application that enables real-time tracking and reporting of the health-related impacts of travel behavior. Using computing, communication, and sensing capabilities of smartphones, an Android phone application—named UbiActive—was developed to collect real-time travel-related physical activity and psychological well-being data from phone users. The application was tested on multiple Android phones, among which Nexus S and HTC Magic were found to produce comparable physical activity outputs with the commercially available accelerometer. The application was further tested in a three-week field study for its viability for real-time data collection and behavior intervention against unhealthy travel behavior. Twenty-three young adults were recruited and randomized into intervention and control groups. Both groups were asked to install UbiActive on their phone and wear their phone on their right hip during all waking hours for three consecutive weeks. The intervention group was provided information on impacts of their travel behavior on physical activity and psychological well-being. No information was provided to the control group. After the field study, all participants were asked to complete a web-based exit survey that was comprised of questions about their general participation experience and specific concerns about the study design, application, compliance requirements, and privacy issues. Findings from the field study show that UbiActive has high potential in collecting travel-related physical activity and psychological experience data, but limited effectiveness in behavior intervention. Findings from the exit survey provide useful insights into potential improvement areas of the study and the UbiActive application.
Test and Evaluate a Bluetooth Based In-Vehicle Message System to Alert Motorists in Work Zones
(Center for Transportation Studies, University of Minnesota, 2019-05) Liao, Chen-Fu
Safe and efficient traffic flow in a work zone is a major concern for transportation agencies. To reduce risky behavior around work zones, we have developed a prototype system to investigate the feasibility of using in-vehicle messages to increase drivers’ awareness of safety-critical and pertinent work zone information. Our previous effort focused on an inexpensive technology based on Bluetooth low energy (BLE) beacons that can be deployed in or ahead of the work zone. A smartphone app, called WorkzoneAlert, was developed to trigger non-distracting, auditory messages in a smartphone mounted in a vehicle within range of the BLE beacons. Messages associated with BLE beacons around the work zone can be updated remotely in real time and thus could provide significantly improved situational awareness about dynamic conditions in work zones, such as awareness of workers on site, changing traffic conditions, or hazards in the environment. We incorporated the recommended in-vehicle message elements and user interface from a human factors study previously conducted by the HumanFirst lab and deployed the in-vehicle work zone information system at three construction sites (CSAH 53, CSAH 112, and MN-65) in the Twin Cities metropolitan area (TCMA). Our field test results indicated that the WorkzoneAlert app is able to reliably detect the BLE beacon placed an average of 127 m away on traffic signs or portable radar speed signs and successfully announce the corresponding message associated with each BLE beacon.

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