1. The document evaluates telecommuting as a trip reduction measure using data from a California government employee pilot program.
2. It finds that telecommuting leads to a substantial reduction in trip generation, vehicle miles traveled, peak period travel, car use, and freeway travel, without increasing non-work trips.
3. However, the long term impacts are complex as telecommuting may change activity and travel patterns as workers and households adapt.
This document summarizes a study on cellular phone users in the San Francisco Bay Area. A survey was conducted of 35,000 GTE Mobilnet customers to assess the impact of cellular communication on driver behavior and travel patterns. Key findings include:
1) The primary transportation effect of cellular phones is on trip scheduling and frequency, with over 60% of respondents reporting it affected their travel.
2) Only 15% of respondents obtained traffic information when expecting congestion, due to the lack of real-time traffic info in the Bay Area.
3) Cellular phones likely alter trip patterns as people adapt activities, but may not significantly affect total trip generation on their own. Route guidance could have a greater impact
The Driving Factors Behind Successful Carpool Formation and UseSmart Commute
This document summarizes a study examining factors that influence successful carpool formation and use through an online carpooling service called Carpool Zone. The study aims to understand individual and spatial factors that affect carpooling by analyzing user data from Carpool Zone. Previous literature found that costs, scheduling, and access to potential matches are important influences on carpooling. The study will analyze user characteristics, vehicle access, attitudes, and match accessibility to understand carpooling behavior. Insights from the study could help improve carpooling programs and policies.
This document discusses technologies that can encourage greater public transportation use. It summarizes that location-tracking mobile apps increase passengers' confidence by providing real-time transit information. On-demand transportation services can increase route efficiency. Smart cards and contactless payments alleviate issues with cash and provide user data to help transit agencies. Future technologies like bike sharing, driverless vehicles, and personal rapid transit could further transform public transportation.
Drivers’ and passengers’ perspectives on factors influencingAlexander Decker
The document discusses factors that influence intercity bus travel time on the route between Accra and Takoradi in Ghana based on interviews with drivers and passengers. Key factors identified include the number of passengers on board which determines the number of stops, purpose of travel which influences a passenger's sensitivity to time, traffic volume which impacts speed, and speed limits which prevent drivers from traveling faster. Misunderstandings between drivers and passengers about expected travel time can cause tension.
This document discusses an online budget path planning mobile application. It aims to analyze budget approaches for tours by determining travel costs in real-time using personalized traveler information from smartphones. The application would help travelers understand costs for different transportation options like trains and flights. It collects data from multiple sources to compare to exhaustive search methods while maintaining service quality. Emergency helpline numbers are also provided for different places in India.
Pay-As-You-Drive is a variable pricing model for auto insurance, where the more you drive the more you pay - the topic of my "Middle Year" thesis. Here the interview report, which was an exercise in writing according to a designated format and tone.
Large cities in developing countries are characterized by growth in automobile ownership, insufficient
transportation infrastructure and service development. These cities often suffer from congestion, poor mobility
and accessibility, significant economic waste, adverse environmental impact and safety problems. This paper
focuses on identification of travel time characteristics and other traffic parameters and to develop a predictive
model for travel time on Akure major roads. Data on travel time were collected for vehicles during the morning
and evening peak periods using floating car technique. The data was analyzed using Statistical Packages for
Social Sciences (SPSS) and fitted into Multiple Regression model to establish a relationship between the
Travel Time and other road traffic parameters. Travel time (Tt) was modeled as a function of section length
(X1), number of intersections (X2), pedestrian/ economic activities (X3), Traffic volume (X4), enforcement
agency (X5) and road width (X6). The Coefficient of multiple determination R2 was 0.702 which means that
there is 70.2% of the dependent variable (travel time) in the forward direction as explained (accounted) by the
independent variables and 72.2% in the opposite direction. The result revealed that section length, pedestrian
economic activity and traffic volume were all significant at 5% level and has a positive relationship with travel
time in both forward and reverse direction. The model identifies the impact of these traffic parameters on travel
time and recommend measures for improvement.
Comprehensive Analysis of Built Environment Characteristics on Household.pdfChetanDoddamani8
This document discusses how mixing land uses in suburban developments can improve mobility and reduce traffic congestion. Specifically, it argues that land-use mixing:
1) Reduces motorized travel by internalizing trips within developments and encouraging walking between nearby uses.
2) Spreads trips out more evenly throughout the day rather than concentrating them during peak hours like single-use developments do.
3) Encourages more ridesharing by providing services and amenities within developments so workers don't need to drive to run errands.
4) Allows for shared parking arrangements which reduces the amount of parking needed.
This document summarizes a study on cellular phone users in the San Francisco Bay Area. A survey was conducted of 35,000 GTE Mobilnet customers to assess the impact of cellular communication on driver behavior and travel patterns. Key findings include:
1) The primary transportation effect of cellular phones is on trip scheduling and frequency, with over 60% of respondents reporting it affected their travel.
2) Only 15% of respondents obtained traffic information when expecting congestion, due to the lack of real-time traffic info in the Bay Area.
3) Cellular phones likely alter trip patterns as people adapt activities, but may not significantly affect total trip generation on their own. Route guidance could have a greater impact
The Driving Factors Behind Successful Carpool Formation and UseSmart Commute
This document summarizes a study examining factors that influence successful carpool formation and use through an online carpooling service called Carpool Zone. The study aims to understand individual and spatial factors that affect carpooling by analyzing user data from Carpool Zone. Previous literature found that costs, scheduling, and access to potential matches are important influences on carpooling. The study will analyze user characteristics, vehicle access, attitudes, and match accessibility to understand carpooling behavior. Insights from the study could help improve carpooling programs and policies.
This document discusses technologies that can encourage greater public transportation use. It summarizes that location-tracking mobile apps increase passengers' confidence by providing real-time transit information. On-demand transportation services can increase route efficiency. Smart cards and contactless payments alleviate issues with cash and provide user data to help transit agencies. Future technologies like bike sharing, driverless vehicles, and personal rapid transit could further transform public transportation.
Drivers’ and passengers’ perspectives on factors influencingAlexander Decker
The document discusses factors that influence intercity bus travel time on the route between Accra and Takoradi in Ghana based on interviews with drivers and passengers. Key factors identified include the number of passengers on board which determines the number of stops, purpose of travel which influences a passenger's sensitivity to time, traffic volume which impacts speed, and speed limits which prevent drivers from traveling faster. Misunderstandings between drivers and passengers about expected travel time can cause tension.
This document discusses an online budget path planning mobile application. It aims to analyze budget approaches for tours by determining travel costs in real-time using personalized traveler information from smartphones. The application would help travelers understand costs for different transportation options like trains and flights. It collects data from multiple sources to compare to exhaustive search methods while maintaining service quality. Emergency helpline numbers are also provided for different places in India.
Pay-As-You-Drive is a variable pricing model for auto insurance, where the more you drive the more you pay - the topic of my "Middle Year" thesis. Here the interview report, which was an exercise in writing according to a designated format and tone.
Large cities in developing countries are characterized by growth in automobile ownership, insufficient
transportation infrastructure and service development. These cities often suffer from congestion, poor mobility
and accessibility, significant economic waste, adverse environmental impact and safety problems. This paper
focuses on identification of travel time characteristics and other traffic parameters and to develop a predictive
model for travel time on Akure major roads. Data on travel time were collected for vehicles during the morning
and evening peak periods using floating car technique. The data was analyzed using Statistical Packages for
Social Sciences (SPSS) and fitted into Multiple Regression model to establish a relationship between the
Travel Time and other road traffic parameters. Travel time (Tt) was modeled as a function of section length
(X1), number of intersections (X2), pedestrian/ economic activities (X3), Traffic volume (X4), enforcement
agency (X5) and road width (X6). The Coefficient of multiple determination R2 was 0.702 which means that
there is 70.2% of the dependent variable (travel time) in the forward direction as explained (accounted) by the
independent variables and 72.2% in the opposite direction. The result revealed that section length, pedestrian
economic activity and traffic volume were all significant at 5% level and has a positive relationship with travel
time in both forward and reverse direction. The model identifies the impact of these traffic parameters on travel
time and recommend measures for improvement.
Comprehensive Analysis of Built Environment Characteristics on Household.pdfChetanDoddamani8
This document discusses how mixing land uses in suburban developments can improve mobility and reduce traffic congestion. Specifically, it argues that land-use mixing:
1) Reduces motorized travel by internalizing trips within developments and encouraging walking between nearby uses.
2) Spreads trips out more evenly throughout the day rather than concentrating them during peak hours like single-use developments do.
3) Encourages more ridesharing by providing services and amenities within developments so workers don't need to drive to run errands.
4) Allows for shared parking arrangements which reduces the amount of parking needed.
Identification of Factors to Improve Public Transit Services (A Case Study of...Dr. Amarjeet Singh
This research presents studies on a segment of highway to determine the quantitative factors that inuence transit services. Travel time and delay study is one of the method to determine quantitative factors. Tour time is described as the average period of time required to journey from one region to some other. Total departure time consists of gadgets which include total working time, places and general delay time. The examine section was done in Prithvi chowk to Tal chowk of Prithvi Highway which is turned to be 12.5 km long.
Additionally, it has been found that the principle variables affecting travel time are: postpone time because of forestall selecting and choosing up passengers, bus model and bus size.32 trips public transport carrier and a 10 trips non-public automobile journey have been held during peak hours. Models are developed the use of SPSS software to become aware of the relationship between the causes of delays and the overall-time delays. Travel time and learning delays can help reduce the number of private vehicles operating and increase the number of public vehicles in order to reduce congestion and improve the e efficiency of the public transport system. It turned into determined that there was a full-size distinction in tour time among the use of the public transit services and the car.
This document summarizes research on the inaccuracies in transportation planning models' traffic forecasts that are used for major capital infrastructure decisions. It finds that forecasts are often inaccurate, with actual traffic volumes being significantly different than what was predicted.
It then examines factors that can contribute to these forecasting inaccuracies, such as uncertainties in inputs, model specification errors, and models not adequately accounting for things like induced demand and land use impacts.
The document presents a case study analyzing changes in land use and traffic patterns near the Attiki Odos motorway in Athens, Greece, finding that the new infrastructure project led to greater development and additional generated traffic beyond what was originally forecasted.
Module 9_Impacts of ICT on Mobility. - Copy.pptxJeniBasanes
The document discusses how information and communication technologies (ICT) have impacted and will continue to impact the transportation sector in three key ways:
1) ICT enables the substitution of physical transportation and mobility for virtual/information flows.
2) ICT promotes new forms of mobility and allows mobility to be substituted through technologies like teleconferencing. This is expected to reduce vehicle use.
3) ICT provides real-time navigation, traffic, and location information that improves transportation efficiency through better routing, estimated times of arrival, and fuel consumption.
This document summarizes a study that compared 50 trips taken using UberPool and Chicago public transit (CTA). Key findings:
- On average, UberPool trips took 35 minutes and 52 seconds compared to 48 minutes and 29 seconds for CTA trips. UberPool was faster for 78% of trips.
- CTA performed best for downtown trips, with an average time only 6 minutes more than UberPool. However, UberPool was often still faster, even with extra stops.
- UberPool dominated for neighborhood-neighborhood trips, being faster than CTA on 21 of 23 trips and significantly faster (over 10 minutes) on 19 trips.
- Factors like comfort, predictability and surge pricing affect choice between
The Urban Information Lab at the University of Texas at Austin will conduct a 3-phase study to evaluate the university's bicycle infrastructure and policies. Phase 1 will inventory existing bike lanes, racks, and other infrastructure. Phase 2 will collect data from smartphone apps on biking routes, issues, and preferences. Phase 3 will analyze the findings to identify specific improvements like expanding bike lanes and facilities to increase biking and support sustainability goals. The goal is to provide a detailed plan to convert car drivers to bike commuters and better support biking on campus.
The document discusses measures that can be taken to influence a modal shift from private cars to public transport in order to reduce traffic congestion in a city. It recommends conducting a stated preference survey to understand factors that influence travel choices. It also suggests implementing policies to dissuade car use such as prioritizing public transit at traffic signals, improving reliability and travel times of public transport, and providing more real-time transit information for passengers. Safety improvements for pedestrians are also highlighted.
This document summarizes a meta-analysis of over 200 studies on the relationship between the built environment and travel behavior. The analysis found that while travel variables are generally insensitive to changes in the built environment, certain environmental factors can significantly influence travel. Vehicle miles traveled is most strongly related to accessibility and street network design, while walking is most strongly linked to land use diversity, intersection density, and nearby destinations. Bus and train use correlate most with proximity to transit and street networks. Population and job density have weaker associations once other variables are controlled for. However, the results should be interpreted cautiously due to small sample sizes and limited controls for residential preferences in the studies.
travel and the built environment- a meta-analysis (2).pdfChetanDoddamani8
This document summarizes a meta-analysis of over 200 studies examining the relationship between the built environment and travel behavior. The study aims to quantify the effects of variables like density, land use diversity, and design on travel outcomes including vehicle miles traveled, walking, and transit use. It finds that travel is generally inelastic to changes in the built environment, with elasticities below 0.39 for most relationships. Vehicle miles traveled is most strongly associated with accessibility and street design, while walking correlates most with land use diversity, intersections and nearby destinations. The study concludes that its elasticities can help adjust travel models to account for built environment impacts, but more research is still needed to address self-selection biases.
Sustainable Last mile delivery- challenges & opportunities.pdfHamid Saeedi
Due to urbanization trends, and megacities, the main part of the last mile happens in urban areas. The cost of providing last-mile services accounts for around 40% of overall supply chain costs. This is more than double compared to any other operations, such as parceling or warehousing in a supply chain. It’s a challenge not just in terms of costs, but also in terms of environmental impact. Transportation in the last mile is accountable for around 25% of GHG emissions in urban areas, and it is expected a 32% jump in carbon emissions from urban delivery by 2030. Last-mile delivery is the most inefficient part of the supply chain, because of small order sizes, lack of consolidation, network conditions, short lead times, and many constantly changing and geographically dispersed locations.
Online Bus Arrival Time Prediction Using Hybrid Neural Network and Kalman fil...IJMER
This document presents a hybrid method for predicting bus arrival times using neural networks and Kalman filters. The proposed method combines a neural network trained on historical bus location and travel time data to make initial predictions, and then uses a Kalman filter to continuously update the predictions based on real-time GPS measurements from buses. The neural network model uses seven input nodes and a double hidden layer structure. The Kalman filter equations are used to fuse the neural network predictions with current GPS observations to improve prediction accuracy over time. A case study on a real bus route in Egypt showed the hybrid method achieved satisfactory prediction accuracy.
- The document discusses how increasing numbers of tolled roads in a network like Sydney could lead to "toll saturation", where commuters reach a limit on how much they are willing to pay in tolls.
- It presents models to test the hypothesis that as toll costs accumulate across multiple roads, the value that commuters place on travel time savings (VTTS) will decrease due to this toll budget constraint.
- The study uses data from Sydney, which has 9 existing tolled roads and 5 more planned, to estimate models that incorporate a toll saturation effect and examine how it impacts VTTS for commuters.
Mapping a hospital using OpenStreetMap and Graphhopper: A navigation systemjournalBEEI
The document describes a mobile navigation system called HKLNS that was developed to help visitors navigate the large and complex Hospital Kuala Lumpur (HKL) campus more easily. OpenStreetMap and Graphhopper API were used to map HKL and determine the shortest pedestrian routes between locations. A survey found that most visitors had difficulty navigating HKL and locating departments. The system addresses this by allowing users to see their current location, view locations of departments, and receive navigation to destinations in the shortest time. Testing showed the system reduced navigation time by over 50% and was effective at helping users navigate HKL.
DESIGN OF PUBLIC TRANSPORTATION IN BARAMULLA CITY OF JAMMU AND KASHMIR”.IRJET Journal
This document summarizes a study on designing public transportation in Baramulla City, Jammu and Kashmir, India. The study analyzed the existing public transportation system and identified issues like limited availability and long travel times. Surveys were conducted to understand transportation usage and needs. It was found that most people rely on private vehicles rather than public transportation. To promote greater public transportation use, the study developed timetables for bus and taxi services on key routes. The timetables aim to provide more frequent, reliable public transportation options to address current issues and encourage more people to shift from private to public transportation.
This document discusses measurement of travel time variability using floating car data. It defines key terms like mean travel time, standard deviation, 95th percentile travel time, buffer index, and planning time index. These statistical measures are used to analyze travel time variability in three case studies on selected highways. The buffer index and planning time index are identified as the most effective reliability measures for communicating with the public.
The document summarizes a research project using big data to help avoid weather-related flight delays. It discusses how researchers gathered over 10 years of hourly weather and flight data and are using advanced analytics to identify patterns that could help airlines better manage delays. The goal is to allow airlines to anticipate delays before they happen by predicting how weather in one location may impact flights elsewhere. This could help airlines proactively adjust schedules and resources to minimize disruptions. The researchers believe this analysis of massive data sets could significantly improve the travel experience for passengers and airlines.
Telecommuting will become the predominant way that people access work over traditional means within the next 10 years. Advances in technology, especially high-speed internet, have increased telecommuting opportunities significantly. Telecommuting provides environmental, economic, and quality of life benefits like reduced energy usage and traffic as well as increased productivity and job satisfaction. As these advantages address issues like cost reduction, work-life balance, and environmental sustainability, telecommuting will become the new standard for how most jobs are performed.
This document summarizes a study that analyzed the built environment of two ferry terminals in Mokpo, South Korea in terms of passenger walkability and satisfaction. The researchers conducted an audit survey to measure the built environment features, then used importance-performance analysis to identify poorly walkable sections. They found passengers' satisfaction with the walking path environment varied by age and residence. In particular, there were significant differences in satisfaction between groups when embarking and disembarking the ferry. The study aims to help improve ferry terminal design for passenger convenience and walking experience.
Submitted Publication in the Transportation Research Record
November 23, 2015
ABSTRACT
A pilot program in Austin, Texas, tested the practicality of integrating a real-time ridesharing application with a toll operator to process toll discounts for carpools. The toll discounts appeared on monthly toll transaction statements. The program lasted for almost a year on the 183A Toll Road and the US 290 Manor Expressway. Travelers used a smartphone application to track, record, and submit their trips for discounts. Two-person carpools that used the application received a 50 percent discount, and carpools of three or more people could travel toll-free. The program was a partnership between the Central Texas Regional Mobility Authority, the local toll systems operator, and a private ridesharing vendor. Back-office processes matched trip data from the smartphone application to transactions recorded by the toll systems. A total of 95 unique drivers were provided toll rebates for 2,213 trips during the 10.5-month pilot period. Most trips during the pilot program were rebated for two-person carpools. Individual driver behavior varied considerably. A select few drivers had a high number of carpool trips, while others took a sporadic or infrequent trip. Drivers took a median of 7 trips during the pilot. Future rideshare programs should consider showing higher-dollar rebates that represent annual savings to incentivize behavior. Timely feedback was found to be an important factor for success. Additionally, program sponsors should provide positive customer service and engage users when problems exist that are not under their direct purview.
This document provides strategies for helping 9th grade math students effectively manage their time. It recommends incorporating daily review activities at the start of class to minimize wasted time. Students should be taught self-monitoring skills to stay on-task during independent work periods. Establishing routines and providing a syllabus can help students prioritize assignments. Frequent praise and rewards can also encourage students to meet deadlines. Overall, these time management strategies are aimed at enhancing learning for 14-year-old students.
The document discusses the primary steps and process for requesting and obtaining writing assistance through the HelpWriting.net website. It outlines 5 main steps: 1) Creating an account with valid email and password. 2) Completing a 10-minute order form providing instructions, sources, and deadline. 3) Reviewing bids from writers and choosing one based on qualifications. 4) Receiving the paper and authorizing payment if pleased. 5) Having the option to request revisions to ensure satisfaction, with a refund offered for plagiarized work. The document promotes the website's writing assistance services.
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Ähnlich wie An Evaluation Of Telecommuting As A Trip Reduction Measure
Identification of Factors to Improve Public Transit Services (A Case Study of...Dr. Amarjeet Singh
This research presents studies on a segment of highway to determine the quantitative factors that inuence transit services. Travel time and delay study is one of the method to determine quantitative factors. Tour time is described as the average period of time required to journey from one region to some other. Total departure time consists of gadgets which include total working time, places and general delay time. The examine section was done in Prithvi chowk to Tal chowk of Prithvi Highway which is turned to be 12.5 km long.
Additionally, it has been found that the principle variables affecting travel time are: postpone time because of forestall selecting and choosing up passengers, bus model and bus size.32 trips public transport carrier and a 10 trips non-public automobile journey have been held during peak hours. Models are developed the use of SPSS software to become aware of the relationship between the causes of delays and the overall-time delays. Travel time and learning delays can help reduce the number of private vehicles operating and increase the number of public vehicles in order to reduce congestion and improve the e efficiency of the public transport system. It turned into determined that there was a full-size distinction in tour time among the use of the public transit services and the car.
This document summarizes research on the inaccuracies in transportation planning models' traffic forecasts that are used for major capital infrastructure decisions. It finds that forecasts are often inaccurate, with actual traffic volumes being significantly different than what was predicted.
It then examines factors that can contribute to these forecasting inaccuracies, such as uncertainties in inputs, model specification errors, and models not adequately accounting for things like induced demand and land use impacts.
The document presents a case study analyzing changes in land use and traffic patterns near the Attiki Odos motorway in Athens, Greece, finding that the new infrastructure project led to greater development and additional generated traffic beyond what was originally forecasted.
Module 9_Impacts of ICT on Mobility. - Copy.pptxJeniBasanes
The document discusses how information and communication technologies (ICT) have impacted and will continue to impact the transportation sector in three key ways:
1) ICT enables the substitution of physical transportation and mobility for virtual/information flows.
2) ICT promotes new forms of mobility and allows mobility to be substituted through technologies like teleconferencing. This is expected to reduce vehicle use.
3) ICT provides real-time navigation, traffic, and location information that improves transportation efficiency through better routing, estimated times of arrival, and fuel consumption.
This document summarizes a study that compared 50 trips taken using UberPool and Chicago public transit (CTA). Key findings:
- On average, UberPool trips took 35 minutes and 52 seconds compared to 48 minutes and 29 seconds for CTA trips. UberPool was faster for 78% of trips.
- CTA performed best for downtown trips, with an average time only 6 minutes more than UberPool. However, UberPool was often still faster, even with extra stops.
- UberPool dominated for neighborhood-neighborhood trips, being faster than CTA on 21 of 23 trips and significantly faster (over 10 minutes) on 19 trips.
- Factors like comfort, predictability and surge pricing affect choice between
The Urban Information Lab at the University of Texas at Austin will conduct a 3-phase study to evaluate the university's bicycle infrastructure and policies. Phase 1 will inventory existing bike lanes, racks, and other infrastructure. Phase 2 will collect data from smartphone apps on biking routes, issues, and preferences. Phase 3 will analyze the findings to identify specific improvements like expanding bike lanes and facilities to increase biking and support sustainability goals. The goal is to provide a detailed plan to convert car drivers to bike commuters and better support biking on campus.
The document discusses measures that can be taken to influence a modal shift from private cars to public transport in order to reduce traffic congestion in a city. It recommends conducting a stated preference survey to understand factors that influence travel choices. It also suggests implementing policies to dissuade car use such as prioritizing public transit at traffic signals, improving reliability and travel times of public transport, and providing more real-time transit information for passengers. Safety improvements for pedestrians are also highlighted.
This document summarizes a meta-analysis of over 200 studies on the relationship between the built environment and travel behavior. The analysis found that while travel variables are generally insensitive to changes in the built environment, certain environmental factors can significantly influence travel. Vehicle miles traveled is most strongly related to accessibility and street network design, while walking is most strongly linked to land use diversity, intersection density, and nearby destinations. Bus and train use correlate most with proximity to transit and street networks. Population and job density have weaker associations once other variables are controlled for. However, the results should be interpreted cautiously due to small sample sizes and limited controls for residential preferences in the studies.
travel and the built environment- a meta-analysis (2).pdfChetanDoddamani8
This document summarizes a meta-analysis of over 200 studies examining the relationship between the built environment and travel behavior. The study aims to quantify the effects of variables like density, land use diversity, and design on travel outcomes including vehicle miles traveled, walking, and transit use. It finds that travel is generally inelastic to changes in the built environment, with elasticities below 0.39 for most relationships. Vehicle miles traveled is most strongly associated with accessibility and street design, while walking correlates most with land use diversity, intersections and nearby destinations. The study concludes that its elasticities can help adjust travel models to account for built environment impacts, but more research is still needed to address self-selection biases.
Sustainable Last mile delivery- challenges & opportunities.pdfHamid Saeedi
Due to urbanization trends, and megacities, the main part of the last mile happens in urban areas. The cost of providing last-mile services accounts for around 40% of overall supply chain costs. This is more than double compared to any other operations, such as parceling or warehousing in a supply chain. It’s a challenge not just in terms of costs, but also in terms of environmental impact. Transportation in the last mile is accountable for around 25% of GHG emissions in urban areas, and it is expected a 32% jump in carbon emissions from urban delivery by 2030. Last-mile delivery is the most inefficient part of the supply chain, because of small order sizes, lack of consolidation, network conditions, short lead times, and many constantly changing and geographically dispersed locations.
Online Bus Arrival Time Prediction Using Hybrid Neural Network and Kalman fil...IJMER
This document presents a hybrid method for predicting bus arrival times using neural networks and Kalman filters. The proposed method combines a neural network trained on historical bus location and travel time data to make initial predictions, and then uses a Kalman filter to continuously update the predictions based on real-time GPS measurements from buses. The neural network model uses seven input nodes and a double hidden layer structure. The Kalman filter equations are used to fuse the neural network predictions with current GPS observations to improve prediction accuracy over time. A case study on a real bus route in Egypt showed the hybrid method achieved satisfactory prediction accuracy.
- The document discusses how increasing numbers of tolled roads in a network like Sydney could lead to "toll saturation", where commuters reach a limit on how much they are willing to pay in tolls.
- It presents models to test the hypothesis that as toll costs accumulate across multiple roads, the value that commuters place on travel time savings (VTTS) will decrease due to this toll budget constraint.
- The study uses data from Sydney, which has 9 existing tolled roads and 5 more planned, to estimate models that incorporate a toll saturation effect and examine how it impacts VTTS for commuters.
Mapping a hospital using OpenStreetMap and Graphhopper: A navigation systemjournalBEEI
The document describes a mobile navigation system called HKLNS that was developed to help visitors navigate the large and complex Hospital Kuala Lumpur (HKL) campus more easily. OpenStreetMap and Graphhopper API were used to map HKL and determine the shortest pedestrian routes between locations. A survey found that most visitors had difficulty navigating HKL and locating departments. The system addresses this by allowing users to see their current location, view locations of departments, and receive navigation to destinations in the shortest time. Testing showed the system reduced navigation time by over 50% and was effective at helping users navigate HKL.
DESIGN OF PUBLIC TRANSPORTATION IN BARAMULLA CITY OF JAMMU AND KASHMIR”.IRJET Journal
This document summarizes a study on designing public transportation in Baramulla City, Jammu and Kashmir, India. The study analyzed the existing public transportation system and identified issues like limited availability and long travel times. Surveys were conducted to understand transportation usage and needs. It was found that most people rely on private vehicles rather than public transportation. To promote greater public transportation use, the study developed timetables for bus and taxi services on key routes. The timetables aim to provide more frequent, reliable public transportation options to address current issues and encourage more people to shift from private to public transportation.
This document discusses measurement of travel time variability using floating car data. It defines key terms like mean travel time, standard deviation, 95th percentile travel time, buffer index, and planning time index. These statistical measures are used to analyze travel time variability in three case studies on selected highways. The buffer index and planning time index are identified as the most effective reliability measures for communicating with the public.
The document summarizes a research project using big data to help avoid weather-related flight delays. It discusses how researchers gathered over 10 years of hourly weather and flight data and are using advanced analytics to identify patterns that could help airlines better manage delays. The goal is to allow airlines to anticipate delays before they happen by predicting how weather in one location may impact flights elsewhere. This could help airlines proactively adjust schedules and resources to minimize disruptions. The researchers believe this analysis of massive data sets could significantly improve the travel experience for passengers and airlines.
Telecommuting will become the predominant way that people access work over traditional means within the next 10 years. Advances in technology, especially high-speed internet, have increased telecommuting opportunities significantly. Telecommuting provides environmental, economic, and quality of life benefits like reduced energy usage and traffic as well as increased productivity and job satisfaction. As these advantages address issues like cost reduction, work-life balance, and environmental sustainability, telecommuting will become the new standard for how most jobs are performed.
This document summarizes a study that analyzed the built environment of two ferry terminals in Mokpo, South Korea in terms of passenger walkability and satisfaction. The researchers conducted an audit survey to measure the built environment features, then used importance-performance analysis to identify poorly walkable sections. They found passengers' satisfaction with the walking path environment varied by age and residence. In particular, there were significant differences in satisfaction between groups when embarking and disembarking the ferry. The study aims to help improve ferry terminal design for passenger convenience and walking experience.
Submitted Publication in the Transportation Research Record
November 23, 2015
ABSTRACT
A pilot program in Austin, Texas, tested the practicality of integrating a real-time ridesharing application with a toll operator to process toll discounts for carpools. The toll discounts appeared on monthly toll transaction statements. The program lasted for almost a year on the 183A Toll Road and the US 290 Manor Expressway. Travelers used a smartphone application to track, record, and submit their trips for discounts. Two-person carpools that used the application received a 50 percent discount, and carpools of three or more people could travel toll-free. The program was a partnership between the Central Texas Regional Mobility Authority, the local toll systems operator, and a private ridesharing vendor. Back-office processes matched trip data from the smartphone application to transactions recorded by the toll systems. A total of 95 unique drivers were provided toll rebates for 2,213 trips during the 10.5-month pilot period. Most trips during the pilot program were rebated for two-person carpools. Individual driver behavior varied considerably. A select few drivers had a high number of carpool trips, while others took a sporadic or infrequent trip. Drivers took a median of 7 trips during the pilot. Future rideshare programs should consider showing higher-dollar rebates that represent annual savings to incentivize behavior. Timely feedback was found to be an important factor for success. Additionally, program sponsors should provide positive customer service and engage users when problems exist that are not under their direct purview.
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This document provides strategies for helping 9th grade math students effectively manage their time. It recommends incorporating daily review activities at the start of class to minimize wasted time. Students should be taught self-monitoring skills to stay on-task during independent work periods. Establishing routines and providing a syllabus can help students prioritize assignments. Frequent praise and rewards can also encourage students to meet deadlines. Overall, these time management strategies are aimed at enhancing learning for 14-year-old students.
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Chapter wise All Notes of First year Basic Civil Engineering.pptxDenish Jangid
Chapter wise All Notes of First year Basic Civil Engineering
Syllabus
Chapter-1
Introduction to objective, scope and outcome the subject
Chapter 2
Introduction: Scope and Specialization of Civil Engineering, Role of civil Engineer in Society, Impact of infrastructural development on economy of country.
Chapter 3
Surveying: Object Principles & Types of Surveying; Site Plans, Plans & Maps; Scales & Unit of different Measurements.
Linear Measurements: Instruments used. Linear Measurement by Tape, Ranging out Survey Lines and overcoming Obstructions; Measurements on sloping ground; Tape corrections, conventional symbols. Angular Measurements: Instruments used; Introduction to Compass Surveying, Bearings and Longitude & Latitude of a Line, Introduction to total station.
Levelling: Instrument used Object of levelling, Methods of levelling in brief, and Contour maps.
Chapter 4
Buildings: Selection of site for Buildings, Layout of Building Plan, Types of buildings, Plinth area, carpet area, floor space index, Introduction to building byelaws, concept of sun light & ventilation. Components of Buildings & their functions, Basic concept of R.C.C., Introduction to types of foundation
Chapter 5
Transportation: Introduction to Transportation Engineering; Traffic and Road Safety: Types and Characteristics of Various Modes of Transportation; Various Road Traffic Signs, Causes of Accidents and Road Safety Measures.
Chapter 6
Environmental Engineering: Environmental Pollution, Environmental Acts and Regulations, Functional Concepts of Ecology, Basics of Species, Biodiversity, Ecosystem, Hydrological Cycle; Chemical Cycles: Carbon, Nitrogen & Phosphorus; Energy Flow in Ecosystems.
Water Pollution: Water Quality standards, Introduction to Treatment & Disposal of Waste Water. Reuse and Saving of Water, Rain Water Harvesting. Solid Waste Management: Classification of Solid Waste, Collection, Transportation and Disposal of Solid. Recycling of Solid Waste: Energy Recovery, Sanitary Landfill, On-Site Sanitation. Air & Noise Pollution: Primary and Secondary air pollutants, Harmful effects of Air Pollution, Control of Air Pollution. . Noise Pollution Harmful Effects of noise pollution, control of noise pollution, Global warming & Climate Change, Ozone depletion, Greenhouse effect
Text Books:
1. Palancharmy, Basic Civil Engineering, McGraw Hill publishers.
2. Satheesh Gopi, Basic Civil Engineering, Pearson Publishers.
3. Ketki Rangwala Dalal, Essentials of Civil Engineering, Charotar Publishing House.
4. BCP, Surveying volume 1
Reimagining Your Library Space: How to Increase the Vibes in Your Library No ...Diana Rendina
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Spark Good (walmart.com/sparkgood) is a charitable platform that enables nonprofits to receive donations directly from customers and associates.
Answers about how you can do more with Walmart!"
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
This document provides an overview of wound healing, its functions, stages, mechanisms, factors affecting it, and complications.
A wound is a break in the integrity of the skin or tissues, which may be associated with disruption of the structure and function.
Healing is the body’s response to injury in an attempt to restore normal structure and functions.
Healing can occur in two ways: Regeneration and Repair
There are 4 phases of wound healing: hemostasis, inflammation, proliferation, and remodeling. This document also describes the mechanism of wound healing. Factors that affect healing include infection, uncontrolled diabetes, poor nutrition, age, anemia, the presence of foreign bodies, etc.
Complications of wound healing like infection, hyperpigmentation of scar, contractures, and keloid formation.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
Leveraging Generative AI to Drive Nonprofit InnovationTechSoup
In this webinar, participants learned how to utilize Generative AI to streamline operations and elevate member engagement. Amazon Web Service experts provided a customer specific use cases and dived into low/no-code tools that are quick and easy to deploy through Amazon Web Service (AWS.)
An Evaluation Of Telecommuting As A Trip Reduction Measure
1. ¯ ~t.,g* ,v..
An Evaluation of Telecommuting
As a Trip Reduction Measure
.. .’.
Ryuichi Kitamura
Patricia L. Mokhtarian
RamM. PendYala
Institute of TransportationStudies and Department
of Civil Engineering
Universityof Californiaat Davis
KonstadinosG. Goulias
Pennsylvania
State University
WorkingPaper. No. 5
August 1991
The Umve~ity o~ C.alHo~ia
T~az~portai4oa Center
Uaiversltyof California TheUniversity of California Transportation Centei"
~erkeley,
CA
94720 University of California at Berkeley
2. The University of California
Transportation Center
TheUniversity of California
Transportation Center (UCTC)
is oneof ten regionalunits
mandatedby Congress and
established in Fall 1988to
supportresearch, education,
andtraining in surfacetrans-
portation. TheUCCenter
serves federal RegionIXand
is supported by matching
grants fromthe U.S. Depart-
mentof Transportation, the
California Department
of
Transportation(Caltrans), and
the University.
Basedon the Berkeley
Campus,UCTC
draws upon
existing capabilities and
resourcesof the Institutes of
TransportationStudies at
Berkeley,Davis,Irvine, and
LosAngeles;the Institute of
Urbanand Re,trial Develop-
mentat Berkeley;and several
academic
departmentsat the
Berkeley,Davis.Irvine, and
Los Angelescampuses.
Facultyandstudents onother
University of California
campuses
mayparticipate in
Centeractivities. Researchers
at otheruniversitieswithinthe
regionalso haveopportunities
to collaboratewithUC
faculty
onselectedstudies.
UCTC’s
educational and
research programsate focused
on strategic planningfor
improving metropolitan
accessibility, with emphasis
on the special conditionsin
RegionIX. Particular attention
is directedto strategiesfor
using transportation as an
instrument of economic
development,while also ac-
commodating
to the region’s
persistent expansionand
while maintaining and enhanc-
ingthe quality,of life there.
TheCenterdistributes reports
on its research in working
papers, monographs,and in
reprints of publishedarticles.
It also publishesAccess.a
magazinepresenting sum-
rnaries of selectedstudies. For
a list of publicationsin print,
write to the addressbelow.
University
of California
TransportationCenter
108Naval
Architecture
Building
Berkeley,
California94720
Tel: 510/643-7378
FAX:
510/643-5456
DISCLAIMER
lile contents
of this repod
reflect theviews
of theauthors,
wlio are
responsible
for the facts andtheaccuracy
of theinformation
presented
herein.Thisdocument
is disseminated
under
the sponsorship
of the
Department
of Transportation,
UniversityTransportation
Centers
Program,
in the interest of informationexchange.
TheU.S.Government
assumes
no
liability for thecontents
orusethereof.
The
contents
of this reportreflecttheviews
of theauthor
who
is responsible
forthe factsandaccuracy
of thedatapresented
herein.The
contents
donot
necessarily
reflecttheofficialviews
or policies
oftheStateof California
orthe
U.S.Department
of Transportation.
Thisreportdoesnotconstitute
a standard,
specification,
or regtflation.
- . - , ...... . . .
" .... . ...
3. AN EVALUATION OF TELECOMMUTING AS A TRIP REDUCTION MEASURE
Ryuichi Kitamura, Professor
Patricia L. Mokhtarian, Asst. Professor
Ram M. Pendyala, Ph.D. Student
Institute of Transportation Studies and
Department of Civil Engineering
University of California at Davis
Davis, CA 95616
and
Konstadinos G. Goulias, Asst. Professor
Pennsylvania State University, University Park, PA 16802
ABSTRACT
Telecommuting, which is the performance of work at home or
at a center close to home using telecommunications, has at-
tracted growing interest among planners and researchers as
a strategy for reducing traveldemand. This paper investi-
gates the potential of telecommuting as a trip reduction
measure, using data obtained from a telecommuting pilot pro-
ject involving State of California government employees.
In this pilot project, a three-day trip diary was adminis-
tered, before and after telecommuting began, to telecom-
muters, a control group, and driving-age household members
of both groups. A sample of 219 "stayers" is analyzed in
this paper.
Findings include: telecommuting leads to a substantial
reduction in trip generation, vehicle-miles traveled, peak
period travel, car use, and freeway travel. It does not
lead to an increase in non-work trips.
i. INTRODUCTION
The evaluation of the impact of telecommunications on travel
demand is a highly complex task. In the past, a variety of
hypotheses have been advanced on this issue. An issue of
particular importance is whether telecommunications tech-
nologies act as substitutes for travel or whether a comple-
mentary relationship exists between telecommunications and
travel (e.g., Salomon, 1986; Mokhtarian, 1988; Nilles,
1988). Little empirical evidence appears to exist at pre-
sent on the interaction between the two (Salomon, 1988).
The use of telecommunications to substitute for the commute
to work has recently drawn extensive attention as a strategy
for reducing travel demand. This came to be known as
telecommuting, broadly defined as "the performance of work
outside the traditional central office, either at home or at
a neighborhood center close to home" (Kitamura, et al.,
1990).
The potential of telecommuting as a means to mitigate urban
traffic congestion, reduce transportation energy consump-
tion, and improve air quality has motivated this study. The
4. ~va~uatioD of Telecommutinq Kitamura, et al. -- 2
objective of the study is to empirically measure the impact
of telecommuting on household travel in conjunction with
the State of California Telecommuting Pilot Project. The
Pilot Project has offered the first opportunity to gather
non-proprietary data on household travel behavior to assess
the impact of telecommuting. Other potential benefits of
telecommuting (e~g., reduced office space requirements,
increased worker productivity) have been examined by JALA
Associates (1990), the principal contractor of the Pilot
Project, and are not discussed in this paper.
Many hypotheses can be formulated on the impact of tele-
commuting on household travel (for related discussions, see
Jovanis, 1983; and Salomon, 1986). It is convenient to
classify these hypotheses according to the time frame into
short-term and long-termhypotheses. The most direct short
term hypothesis is that the number of trips generated by
telecommuters will decrease due to the reduction in commute
trips to and from work. Because work trips are most often
made during the peak period, a decrease in peak-hour trips
will follow as a direct consequence.
Furthermore, the eliminated need to travel to work would
lead to savings in both time and monetary cost. This would
in turn result in an increased availability of discretionary
time, flexibility in activity scheduling, and some monetary
saving. One may then hypothesize that these changes prompt
new, discretionary trips such as social and shopping trips.
Indeed, if the assumption is true that a person budgets a
fixed amount of time for travel, then those commute trips
eliminated by telecommuting may be replaced by new trips.
Also, other destinations, timing and modes could be chosen
for the existing non-work trips to reach more desirable
destinations, or to travel at more convenient times, while
using up the time saved.
Another consideration is that the absence of commute trips
by itself may lead to changes in the location and timing of
certain out-of-home activities, hence the destination and
timing of trips. For example, grocery shopping which used
to be done on the way home from work at a shopping center
along a commute route, may be performed at a grocery store
near the home in the late morning. One may surmise that the
spatial distribution of trip ends may be concentrated around
the home location rather than the work location when the
worker telecommutes. This redistribution of trips may af-
fect (suburban) congestion and air quality if telecommuting
is widely implemented.
An important consequence of telecommuting is the removal of
some of the work-related constraints -- a worker must report
to work by 8:00 a.m., a lunch break must be taken between 12
noon and i:00 p.m., and so on. Relaxation of these con-
straints is likely to reduce the need to link trips, i.e.,
consolidation of several stops into one home-to-home jour-
5. Evaluation of Telec0mmutinq Kitamura, et al. -- 3
ney. In fact, a recent analysis of trip linking behavior
under different conditions (Goulias, et al., 1990a) has
shown that people increase their linking of trips under
tighter constraints. If this in fact is the case, then
telecommuting may lead to an increased number of sporadic
home-based trips, leading to less efficient travel patterns
and more cold starts.
It is also conceivable that the flexibility andirregularity
in work schedule brought about by telecommuting may lead to
a change in mode use. For example, participating in a car,
pool may not be convenient for a telecommuter who does not
commute every day, therefore it may be more likely than
before that a personal car is used for commuting.
At the household level, the presence of a telecommuter at
home with a flexible work schedule may result in a realloca-
tion of tasks among the household members. This may stream-
line the travel patterns of the entire household, making
possible more efficient engagement in out-of-home activi-
ties. On the other hand, household members may choose to
use the car left at home by the telecommuter who would
otherwise use it to commute, possibly leading to increased
car trips.
Many changes are conceivable even within a short time frame.
Some changes will be beneficial while others may not be.
The timing of these changes is also uncertain. Telecom-
muters and their household members may go through a process
of experimentation and learning before they adopt a new rou-
tine that best takes advantage of telecommuting. Adaptation
to telecommuting thus involves a certain amount of £ime lag
whose length is not known.
Further impacts of telecommuting are conceivable in the long
term. The reduced need to commute may prompt a household
decision to own fewer cars. At the same time, telecommuting
reduces the need to reside close to the work site. Hence,
some telecommuters may choose to move further from work,
which could ultimately lead to increases in travel (Salomon,
1985). Testing such long-termhypotheses, however, is out-
side the scope of this study because the empirical data
available allow observation of changes over a period of only
one year.
However, many of the short-term hypotheses can be tested
against the empirical evidence generated bythe State Pilot
Project. These hypotheses guide the statistical analysis
presented in this report. An effort is made in this study
to assess the overall impact of telecommuting on household
travel utilizing the available data. In particular, atten-
tion is directed to a possible increase in trip generation
and car use as a result of telecommuting.
6. Evaluation of Telecom/nutinq Kitamura, et al. -- 4
This report is organized as follows. A description of the
State of California Telecommuting Pilot Project, the survey
sample and the data files comprises Section 2. Following
this, the results of the analysis pertaining to the impact
of telecommuting on travel characteristics are presented in
Section 3. Section 4 summarizes the research findings.
2. STATE OF CALIFORNIA TELECOMMUTE PILOT PROJECT
The State of California Telecommute Pilot Project provides
a unique opportunity to examine the impacts of telecommuting
on household travel. The main purpose of the project is to
assess the utility of telecommuting to the State Government.
It involves State employees who volunteered to participate.
Approximately half of the participants telecommuted, 1.5
days a week on average (from JALA Associates, 1990), while
the rest served as members of a control group against which
the impact of telecommuting is measured.
Factors that contributed to the implementation of the Pilot
Project include the increasing cost of acquiring new office
space and the changing nature of tasks performed in State
agencies. Increases in workload without an accompanying
expansion of the work force, worsening traffic congestion
and air quality, and the need to conserve energy are also
among the factors that motivated the project (JALA Associ-
ates, 1985).
Two three-day travel diary surveys, performed approximately
one year apart, serve as the primary information source for
this assessment of the impact of telecommuting on travel
patterns. The diary was used to collect information on the
trips made by the project participants and their household
members of driving age.
The first round of the survey (i.e., the Wave i survey) was
conducted from January through June, 1988, before the parti-
cipants commenced telecommuting. Therefore all the respon-
dents were commuting to work in the conventional way at the
time of the Wave 1 survey. In the second wave, conducted in
1989, telecommuting had begun. Thus the survey represents
a "before and after" study to analyze the effects of tele-
commuting. In addition, all participants were requested to
provide information on their household characteristics.
The second wave of the survey commenced in April 1989 and
ended in July 1989. The development of the Wave 2 survey
instruments and data development procedure are summarized in
a separate paper (Goulias, et al., 1990b). In the Wave
survey, the telecommuters were requested to fill out the
travel diary on three successive weekdays, of which at least
one day was a telecommuting day (a day during which work was
performed at home).
7. Evaluation of Telec0mmutinq Kitamura, et al. -- 5
As noted earlier, volunteer State employees also partici-
pated in the Pilot Project as members of a control group.
The intent of forming the control group was to measure
changes in travel patterns, energy use, and other measures
of effectiveness that are due to changes in economy, gaso-
line prices, and other such factors that influence all
individuals. The group would aid in separating the effect
of telecommuting from the effects of these factors in the
background. The control group members did not change their
usual work schedules between the two waves.
Description of the Survey Sample
The travel survey involved State employees from 14 agencies
and their household members of driving age. The partici-
pants live and work mostly in the Sacramento area. In
Wave i, information about the participants and their house-
hold members of driving age was available from 430 persons
out of the original group of 447 individuals. Of the 430
individuals, 252 were state employees, and 178 were their
driving-age household members. Of the 252 state employees,
137 (54.3%) were scheduled to telecommute in the second wave
and 115 (45.7%) were assigned to the control group.
Table 1 compares the number of respondents between the two
waves. The number of respondents is 257 persons in Wave 2.
The number of respondents who dropped out of the survey is
not negligible. Of the 252 employees and 178 household
members in Wave i, usable travel diaries are available from
138 employees and 81 household members (these respondents
will be referred to as "stayers" in this paper). It is
unknown to what degree this rather high rate of attrition
represents employees and their household members who: (i)
were no longer participating in the Pilot Project due to
outside factors such as retirement, promotion, reassignment,
relocation, or organizational change; (ii) chose (or were
asked by the manager) to stop telecommuting for internal
reasons -- i.e., reasons related to telecommuting itself
(family issues, lack of self-discipline, etc.); or (iii)
continued to teiecommute (or remain control members) but did
not return the Wave 2 survey.
In addition to the stayers, 38 new people submitted Wave 2
surveys that had not participated in Wave i.
TABLE i:
WAVES
COMPOSITION OF STUDY SAMPLE ACROSS THE TWO SURVEY
Group Wave 1 Wave 2 Stayers
TC Employees
CG Employees
TC Household Members
CG Household Members
137 79 73
115 75 ¯ 65
93 56 45
85 47 36
8. Evaluation of Telecommutinq Kitamura, et al. -- 6
Two types of data files were created to analyze the travel
characteristics of the project participants and their house-
hold members. One file contains personal and household in-
formation while the other contains trip information. The
person file provides information on the respondent’s project
participation status (telecommuter, control group member,
etc.), age, gender, employment, and relation to the State
employee. This file also contains the respondent’s home,
work, school, and other activity locations frequently vis-
ited by the respondents, transit lines frequently used and
household car ownership. This information has been geo-
coded for the analysis of spatial changes in urban travel
patterns.
The trip files contain characteristics of each trip made by
the respondent in each wave. The information includes trip
origin and destination, trip beginning and ending times,
trip purpose, approximate trip length in miles, mode used,
and, if a car were used, beginning and ending odometer
readings, the number of passengers, and the percentage of
the trip spent on the freeway. The Wave 1 trip file con-
tains 4808 trips reported by 430 persons in 269 households
while that from Wave 2 contains 2389 trips reported by 257
respondents in 159 households.
3. IMPACT OF TELECOMMJ~ING
The impact of telecommuting is statistically analyzed in
this section using the sample of 219 participants who res-
ponded to both Wave I and Wave 2 surveys. These respondents
consist of 73 telecommuter employees, 45 telecommuter house-
hold members, 65 control group employees and 36 control
household members. Wave 2 travel characteristics of the
telecommuters are further examined by day type (telecom-
muting or commuting day). On average, respondents telecom-
muted 1.3 days out of the three-day diary period.
The control group is used as a reference group in this
assessment. The changes exhibited by telecommuters are
evaluated relative to those shown by the control group
members. Two types of comparisons are made: First, the
travel characteristics are compared between the telecom-
muters and control group members within each wave, and
second, comparison is made across the two waves for each
group. For the first type of comparison, the pooled t-test
is appropriate as the two groups can be considered as in-
dependent samples of different sample sizes. For the sec-
ond comparison, the paired t-test is used as it allows for
possible correlation among repeated observations of the same
individuals (Snedecor and Cochran, 1989).
Daily Averaqe Trip Rates
Based on the daily average trip rates, the control group
employees display a higher level of mobility in both waves
9. Evaluation of Telecommutinq Kitamura, et al. -- 7
(Table 2). In Wave I, the control group employees made
average of 4.30 trips per day, compared to 3.99 trips made
by the telecommuters (this difference is not statistically
significant at a 5% level). In Wave 2, the control group
employees made 3.95 trips per person per day, while the
telecommuters made a much lower daily average of 1.94 trips
on telecommuting days. The difference, statistically sig-
nificant at a 5% level, is expected because the telecom-
muters made at least two trips less (trips to and from work)
than the control group on a telecommuting day.
On a commuting day in Wave 2, telecommuters averaged the
same number of trips as in Wave 1. On a telecommuting day,
the telecommuters make a significantly smaller number of
trips when compared with Wave I. The reduction in trip
making shown by telecommuter household members across the
two waves is also significant and noteworthy.
TABLE 2 : NUMBER OF TRIPS PER DAY
Group Wave 1 Wave 2-TC Wave 2-C
Telecommuter Employees 3.99 1.94* 4.00
Control Group Employees 4.30 n/a 3.95
Telecommuter Household 3.98 n/a 3.08*
Control Group Household 3.53 n/a 3.30
* significantly different from Wave 1 at a 5% level
Wave 2-TC: Telecommuting Day in Wave 2
Wave 2-C: Commuting Day in Wave 2
Trip Rates by Purpose
In Table 3, average daily trip rates are presented for each
wave by purpose and by project participation status. The
"other" trip purposes include return home, social-recre-
ation, visit friend/relative, personal business, shopping,
serve passengers, medical, eat meal, and change mode.
Telecommuters make virtually no work trips on telecommuting
days. On commuting days, they make the usual one work trip.
All other groups showed statistically stable work trip rates
across the two waves.
Contrary to what was hypothesized in the introduction, no
increase in "other" trips, which include discretionary non-
work trips, is observed for the telecommuters. Apparently,
decreased travel needs, increased availability of discre-
tionary time, and flexibility in work schedule brought about
by telecommuting, did not lead to an increase in non-work
trips.
In fact, between Wave 1 and Wave 2 a significant decline in
the number of "other" trips is observed for telecommuters on
telecommute days, and for telecommuter household members.
For the telecommuters, this decline is explained by the fact
that one fewer "return home" (i.e., returning home from
10. Evaluation of Telecommutinq Kitamura, et al. -- 8
work) or "work-to-elsewhere" trip will be made on telecom-
muting days. The finding for household members, though, is
unexpected. The indication is that telecommuting reduces
trip generation for the entire household. Before this re-
sult can be generalized, however, further examination of the
data and possibly a supplementary survey of household mem-
bers are needed to examine the mechanism underlying this
apparent reduction.
In any case, the result is encouraging because it indicates
that telecommuting effectively serves as a trip reduction
measure by eliminating some work trips without increasing
non-work trips, at least in the short term.
TABLE 3: NUMBER OF TRIPS PER DAY BY PURPOSE
Group Wave 1 Wave 2-TC Wave 2-C
Work Other Work Other Work Other
TC Employees 1.02 2.97 0.09* 1.85" i. Ii 2.89
CG Employees l.lO 3.20 n/a n/a 1.07 2.88
TC Household 0.74 3.24 n/a n/a 0.70 2.38*
CG Household 0.60 2.93 n/a n/a 0.77 2.53
* significantly different from Wave 1 at a 5% level
Wave 2-TC: Telecommuting Day in Wave 2
Wave 2-C: Commuting Day in Wave 2
Mode Use
Trip rates by car are summarized in Table 4. Car trips are
defined here as those made in personal vehicles or State
vehicles, and exclude carpooling or vanpooling. The
decrease in car trips by telecommuters on a telecommuting
day is noteworthy. This is a direct consequence of the
reduction of commute trips by the introduction of
telecommuting.
There is no indication that the availability of the car pre-
viously used by the telecommuters to commute, is inducing
more car trips by household members. The household members
of telecommuters have not increased car usage even though
additional family cars have become available for their use.
This may be because, in California and nationwide, there are
about 0.99 personal-use vehicles per driving-age person
(Lave, 1990). An idle vehicle will not be used by other
family members if they already have vehicles of their own.
There is, however, some indication that changes in mode
choice are greater among the telecommuters than the control
group employees. Table 4 also presents the percentage share
of car trips. The share of car trips among the control
group employees shows practically no change between the
waves. Among the telecommuter employees, the share in-
creased somewhat from 81% to 91%. Associated with this in-
crease is a chi-square statistic of 7.01, which, with one
11. Evaluation of Telecommutinq Kitamura, et al. -- 9
degree of freedom, indicates an increase significant at a 5%
level.
In this context, it is important to note that telecommuting
can induce a series of changes in transport related deci-
sions, including car ownership, residence location, and
other life-style related choices. These changes, which tend
to be observed only in the long run, could cause measurable
changes in travel patterns, including mode use. It is de-
sirable that the validity of the findings here, which are
based on short-term data, be examined using observations
obtained over a longer time span.
TABLE 4: CAR TRIPS PER DAY
Group Wave 1 Wave 2-TC Wave 2-C
TC Employees 3.25 (81) 1.77. (91) 3.25 (81)
CG Employees 3.17 (74) n/a 2.88 (73)
TC Household 3.53 (89) n/a 2.83*(92)
CG Household 2.72 (77) n/a 2.69 (81)
* significantly different from Wave 1 at a 5% level
( ): As a percentage of Total Trips per Day
Wave 2-TC: Telecommuting Day in Wave 2
Wave 2-C: Commuting Day in Wave 2
Peak Period Trip Generation
Telecommuting substantially reduced peak hour travel by the
telecommuters, whereas the control group did not show any
substantial reduction. Table 5 presents the number of de-
partures during the morning and afternoon peak periods. The
morning peak period is defined in this study as 7:00 to 8:59
a.m. and the afternoon peak period as 4:00 to 5:59 p.m.
TABLE 5: NUMBER OF PEAK PERIOD TRIPS PER DAY
Group Wave 1 Wave 2-TC Wave 2-C
AM PM AM PM AM PM
TC Employees 0.89 0.99 0.24* 0.46* 0.82 1.16
CG Employees 0.86 1.13 n/a n/a 0.98 1.15
TC Household 0.79 0.84 n/a n/a 0.64* 0.65*
CG Household 0.62 0.60 n/a n/a 0.50 0.83
* significantly different from Wave 1 at a 5% level
Wave 2-TC: Telecommuting Day in Wave 2
Wave 2-C: Commuting Day in Wave 2
The decrease in the number of peak-hour departures made by
the telecommuters on telecommuting days in Wave 2 is sig-
nificant for both morning and afternoon peak periods (at
5% level). They made 73% fewer morning-peak departures and
about 54% fewer afternoon-peak departures. The reduction in
peak-hour trips is significant for the telecommuter house-
hold members as well. A decrease in peak hour trip genera-
12. Evaluation of Telecommuting Kitamura, et al. -- i0
tion appears to b~ a direct consequence of the introduction
of telecommuting.
Total Distance Traveled
The estimated average distance traveled decreased signifi-
cantly in Wave 2 on telecommuting days. The average total
distance traveled per day for each group is presented in
Table 6. In Table 6, the average distance traveled is com-
puted from the trip lengths reported by the respondents.
The telecommuters reduced the total distance traveled by
about 40 miles per telecommuting day. This decrease is
found to be highly significant. On commuting days, the
telecommuters showed no increase in vehicle miles traveled
over Wave i. The control group employees showed relative
stability in their vehicle miles traveled per day. The
results thus clearly show that telecommuting leads to a
reduction in total travel distance.
TABLE 6: AVERAGE TOTAL DISTANCE TRAVELED PER DAY (MILES)
Group Wave 1 Wave 2-TC Wave 2-C
Telecommuter Employees 53.7
Control Group Employees 50.0
Telecommuter Household 36.4
Control Group Household 25.7
13.2" 56.1
n/a 45.1
n/a 33.1
n/a 23.8
* significantly different from Wave 1 at a 5% level
Wave 2-TC: Telecommuting Day in Wave 2
Wave 2-C: Commuting Day in Wave 2
TABLE 7 : FREEWAY PERCENTAGE PER TRIP
Group Wave 1 Wave 2-TC Wave 2-C
Telecommuter Employees 53
Control Group Employees 35
Telecommuter Household 31
Control Group Household 30
i0" 49
n/a 40
n/a 30
n/a 25
* significantly different from Wave 1 at a 5% level
Wave 2-TC: Telecommuting Day in Wave 2
Wave 2-C: Commuting Day in Wave 2
FrEeway Percentages
The percentage of the trip spent on the freeway is shown in
Table 7. The telecommuters are found to significantly re-
I
The reduction in morning peak period trip generation for telecom-
muter and control group household members may, in part, be due to seasonal
effects. While the entire Wave 1 survey occurred before closing of schools
(i.e., before June), a portion of the Wave 2 survey took place in June after
schools were closed. No school trips (which usually occur in peak periods)
were observed during this period.
13. Evaluation of Telec0mmutinq Kitamura, et al. -- ii
duce their freeway use on telecommuting days while showing
stable freeway use on commuting days. All other groups also
show relative stability in freeway use. The conjecture that
telecommuters are choosing different destinations which are
reachable by different routes is supported by this finding.
4. CONCLUSIONS
The impact of telecommuting on travel demand is examined in
this study, using three-day travel diary data obtained from
State employees participating in the State of California
Telecommute Pilot Project, and from their household members
of driving age. Travel data were collected twice, before
and after telecommuting started. The main body of the
analysis presented in this report is based on trip records
obtained from 219 respondents, of which 73 are telecom-
muters.
The results of the statistical analysis presented in this
report offer strong empirical evidence that telecommuting is
a viable trip reduction measure. The salient findings of
this study can be summarized as follows:
-- Telecommuting leads to a substantial reduction in trip
generation. The observed reduction of two trips per tele-
commuting day corresponds to the two commute trips elimin-
ated by telecommuting each day. Virtually no work trips
were generated by the telecommuters in the Pilot Project on
the days they telecommuted.
-- Telecommuting does not lead to an increase in non-work
trips. On the contrary, the evidence suggests that telecom-
muting leads not only telecommuters but also their household
members to be more efficient in traveling.
-- The total travel distance was reduced by 40 miles per
telecommuting day in the study sample. On a telecommuting
day, telecommuters traveled about 20% of the distance they
normally traveled on commute days.
-- Telecommuting reduces peak-period trips. On telecom-
muting days, morning-peak trips are reduced on the average
by 73%, and afternoon-peak trips by about 54%.
-- The household members of telecommuters do not increase
car use even when additional family cars have become avail-
able for their use.
-- Although the total number of car trips is lower, the
proportion of trips made by car tends to be slightly greater
among telecommuters. This is in part due to the reduced
number of work trips, where transit is more likely to be
used. Another contributing factor is the frequent use of
the car for non-work trips made on telecommuting days.
14. Evaluation of Telec0mmutinq Kitamura, et al. -- 12
-- Trips made on telecommuting days are much shorter and
involve less freeway travel. This presumably reflects
changes in the spatial distribution of trips as a result of
telecommuting.
ACKNOWLEDGEMENTS
This research was funded by the State of California
Department of Transportation, and by the University of
California Transportation Center.
REFERENCES
Goulias, K.G., R. Pendyala, and R. Kitamura (1990a) A practical method
for the estimation of trip generation and trip chaining. Transportation
Research Record 1285, 47-56.
Goulias, K.G., R. Pendyala, and R. Kitamura (1990b) Telecommuting and
Travel Demand: An Activity-Based Impact Assessment, Interim Report
No. 2, Panel Survey Questionnaire Updating. Research Report, Transporta-
tion Research Group, University of California, Davis, CA (Prepared for
the California State Department of Transportation).
Hogg, R.V. and E.A. Tanis (1988) Probability and Statistical Inference.
3rd edition, Macmillan Publishing Company, New York.
JALA Associates, Inc. (1985) Telecommuting: A Pilot Project Plan. The
Department of General Services, State of California, Sacramento, CA,
June.
JALA Associates, Inc. (1990) California Telecommuting Pilot Project
Final Report. Stock No. 7540-930-1400-0, State of California Department
of General Services, North Highlands, CA 95660, June.
Jovanis, P. (1983) Telecommunications and alternative work schedules:
Options for managing transit travel demand. Urban Affairs Quarterly,
19(2), 167-90.
Kitamura, R., J.M. Nilles, P. Conroy, and D.M. Fleming (1990) Telecom-
muting as a transportation planning measure: Initial results of Califor-
nia Pilot Project. Transportation Research Record 1285, 98-104.
Lave, C. (1990) Things won’t get a lot worse: The future of U.S. traf-
fic congestion. Working Paper UCI-ITS-WP-90-2, Institute of Transporta-
tion Studies, University of California, Irvine, CA 92717, February.
Mokhtarian, P.L. (1988) An empirical evaluation of the travel impacts
of teleconferencing. Transportation Research A, 22A(4), 283-89.
Nilles, J.M. (1988) Traffic reduction by telecommuting: A status review
and selected bibliography. Transportation Research A, 22A(4), 301-317.
Salomon, I. (1985) Telecommunications and travel: Substitution or Mod-
ified Mobility? Journal of Transport Economics and Policy, 219-235.
Salomon, I. (1986) Telecommunications and travel relationships:
review. Transportation Research A, 20A(3), 223-38.
A
Salomon, I. (1988) Transporting information and transporting people.
Transportation Research A, 22A(4), 237.
Snedecor, G.W., and W.G. Cochran (1989) Statistical Methods.
Edition, Iowa State University Press, Ames, Iowa.
7th