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Articles 91 - 120 of 203
Full-Text Articles in Transportation
Pricing And Equilibrium In On-Demand Ride-Pooling Markets, Jintao Ke, Hai Yang, Xinwei Li, Hai Wang, Jieping Ye
Pricing And Equilibrium In On-Demand Ride-Pooling Markets, Jintao Ke, Hai Yang, Xinwei Li, Hai Wang, Jieping Ye
Research Collection School Of Computing and Information Systems
With the recent rapid growth of technology-enabled mobility services, ride-sourcing platforms, such as Uber and DiDi, have launched commercial on-demand ride-pooling programs that allow drivers to serve more than one passenger request in each ride. Without requiring the prearrangement of trip schedules, these programs match on-demand passenger requests with vehicles that have vacant seats. Ride-pooling programs are expected to offer benefits for both individual passengers in the form of cost savings and for society in the form of traffic alleviation and emission reduction. In addition to some exogenous variables and environments for ride-sourcing market, such as city size and population …
Adaptive Large Neighborhood Search For Vehicle Routing Problem With Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu
Adaptive Large Neighborhood Search For Vehicle Routing Problem With Cross-Docking, Aldy Gunawan, Audrey Tedja Widjaja, Pieter Vansteenwegen, Vincent F. Yu
Research Collection School Of Computing and Information Systems
Cross-docking is considered as a method to manage and control the inventory flow, which is essential in the context of supply chain management. This paper studies the integration of the vehicle routing problem with cross-docking, namely VRPCD which has been extensively studied due to its ability to reducethe overall costs occurring in a supply chain network. Given a fleet of homogeneous vehicles for delivering a single type of product from suppliers to customers through a cross-dock facility, the objective of VRPCD is to determine the number of vehicles used and the corresponding vehicle routes, such that the vehicleoperational and transportation …
The Prediction Of Delay Time At Intersection And Route Planning For Autonomous Vehicles, Genwang Gou, Yongxin Zhao, Jiawei Liang, Ling Shi
The Prediction Of Delay Time At Intersection And Route Planning For Autonomous Vehicles, Genwang Gou, Yongxin Zhao, Jiawei Liang, Ling Shi
Research Collection School Of Computing and Information Systems
Intelligent Intersections (roundabout and crossroads) management is considered as one of the challenges to significantly improve urban traffic efficiency. Recent researches in artificial intelligence suggest that autonomous vehicles have the possibility of forming intelligent intersection management, and likely to occupy the leading role in future urban traffic. If route planning method can be used for route decision of autonomous vehicle, the urban traffic efficiency can be further improved. In this paper, we propose an Intelligent Intersection Control Protocol (IICP) for controlling autonomous vehicles cross intersection, and recommend route for autonomous vehicles to reduce travel time and improve urban traffic efficiency. …
Goods Consumed During Transit In Split Delivery Vehicle Routing Problems: Modeling And Solution, Wenzhe Yang, Di Wang, Wei Pang, Ah-Hwee Tan, You Zhou
Goods Consumed During Transit In Split Delivery Vehicle Routing Problems: Modeling And Solution, Wenzhe Yang, Di Wang, Wei Pang, Ah-Hwee Tan, You Zhou
Research Collection School Of Computing and Information Systems
This article presents the modeling and solution of an extended type of split delivery vehicle routing problem (SDVRP). In SDVRP, the demands of customers need to be met by efficiently routing a given number of capacitated vehicles, wherein each customer may be served multiple times by more than one vehicle. Furthermore, in many real-world scenarios, consumption of vehicles en route is the same as the goods being delivered to customers, such as food, water and fuel in rescue or replenishment missions in harsh environments. Moreover, the consumption may also be in virtual forms, such as time spent in constrained tasks. …
Hierarchical Multiagent Reinforcement Learning For Maritime Traffic Management, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau
Hierarchical Multiagent Reinforcement Learning For Maritime Traffic Management, Arambam James Singh, Akshat Kumar, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Increasing global maritime traffic coupled with rapid digitization and automation in shipping mandate developing next generation maritime traffic management systems to mitigate congestion, increase safety of navigation, and avoid collisions in busy and geographically constrained ports (such as Singapore's). To achieve these objectives, we model the maritime traffic as a large multiagent system with individual vessels as agents, and VTS (Vessel Traffic Service) authority as a regulatory agent. We develop a hierarchical reinforcement learning approach where vessels first select a high level action based on the underlying traffic flow, and then select the low level action that determines their future …
Route Choice Behaviour And Travel Information In A Congested Network: Static And Dynamic Recursive Models, Giselle De Moraes Ramos, Tien Mai, Winnie Daamen, Emma Frejinger
Route Choice Behaviour And Travel Information In A Congested Network: Static And Dynamic Recursive Models, Giselle De Moraes Ramos, Tien Mai, Winnie Daamen, Emma Frejinger
Research Collection School Of Computing and Information Systems
Travel information has the potential to influence travellers choices, in order to steer travellers to less congested routes and alleviate congestion. This paper investigates, on the one hand, how travel information affects route choice behaviour, and on the other hand, the impact of the travel time representation on the interpretation of parameter estimates and prediction accuracy. To this end, we estimate recursive models using data from an innovative data collection effort consisting of route choice observation data from GPS trackers, travel diaries and link travel times on the overall network. Though such combined data sets exist, these have not yet …
Incorporating A Reverse Logistics Scheme In A Vehicle Routing Problem With Cross-Docking Network: A Modelling Approach, Audrey Tedja Widjaja, Aldy Gunawan, Panca Jodiawan, Vincent F. Yu
Incorporating A Reverse Logistics Scheme In A Vehicle Routing Problem With Cross-Docking Network: A Modelling Approach, Audrey Tedja Widjaja, Aldy Gunawan, Panca Jodiawan, Vincent F. Yu
Research Collection School Of Computing and Information Systems
Reverse logistics has been implemented by various companies because of its ability to gain more profit and maintain the competitiveness of the company. However, extensive studies on the vehicle routing problem with cross-docking (VRPCD) only considered the forward flow instead of the reverse flow. Motivated by the ability of a VRPCD network to minimize the distribution cost in the forward flow, this research incorporates the reverse logistics scheme in a VRPCD network, namely the VRP with reverse cross-docking (VRP-RCD). We propose a VRP-RCD mathematical model for a four-level supply chain network that involves suppliers, cross-dock, customers, and outlets. The main …
Using Reinforcement Learning To Minimize The Probability Of Delay Occurrence In Transportation, Zhiguang Cao, Hongliang Guo, Wen Song, Kaizhou Gao, Zhengghua Chen, Le Zhang, Xuexi Zhang
Using Reinforcement Learning To Minimize The Probability Of Delay Occurrence In Transportation, Zhiguang Cao, Hongliang Guo, Wen Song, Kaizhou Gao, Zhengghua Chen, Le Zhang, Xuexi Zhang
Research Collection School Of Computing and Information Systems
Reducing traffic delay is of crucial importance for the development of sustainable transportation systems, which is a challenging task in the studies of stochastic shortest path (SSP) problem. Existing methods based on the probability tail model to solve the SSP problem, seek for the path that minimizes the probability of delay occurrence, which is equal to maximizing the probability of reaching the destination before a deadline (i.e., arriving on time). However, they suffer from low accuracy or high computational cost. Therefore, we design a novel and practical Q-learning approach where the converged Q-values have the practical meaning as the actual …
Neural Approximate Dynamic Programming For On-Demand Ride-Pooling, Sanket Shah, Meghna Lowalekar, Pradeep Varakantham
Neural Approximate Dynamic Programming For On-Demand Ride-Pooling, Sanket Shah, Meghna Lowalekar, Pradeep Varakantham
Research Collection School Of Computing and Information Systems
On-demand ride-pooling (e.g., UberPool, LyftLine, GrabShare) has recently become popular because of its ability to lower costs for passengers while simultaneously increasing revenue for drivers and aggregation companies (e.g., Uber). Unlike in Taxi on Demand (ToD) services – where a vehicle is assigned one passenger at a time – in on-demand ride-pooling, each vehicle must simultaneously serve multiple passengers with heterogeneous origin and destination pairs without violating any quality constraints. To ensure near real-time response, existing solutions to the real-time ride-pooling problem are myopic in that they optimise the objective (e.g., maximise the number of passengers served) for the current …
A Mathematical Programming Model For The Green Mixed Fleet Vehicle Routing Problem With Realistic Energy Consumption And Partial Recharges, Vincent F. Yu, Panca Jodiwan, Aldy Gunawan, Audrey Tedja Widjaja
A Mathematical Programming Model For The Green Mixed Fleet Vehicle Routing Problem With Realistic Energy Consumption And Partial Recharges, Vincent F. Yu, Panca Jodiwan, Aldy Gunawan, Audrey Tedja Widjaja
Research Collection School Of Computing and Information Systems
A green mixed fleet vehicle routing with realistic energy consumption and partial recharges problem (GMFVRP-REC-PR) is addressed in this paper. This problem involves a fixed number of electric vehicles and internal combustion vehicles to serve a set of customers. The realistic energy consumption which depends on several variables is utilized to calculate the electricity consumption of an electric vehicle and fuel consumption of an internal combustion vehicle. Partial recharging policy is included into the problem to represent the real life scenario. The objective of this problem is to minimize the total travelled distance and the total emission produced by internal …
Inferring Accurate Bus Trajectories From Noisy Estimated Arrival Time Records, Lakmal Meegahapola, Noel Athaide, Kasthuri Jayarajah, Shili Xiang, Archan Misra
Inferring Accurate Bus Trajectories From Noisy Estimated Arrival Time Records, Lakmal Meegahapola, Noel Athaide, Kasthuri Jayarajah, Shili Xiang, Archan Misra
Research Collection School Of Computing and Information Systems
Urban commuting data has long been a vital source of understanding population mobility behaviour and has been widely adopted for various applications such as transport infrastructure planning and urban anomaly detection. While individual-specific transaction records (such as smart card (tap-in, tap-out) data or taxi trip records) hold a wealth of information, these are often private data available only to the service provider (e.g., taxicab operator). In this work, we explore the utility in harnessing publicly available, albeit noisy, transportation datasets, such as noisy “Estimated Time of Arrival" (ETA) records (commonly available to commuters through transit Apps or electronic signages). We …
Model And Analysis Of Labor Supply For Ride-Sharing Platforms In The Presence Of Sample Self-Selection And Endogeneity, Hao Sun, Hai Wang, Zhixi Wan
Model And Analysis Of Labor Supply For Ride-Sharing Platforms In The Presence Of Sample Self-Selection And Endogeneity, Hao Sun, Hai Wang, Zhixi Wan
Research Collection School Of Computing and Information Systems
With the popularization of ride-sharing services, drivers working as freelancers on ride-sharing platforms can design their schedules flexibly. They make daily decisions regard- ing whether to participate in work, and if so, how many hours to work. Factors such as hourly income rate affect both the participation decision and working-hour decision, and evaluation of the impacts of hourly income rate on labor supply becomes important. In this paper, we propose an econometric framework with closed-form measures to estimate both the participation elasticity (i.e., extensive margin elasticity) and working-hour elasticity (i.e., intensive margin elasticity) of labor supply. We model the sample …
Zac: A Zone Path Construction Approach For Effective Real-Time Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Zac: A Zone Path Construction Approach For Effective Real-Time Ridesharing, Meghna Lowalekar, Pradeep Varakantham, Patrick Jaillet
Research Collection School Of Computing and Information Systems
Real-time ridesharing systems such as UberPool, Lyft Line, GrabShare have become hugely popular as they reduce the costs for customers, improve per trip revenue for drivers and reduce traffic on the roads by grouping customers with similar itineraries. The key challenge in these systems is to group the right requests to travel in available vehicles in real-time, so that the objective (e.g., requests served, revenue or delay) is optimized. The most relevant existing work has focussed on generating as many relevant feasible (with respect to available delay for customers) combinations of requests (referred to as trips) as possible in real-time. …
Volumetric Optimization Of Freight Cargo Loading: Case Study Of A Smu Forwarder, Tristan Lim, Michael Ser Chong Ping, Mark Goh, Shi Ying Jacelyn Tan
Volumetric Optimization Of Freight Cargo Loading: Case Study Of A Smu Forwarder, Tristan Lim, Michael Ser Chong Ping, Mark Goh, Shi Ying Jacelyn Tan
Research Collection School Of Computing and Information Systems
Purpose: Freight forwarders faces a challenging environment of high market volatility and margin compression risks. Hence, strategic consideration is given to undertaking capacity management and transport asset ownership to achieve longer term cost leadership. Doing so will also help to address management issues, such as better control of potential transport disruptions, improve scheduling flexibility and efficiency, and provide service level enhancement.Design/methodology/approach: The case company currently hastruck resource which is unprofitable, and the firm’s schedulers are having difficulty optimizing the loading capacity. We apply Genetic Algorithm (GA) to undertake volumetric optimization of truckcapacity and to build an easy-to-use platform to help …
Entrans: Leveraging Kinetic Energy Harvesting Signal For Transportation Mode Detection, Guohao Lan, Weitao Xu, Dong Ma, Sara Khalifa, Mahbub Hassan, Wen Hu
Entrans: Leveraging Kinetic Energy Harvesting Signal For Transportation Mode Detection, Guohao Lan, Weitao Xu, Dong Ma, Sara Khalifa, Mahbub Hassan, Wen Hu
Research Collection School Of Computing and Information Systems
Monitoring the daily transportation modes of an individual provides useful information in many application domains, such as urban design, real-time journey recommendation, as well as providing location-based services. In existing systems, accelerometer and GPS are the dominantly used signal sources for transportation context monitoring which drain out the limited battery life of the wearable devices very quickly. To resolve the high energy consumption issue, in this paper, we present EnTrans, which enables transportation mode detection by using only the kinetic energy harvester as an energy-efficient signal source. The proposed idea is based on the intuition that the vibrations experienced by …
Re-Org: An Online Repositioning Guidance Agent, Muralidhar Konda, Pradeep Varakantham, Aayush Saxena, Meghna Lowalekar
Re-Org: An Online Repositioning Guidance Agent, Muralidhar Konda, Pradeep Varakantham, Aayush Saxena, Meghna Lowalekar
Research Collection School Of Computing and Information Systems
No abstract provided.
Route Planning For A Fleet Of Electric Vehicles With Waiting Times At Charging Stations, Baoxiang Li, Shashi Shekhar Jha, Hoong Chuin Lau
Route Planning For A Fleet Of Electric Vehicles With Waiting Times At Charging Stations, Baoxiang Li, Shashi Shekhar Jha, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
Electric Vehicles (EVs) are the next wave of technology in the transportation industry. EVs are increasingly becoming common for personal transport and pushing the boundaries to become the mainstream mode of transportation. Use of such EVs in logistic fleets for delivering customer goods is not far from becoming reality. However, managing such fleet of EVs bring new challenges in terms of battery capacities and charging infrastructure for efficient route planning. Researchers have addressed such issues considering different aspects of the EVs such as linear battery charging/discharging rate, fixed travel times, etc. In this paper, we address the issue of waiting …
Analysis Of Bus Ride Comfort Using Smartphone Sensor Data, Hoong-Chor Chin, Xingting Pang, Zhaoxia Wang
Analysis Of Bus Ride Comfort Using Smartphone Sensor Data, Hoong-Chor Chin, Xingting Pang, Zhaoxia Wang
Research Collection School Of Computing and Information Systems
Passenger comfort is an important indicator that is often used to measure the quality of public transport services. It may also be a crucial factor in the passenger’s choice of transport mode. The typical method of assessing passenger comfort is through a passenger interview survey which can be tedious. This study aims to investigate the relationship between bus ride comfort based on ride smoothness and the vehicle’s motion detected by the smartphone sensors. An experiment was carried out on a bus fixed route within the University campus where comfort levels were rated on a 3-point scale and recorded at 5-second …
A State Aggregation Approach For Stochastic Multiperiod Last-Mile Ride-Sharing Problems, Lucas Agussurja, Shih-Fen Cheng, Hoong Chuin Lau
A State Aggregation Approach For Stochastic Multiperiod Last-Mile Ride-Sharing Problems, Lucas Agussurja, Shih-Fen Cheng, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
The arrangement of last-mile services is playing an increasingly important role in making public transport more accessible. We study the use of ridesharing in satisfying last-mile demands with the assumption that demands are uncertain and come in batches. The most important contribution of our paper is a two-level Markov decision process framework that is capable of generating a vehicle-dispatching policy for the aforementioned service. We introduce state summarization, representative states, and sample-based cost estimation as major approximation techniques in making our approach scalable. We show that our approach converges and solution quality improves as sample size increases. We also apply …
Routing And Scheduling For A Last-Mile Transportation System, Hai Wang
Routing And Scheduling For A Last-Mile Transportation System, Hai Wang
Research Collection School Of Computing and Information Systems
The last-mile problem concerns the provision of travel services from the nearest public transportation node to a passenger’s home or other destination. We study the operation of an emerging last-mile transportation system (LMTS) with batch demands that result from the arrival of groups of passengers who desire last-mile service at urban metro stations or bus stops. Routes and schedules are determined for a multivehicle fleet of delivery vehicles, with the objective of minimizing passenger waiting time and riding time. An exact mixed-integer programming (MIP) model for LMTS operations is presented first, which is difficult to solve optimally within acceptable computational …
Design And Implementation Of Decision Support For Traffic Management At Multipurpose Port Gates, Ketki Kulkarni, Hoong Chuin Lau, Hai Wang, Sathyavarathan Sivabalasingam, Trong Khiem Tran
Design And Implementation Of Decision Support For Traffic Management At Multipurpose Port Gates, Ketki Kulkarni, Hoong Chuin Lau, Hai Wang, Sathyavarathan Sivabalasingam, Trong Khiem Tran
Research Collection School Of Computing and Information Systems
Effective traffic management can help port operators gain a competitive edge in service level and efficient use of limited resources. One critical aspect of traffic management is gate operations management, ensuring a good customer experience to logistic carriers and considering the impact of congestion in and around the port. In this paper, we describe the design and implementation of a decision support tool to help gate operators plan for future scenarios with fluctuating demand and limited resources. We propose a simulation optimization framework which incorporates theoretical results from queuing theory to approximate complex multi-lane multi-server systems. Our major contribution in …
Using Smart Card Data To Model Commuters’ Responses Upon Unexpected Train Delays, Xiancai Tian, Baihua Zheng
Using Smart Card Data To Model Commuters’ Responses Upon Unexpected Train Delays, Xiancai Tian, Baihua Zheng
Research Collection School Of Computing and Information Systems
The mass rapid transit (MRT) network is playing an increasingly important role in Singapore's transit network, thanks to its advantages of higher capacity and faster speed. Unfortunately, due to aging infrastructure, increasing demand, and other reasons like adverse weather condition, commuters in Singapore recently have been facing increasing unexpected train delays (UTDs), which has become a source of frustration for both commuters and operators. Most, if not all, existing works on delay management do not consider commuters' behavior. We dedicate this paper to the study of commuters' behavior during UTDs. We adopt a data-driven approach to analyzing the six-month' real …
Integrated Reward Scheme And Surge Pricing In A Ride-Sourcing Market, Hai Yang, Chaoyi Shao, Hai Wang, Jieping Ye
Integrated Reward Scheme And Surge Pricing In A Ride-Sourcing Market, Hai Yang, Chaoyi Shao, Hai Wang, Jieping Ye
Research Collection School Of Computing and Information Systems
Surge pricing is commonly used in on-demand ride-sourcing platforms (e.g., Uber, Lyft and Didi) to dynamically balance demand and supply. However, since the price for ride service cannot be unlimited, there is usually a reasonable or legitimate range of prices in practice. Such a constrained surge pricing strategy fails to balance demand and supply in certain cases, e.g., even adopting the maximum allowed price cannot reduce the demand to an affordable level during peak hours. In addition, the practice of surge pricing is controversial and has stimulated long debate regarding its pros and cons. To address the limitation of current …
Inferring Trip Occupancies In The Rise Of Ride-Hailing Services, Meng-Fen Chiang, Ee-Peng Lim, Wang-Chien Lee, Tuan-Anh Hoang
Inferring Trip Occupancies In The Rise Of Ride-Hailing Services, Meng-Fen Chiang, Ee-Peng Lim, Wang-Chien Lee, Tuan-Anh Hoang
Research Collection School Of Computing and Information Systems
The knowledge of all occupied and unoccupied trips made by self-employed drivers are essential for optimized vehicle dispatch by ride-hailing services (e.g., Didi Dache, Uber, Lyft, Grab, etc.). However, the occupancy status of vehicles is not always known to the service operators due to adoption of multiple ride-hailing apps. In this paper, we propose a novel framework, Learning to INfer Trips (LINT), to infer occupancy of car trips by exploring characteristics of observed occupied trips. Two main research steps, stop point classification and structural segmentation, are included in LINT. In the stop point classification step, we represent a vehicle trajectory …
Traffic-Cascade: Mining And Visualizing Lifecycles Of Traffic Congestion Events Using Public Bus Trajectories, Agus Trisnajaya Kwee, Meng-Fen Chiang, Philips Kokoh Prasetyo, Ee-Peng Lim
Traffic-Cascade: Mining And Visualizing Lifecycles Of Traffic Congestion Events Using Public Bus Trajectories, Agus Trisnajaya Kwee, Meng-Fen Chiang, Philips Kokoh Prasetyo, Ee-Peng Lim
Research Collection School Of Computing and Information Systems
As road transportation supports both economic and social activities in developed cities, it is important to maintain smooth traffic on all highways and local roads. Whenever possible, traffic congestions should be detected early and resolved quickly. While existing traffic monitoring dashboard systems have been put in place in many cities, these systems require high-cost vehicle speed monitoring instruments and detect traffic congestion as independent events. There is a lack of low-cost dashboards to inspect and analyze the lifecycle of traffic congestion which is critical in assessing the overall impact of congestion, determining the possible the source(s) of congestion and its …
Accurate And Cost-Effective Traffic Information Acquisition Using Adaptive Sampling: Centralized And V2v Schemes, Shiau Hong Lim, Yeow Khiang Chia, Laura Wynter
Accurate And Cost-Effective Traffic Information Acquisition Using Adaptive Sampling: Centralized And V2v Schemes, Shiau Hong Lim, Yeow Khiang Chia, Laura Wynter
Research Collection School Of Computing and Information Systems
The new generation of GPS-based tolling systems allow for a much higher degree of road sensing than has been available up to now. We propose an adaptive sampling scheme to collect accurate real-time traffic information from large-scale implementations of on-board GPS-based devices over a road network. The goal of the system is to minimize the transmission costs over all vehicles while satisfying requirements in the accuracy and timeliness of the traffic information obtained. The system is designed to make use of cellular communication as well as leveraging additional technologies such as roadside units equipped with WiFi and vehicle-to-vehicle (V2V) dedicated …
Transferring Time-Series Discrete Choice To Link-Based Route Choice In Space: Estimating Vehicle Type Preference Using Recursive Logit Model, Fabian Bastin, Yan Liu, Cinzia Cirillo, Tien Mai
Transferring Time-Series Discrete Choice To Link-Based Route Choice In Space: Estimating Vehicle Type Preference Using Recursive Logit Model, Fabian Bastin, Yan Liu, Cinzia Cirillo, Tien Mai
Research Collection School Of Computing and Information Systems
This paper considers a sequential discrete choice problem in a time domain, formulated and solved as a route choice problem in a space domain. Starting from a dynamic specification of time-series discrete choices, we show how it is transferrable to link-based route choices that can be formulated by a finite path choice multinomial logit model. This study establishes that modeling sequential choices over time and in space are equivalent as long as the utility of the choice sequence is additive over the decision steps, the link-specific attributes are deterministic, and the decision process is Markovian. We employ the recursive logit …
Accurate And Cost-Effective Traffic Information Acquisition Using Adaptive Sampling: Centralized And V2v Schemes, Shiau Hong Lim, Yeow Khiang Chia, Laura Wynter
Accurate And Cost-Effective Traffic Information Acquisition Using Adaptive Sampling: Centralized And V2v Schemes, Shiau Hong Lim, Yeow Khiang Chia, Laura Wynter
Research Collection School Of Computing and Information Systems
The new generation of GPS-based tolling systems allow for a much higher degree of road sensing than has been available up to now. We propose an adaptive sampling scheme to collect accurate real-time traffic information from large-scale implementations of on-board GPS-based devices over a road network. The goal of the system is to minimize the transmission costs over all vehicles while satisfying requirements in the accuracy and timeliness of the traffic information obtained. The system is designed to make use of cellular communication as well as leveraging additional technologies such as roadside units equipped with WiFi and vehicle-to-vehicle (V2V) dedicated …
A Driver Guidance System For Taxis In Singapore, Shashi Shekhar Jha, Shih-Fen Cheng, Meghna Lowalekar, Nicholas Wong, Rishikeshan Rajendram, Pradeep Varakantham, Nghia Troung Troung, Firmansyah Bin Abd Rahman
A Driver Guidance System For Taxis In Singapore, Shashi Shekhar Jha, Shih-Fen Cheng, Meghna Lowalekar, Nicholas Wong, Rishikeshan Rajendram, Pradeep Varakantham, Nghia Troung Troung, Firmansyah Bin Abd Rahman
Research Collection School Of Computing and Information Systems
Traditional taxi fleet operators world-over have been facing intense competitions from various ride-hailing services such as Uber and Grab.Based on our studies on the taxi industry in Singapore, we see that the emergence of Uber and Grab in the ride-hailing market has greatly impacted the taxi industry: the average daily taxi ridership for the past two years has been falling continuously, by close to 20% in total. In this work, we discuss how efficient real-time data analytics and large-scale multiagent optimization technology could help taxi drivers compete against more technologically advanced service platforms. Our system has been in field trial …
Taxis Strike Back: A Field Trial Of The Driver Guidance System, Shih-Fen Cheng, Shashi Shekhar Jha, Rishikeshan Rajendram
Taxis Strike Back: A Field Trial Of The Driver Guidance System, Shih-Fen Cheng, Shashi Shekhar Jha, Rishikeshan Rajendram
Research Collection School Of Computing and Information Systems
Traditional taxi fleet operators world-over have been facing intense competitions from various ride-hailing services such as Uber and Grab (specific to the Southeast Asia region). Based on our studies on the taxi industry in Singapore, we see that the emergence of Uber and Grab in the ride-hailing market has greatly impacted the taxi industry: the average daily taxi ridership for the past two years has been falling continuously, by close to 20% in total. In this work, we discuss how efficient real-time data analytics and large-scale multi-agent optimization technology could potentially help taxi drivers compete against more technologically advanced service …