The Experts below are selected from a list of 45978 Experts worldwide ranked by ideXlab platform
Mustafa Lokhandwala - One of the best experts on this subject based on the ideXlab platform.
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dynamic ride sharing using traditional Taxis and shared autonomous Taxis a case study of nyc
Transportation Research Part C-emerging Technologies, 2018Co-Authors: Mustafa LokhandwalaAbstract:Abstract This study analyzes the potential benefits and drawbacks of taxi sharing using agent-based modeling. New York City (NYC) Taxis are examined as a case study to evaluate the advantages and disadvantages of ride sharing using both traditional Taxis (with shifts) and shared autonomous Taxis. Compared to existing studies analyzing ride sharing using NYC taxi data, our contributions are that (1) we proposed a model that incorporates individual heterogeneous preferences; (2) we compared traditional Taxis to autonomous Taxis; and (3) we examined the spatial change of service coverage due to ride sharing. Our results show that switching from traditional Taxis to shared autonomous Taxis can potentially reduce the fleet size by 59% while maintaining the service level and without significant increase in wait time for the riders. The benefit of ride sharing is significant with increased occupancy rate (from 1.2 to 3), decreased total travel distance (up to 55%), and reduced carbon emissions (up to 866 metric tonnes per day). Dynamic ride sharing, wich allows shared trips to be formed among many groups of riders, up to the taxi capacity, increases system flexibility. Constraining the sharing to be only between two groups limits the sharing participation to be at the 50–75% level. However, the reduced fleet from ride sharing and autonomous driving may cause Taxis to focus on areas of higher demands and lower the service levels in the suburban regions of the city.
Jie Yang - One of the best experts on this subject based on the ideXlab platform.
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Analyzing battery electric vehicle feasibility from taxi travel patterns: The case study of New York City, USA
Transportation Research Part C: Emerging Technologies, 2018Co-Authors: Liang Hu, Zhenhong Lin, Jing Dong, Jie YangAbstract:Electric Taxis have the potential to improve urban air quality and save driver's energy expenditure. Although battery electric vehicles (BEVs) have drawbacks such as the limited range and charging inconvenience, technological progress has been presenting promising potential for electric Taxis. Many cities around the world including New York City, USA are taking initiatives to replace gasoline Taxis with plug-in electric vehicles. This paper extracts ten variables from the trip data of the New York City yellow Taxis to represent their spatial-temporal travel patterns in terms of driver-shift, travel demand and dwell, and examines the implications of these driving patterns on the BEV taxi feasibility. The BEV feasibility of a taxi is quantified as the percentage of occupied trips that can be completed by BEVs of a given driving range during a year. It is found that the currently deployed 280 public charging stations in New York City are far from sufficient to support a large BEV taxi fleet. However, adding merely 372 new charging stations at various locations where Taxis frequently dwell can potentially make BEVs with 200- and 300-mile ranges feasible for more than half of the taxi fleet. The results also show that Taxis with certain characteristics are more suitable for switching to BEV-200 or BEV-300, such as fewer daily shifts, fewer drivers assigned to the taxi, shorter daily driving distance, fewer daily dwells but longer dwelling time, and higher likelihood to dwell at the borough of Manhattan.
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predicting market potential and environmental benefits of deploying electric Taxis in nanjing china
Transportation Research Part D-transport and Environment, 2016Co-Authors: Jie Yang, Jing Dong, Liang HuAbstract:This paper investigates the market potential and environmental benefits of replacing internal combustion engine (ICE) vehicles with battery electric vehicles (BEVs) in the taxi fleet in Nanjing, China. Vehicle trajectory data collected by onboard global positioning system (GPS) units are used to study the travel patterns of Taxis. The impacts of charger power, charging infrastructure coverage, and taxi apps on the feasibility of electric Taxis are quantified, considering taxi drivers’ recharging behavior and operating activities. It is found that (1) depending on the charger power and coverage, 19% (with AC Level 2 chargers and 20% charger network coverage) to 56% (with DC chargers and 100% charger network coverage) of the ICE vehicles can be replaced by electric Taxis without driving pattern changes; (2) by using taxi apps to find nearby passengers and charging stations, drivers could utilize the empty cruising time to charge the battery, which may increase the acceptance of BEVs by up to 82.6% compared to the scenario without taxi apps; and (3) tailpipe emissions in urban areas could be significantly reduced with taxi electrification: a mixed taxi fleet with 46% compressed-natural-gas-powered (CNG) and 54% electricity-powered vehicles can reduce the tailpipe emissions by 48% in comparison with the fleet of 100% CNG Taxis.
Liuhang Zhang - One of the best experts on this subject based on the ideXlab platform.
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T-Finder: A Recommender System for Finding Passengers and Vacant Taxis
IEEE Transactions on Knowledge and Data Engineering, 2013Co-Authors: Nicholas Jing Yuan, Yu Zheng, Liuhang ZhangAbstract:This paper presents a recommender system for both taxi drivers and people expecting to take a taxi, using the knowledge of 1) passengers' mobility patterns and 2) taxi drivers' picking-up/dropping-off behaviors learned from the GPS trajectories of taxicabs. First, this recommender system provides taxi drivers with some locations and the routes to these locations, toward which they are more likely to pick up passengers quickly (during the routes or in these locations) and maximize the profit of the next trip. Second, it recommends people with some locations (within a walking distance) where they can easily find vacant Taxis. In our method, we learn the above-mentioned knowledge (represented by probabilities) from GPS trajectories of Taxis. Then, we feed the knowledge into a probabilistic model that estimates the profit of the candidate locations for a particular driver based on where and when the driver requests the recommendation. We build our system using historical trajectories generated by over 12,000 Taxis during 110 days and validate the system with extensive evaluations including in-the-field user studies.
Sid Chi-kin Chau - One of the best experts on this subject based on the ideXlab platform.
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Improving Viability of Electric Taxis by Taxi Service Strategy Optimization: A Big Data Study of New York City
IEEE Transactions on Intelligent Transportation Systems, 2019Co-Authors: Chien-ming Tseng, Sid Chi-kin ChauAbstract:Electrification of transportation is critical for a low-carbon society. In particular, public vehicles (e.g., Taxis) provide a crucial opportunity for electrification. Despite the benefits of eco-friendliness and energy efficiency, adoption of electric Taxis faces several obstacles, including constrained driving range, long recharging duration, limited charging stations, and low gas price, all of which impede taxi drivers' decisions to switch to electric Taxis. On the other hand, the popularity of ride-hailing mobile apps facilitates the computerization and optimization of taxi service strategies, which can provide computer-assisted decisions of navigation and roaming for taxi drivers to locate potential customers. This paper examines the viability of electric Taxis with the assistance of taxi service strategy optimization, in comparison with conventional Taxis with internal combustion engines. A big data study is provided using a large data set of real-world taxi trips in New York City (NYC). Our methodology is to first model the computerized taxi service strategy by Markov decision process, and then obtain the optimized taxi service strategy based on NYC taxi trip data set. The profitability of electric taxi drivers is studied empirically under various battery capacity and charging conditions. Consequently, we shed light on the solutions that can improve viability of electric Taxis.
Liang Hu - One of the best experts on this subject based on the ideXlab platform.
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Analyzing battery electric vehicle feasibility from taxi travel patterns: The case study of New York City, USA
Transportation Research Part C: Emerging Technologies, 2018Co-Authors: Liang Hu, Zhenhong Lin, Jing Dong, Jie YangAbstract:Electric Taxis have the potential to improve urban air quality and save driver's energy expenditure. Although battery electric vehicles (BEVs) have drawbacks such as the limited range and charging inconvenience, technological progress has been presenting promising potential for electric Taxis. Many cities around the world including New York City, USA are taking initiatives to replace gasoline Taxis with plug-in electric vehicles. This paper extracts ten variables from the trip data of the New York City yellow Taxis to represent their spatial-temporal travel patterns in terms of driver-shift, travel demand and dwell, and examines the implications of these driving patterns on the BEV taxi feasibility. The BEV feasibility of a taxi is quantified as the percentage of occupied trips that can be completed by BEVs of a given driving range during a year. It is found that the currently deployed 280 public charging stations in New York City are far from sufficient to support a large BEV taxi fleet. However, adding merely 372 new charging stations at various locations where Taxis frequently dwell can potentially make BEVs with 200- and 300-mile ranges feasible for more than half of the taxi fleet. The results also show that Taxis with certain characteristics are more suitable for switching to BEV-200 or BEV-300, such as fewer daily shifts, fewer drivers assigned to the taxi, shorter daily driving distance, fewer daily dwells but longer dwelling time, and higher likelihood to dwell at the borough of Manhattan.
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predicting market potential and environmental benefits of deploying electric Taxis in nanjing china
Transportation Research Part D-transport and Environment, 2016Co-Authors: Jie Yang, Jing Dong, Liang HuAbstract:This paper investigates the market potential and environmental benefits of replacing internal combustion engine (ICE) vehicles with battery electric vehicles (BEVs) in the taxi fleet in Nanjing, China. Vehicle trajectory data collected by onboard global positioning system (GPS) units are used to study the travel patterns of Taxis. The impacts of charger power, charging infrastructure coverage, and taxi apps on the feasibility of electric Taxis are quantified, considering taxi drivers’ recharging behavior and operating activities. It is found that (1) depending on the charger power and coverage, 19% (with AC Level 2 chargers and 20% charger network coverage) to 56% (with DC chargers and 100% charger network coverage) of the ICE vehicles can be replaced by electric Taxis without driving pattern changes; (2) by using taxi apps to find nearby passengers and charging stations, drivers could utilize the empty cruising time to charge the battery, which may increase the acceptance of BEVs by up to 82.6% compared to the scenario without taxi apps; and (3) tailpipe emissions in urban areas could be significantly reduced with taxi electrification: a mixed taxi fleet with 46% compressed-natural-gas-powered (CNG) and 54% electricity-powered vehicles can reduce the tailpipe emissions by 48% in comparison with the fleet of 100% CNG Taxis.
