Jing-Quan Li

Traveler Information Tool with Integrated Real-Time Transit Information and Multimodal Trip Planning: Design and Implementation

The chief objective of the PATH2Go multimodal traveler information application is to improve the accessibility and the quality of real-time traveler information and to make transit a known and viable choice for travelers. PATH2Go was developed as part of a field test on the US-101 corridor in the San Francisco Bay Area of California, with the primary hypothesis that travelers would benefit from real-time multimodal traveler information and therefore would be likely to consider using transit. PATH2Go integrates a web-based multimodal trip-planning tool that uses real-time transit, traffic, and parking information; a web-based search tool that finds real-time information about transit arrivals and schedules; and a mobile application that provides personalized en route transit trip information. PATH2Go integrates these major components of traveler information in one platform and makes real-time information easily accessible to travelers. The PATH2Go system architecture and major design considerations are described, and enabling technologies–including the Global Positioning System (GPS) fusing algorithm and a scenario-parsing algorithm based on GPS location data–are introduced.

Path2Go: Context-aware services for mobile real-time multimodal traveler information

Mobile platforms are now becoming a more and more important medium for providing information to travelers on the move. To improve the accuracy and relevance of the mobile traveler information, context awareness has become a active research topic. In this paper, we describe algorithms and services provided by Path2Go, a multimodal traveler information system developed by California PATH, UC Berkeley. The Path2Go activity detection algorithm, the core of the context-aware design, has made the following contributions: (1) it uses a rule-based multi-hypothesis Bayesian method for mode detection, to address the limitations of using mobile phone GPS for activity detection and increase the speed of convergence; (2) it fuses GPS data from transit vehicles and the GPS of the users mobile phone for better activity detection; and (3) it enables several experimental services, including variable-frequency client-server communication and need-based GPS use. Field testing of the Path2Go activity detection algorithms showed reasonably good results. The Path2Go application has also been made available to the public through iPhone, Android and Windows Mobile platforms, with some of the features discussed in this paper included.

A Multimodal Trip Planning System With Real-Time Traffic and Transit Information

Most transit trip planning systems are based on static schedules and generate trips that do not dynamically respond to delays in transit operation caused by traffic congestion or accidents. In addition, the driving-parking-then-transit travel mode is common in metropolitan areas. However, very few transit trip planners incorporate real-time transit data into this mode. This article describes a multimodal trip planning system for multiple modes: driving, transit, and driving-parking-then-transit. The system considers the real-time transit arrival time, which is estimated by a prediction model. Both Web-based and mobile phone-based clients are used to access the system. Case studies show that the multimodal trip planning system works well in real-life situations.

Planning for Bus Rapid Transit in Single Dedicated Bus Lane

Bus rapid transit (BRT) systems with dedicated lanes have shown advantages over traditional bus systems and have attracted more transit riders. However, it is not always possible to build BRT systems with double dedicated lanes because of physical and cost constraints. A BRT system with a single dedicated lane is more practical in such situations. In a single-lane configuration, buses approaching from opposite directions have to share the same road section and can overtake or pass each other only at the bus stops. An optimization model is proposed to describe the synchronization requirements of the BRT buses with the objective of minimizing the total travel and dwell time. The computational results show that a BRT system with a single dedicated lane yields total travel time that is similar to that of a BRT system with double dedicated lanes when the headway is not short (e.g., more than 20 min). In addition, to address possible delay at intersections, a simple speed control algorithm is implemented to adjust the bus speed in real time if the bus is delayed considerably. A microscopic simulation based on VISSIM is conducted to examine the impacts of the BRT bus on other traffic and the performance of the speed control. The simulation result shows that the speed control effectively handles the delay in the intersection and the other traffic is rarely affected by the speed control.

Bicyclist Intersection Crossing Times

In support of efforts to improve traffic signal timing to accommodate bicyclists’ needs, observations were made of the timing of bicyclists’ intersection crossing maneuvers. Video recordings were made of bicyclists’ crossings and the video images were processed to extract the bicyclists’ trajectories. These trajectories were synchronized with video images of the traffic signals so that the timing of the bicyclists’ maneuvers could be determined relative to the signal phases. The processed data yielded cumulative distributions of the crossing speeds of bicyclists who did not have to stop at the intersection and the start-up times and final crossing speeds of the bicyclists who had to cross from a standing start. A unique feature of these data is the timing information relative to the traffic signal, which is used to define recommended signal times to permit most bicyclists to cross wide arterial intersections safely.

Evaluation of probe vehicle sampling strategies for traffic signal control

The impending widespread availability of realtime traffic condition data from vehicles serving as traffic probes offers the possibility of significant advances in traffic signal control performance. In order to realize these advances, it is necessary to understand the capabilities and limitations of traffic probe data collection. In this paper, vehicle trajectories from a microscopic simulation of an arterial corridor are used as the baseline truth model, and are then sampled according to a variety of sampling strategies that could be implemented on probe vehicles. Measures of effectiveness relevant to traffic signal control, such as travel times and speeds, queue lengths and percentages of vehicles that need to stop, are estimated using the sampled data and these estimates are compared with the baseline truth values. These comparisons show the difficulty of estimating the MOEs at low market penetrations of probe vehicles, indicating that at the lower market penetrations it will probably be necessary to aggregate data from multiple signal cycles in order to obtain reliable enough outputs to use for real-time signal control adjustments.

Integrating Travelers and Transit into Solutions for Congestion Relief

Real-time highway and transit information, when presented in parallel, has the potential to influence travelers to make informed decisions to choose transit when highways are congested to save time and make the transit trip less stressful and more productive or pleasurable. The mode shifts by commuters can potentially relieve traffic congestion, reduce fuel consumption, and lower tailpipe emissions. Under the sponsorship of USDOT and California Department of Transportation, California PATH at University of California at Berkeley developed and field tested Path2go--a suite of both web-based and mobile-phone-based applications to assess if integrated multimodal real-time traveler information can enable travelers to make choice decisions. Evaluation of data collected through field testing showed that the Path2go application performed well with regard to its capability to integrate real-time, multimodal information; the accuracy and reliability of the information; its usefulness in helping users to reduce waiting time and overall travel time; and its effectiveness in encouraging travelers to consider transit as a more viable choice.

Data Collection for Measuring Performance of Integrated Transportation Systems

More than ever, traffic congestion is plaguing our heavily populated metropolitan areas. Transportation professionals have recognized that we cannot build our way out of this ever-increasing congestion. The challenge over the next decade is to get more out of the existing transportation system by improving its productivity. To address this challenge, we must evolve into “system managers”: agencies and individuals who manage the system through operational strategies, complemented by targeted expansion investments. The concept of system management has been embraced by many agencies at both state and federal levels. For example, the California Department of Transportation (Caltrans) and most of its stakeholders adopted the concept of the System Management pyramid, as depicted in Fig. 3.1. The foundation of system management is “System Monitoring and Evaluation”. This foundation provides support for a variety of informed investment decisions.