Yiguang Xuan

Identifying Lane-Change Maneuvers with Probe Vehicle Data and an Observed Asymmetry in Driver Accommodation

AbstractThis paper uses an instrumented probe vehicle to monitor ambient traffic and overcome many challenges of observing traffic flow phenomena that occur over extended distances. One contribution of this paper is a general methodology to identify the probe vehicle’s lane of travel without a priori knowledge of where the lanes are. This knowledge is used to find the probe’s lane-change maneuvers (LCMs), to differentiate these LCMs from GPS errors, and, in conjunction with a ranging sensor, to identify which lanes the ambient vehicles are in to find their LCMs. The second contribution of this paper comes from the identified LCMS. The data are used to provide an independent validation of earlier studies, and thus yield further evidence of how LCMs contribute to the formation of disturbances within freeway queues. In particular, it is found that vehicles following an entering vehicle generally complete their response and return to steady state quicker than those following an exiting vehicle. As discussed h...

Estimation of measures of effectiveness based on Connected Vehicle data

Vehicle-infrastructure cooperation via the Connected Vehicle initiative is a promising mobile data source for improving real-time traffic management applications such as adaptive signal control. This paper focuses on developing estimation methods with the use of Connected Vehicle data for several measures of effectiveness (e.g., queue length, average speed, number of stops), essential for determining traffic conditions on urban signalized arterials for real-time applications. This research systematically determines minimum penetration rates that allow accurate estimates for a wide range of measures of effectiveness in undersaturated traffic conditions. The estimation of these measures and minimum penetration requirements has been tested using Next Generation Simulation (NGSIM) data.

Crowd Sourcing Indoor Maps with Mobile Sensors

The paper describes algorithms required to enable the crowd sourcing of indoor building maps, i.e., where GPS is not available. Nevertheless to enable crowd sourcing we use the 3-axis accelerometers and the 3-axis magnetometers available in many smart phones and the piezometer in a Nike running shoe. Volunteers carry the sensors while walking around in buildings, and use some application on their smart phone to send the data to a mapping server. We present the algorithms to obtain walking trajectories from the data by dead reckoning, and to estimate indoor maps with multiple walking trajectories.

Lane Change Maneuver Detection from Probe Vehicle DGPS Data

The impact of lane change maneuvers is fundamental to microscopic traffic flow theory. Due to the difficulty of tracking many vehicles over time and space, most of the published research in this area seek to find lane change maneuvers visually from wayside cameras. This paper presents a different approach, finding the lane change maneuvers of a probe vehicle itself using differential Global Positioning System (DGPS) data. We first use multiple probe vehicle trajectories through a study corridor to establish a reference trajectory from the median of all trajectories and this reference trajectory is used to define the position of the current lane. This approach eliminates the need for high-resolution maps accurate enough to capture the exact position of the individual lanes. Our lane change maneuver detection is then divided into two parts, controlling for the impacts of mandatory lane change maneuvers (MLC) and then for discretionary lane change maneuvers (DLC). MLC are detected by comparing the difference between the mean and median of lateral distance of all trajectories relative to a reference trajectory. After distinguishing all the MLCs, the DLC are found by setting lateral thresholds around the reference trajectory, i.e., when a given trajectory leaves this virtual lane. In the process we control for the impacts of GPS errors, such as multipath, arising from obstructions. DLC are then found by comparing the out-of-threshold-line time and length to a threshold acquired empirically from data

Making indoor maps with portable accelerometer and magnetometer

The paper describes algorithms required to enable the crowd sourcing of indoor building maps, i.e., where global positioning system (GPS) is not available. Nevertheless to enable crowd sourcing we use the 3-axis accelerometers and the 3-axis magnetometers available in many smart phones. Volunteers carry the phones while walking around in buildings, and use some application on their smart phones to send the data to a mapping server. We present the algorithms to obtain walking trajectories from the data by dead reckoning, and to estimate indoor maps with multiple walking trajectories.

A high-range-resolution microwave radar system for traffic flow rate measurement

The estimation of traffic flow parameters is a fundamental problem in intelligent traffic systems. This paper presents a system based on a microwave radar with high range resolution and short sweep time to estimate the flow rate of traffic stream. Radar echoes are organized into sequential height images. The sequential height images contain all reflecting point information and thus give out detailed height distribution of echo intensity. By processing the height images with our vehicle detection and classification algorithms, passing vehicles can be automatically detected and simultaneously classified into eight types.

Presignal Used to Increase Bus- and Car-Carrying Capacity at Intersections: Theory and Experiment

In theory midblock presignals can be used to increase the capacity of signalized intersections [The authors define “presignal” as “a set of signal heads that are installed in the middle of a block upstream of an intersection.”—Ed.]. The capacity is increased because presignals can reorganize how traffic is stored between a presignal and an intersection downstream. However, different vehicle classes have different acceleration characteristics, and the effectiveness of presignals hinges on the assumption of linear superposition; that is, the total time to discharge a mixture of distinct vehicle classes equals the sum of the times to discharge each vehicle class separately. This assumption has not been tested in the field. In this study, results from a natural experiment are used to validate the assumption for the case of cars and buses. The effectiveness of presignals to increase intersection capacity is also demonstrated.

A mathematical framework for delay analysis in single source networks

This article presents a mathematical framework for modeling heterogeneous flow networks with a single source and multiple sinks. The traffic is differentiated by its destination (i.e. Lagrangian flow) and different flow groups are assumed to satisfy the first-in-first-out (FIFO) condition at each junction. We show that our model leads to a well-posed problem for computing the dynamics of the system and prove that the solution is unique through a mathematical derivation of the model properties. The framework is then used to analytically prescribe the delays at each junction of the network and across any sub-path, which is one of the contributions of the article. This is a critical requirement when solving control and optimization problems over the network, such as system optimal network routing and solving for equilibrium behavior. In fact, the framework provides analytical expressions for the delay at any node or sub-path as a function of the inflow at any upstream node. Furthermore, the model can be solved numerically using a very simple and efficient feed forward algorithm. We demonstrate the versatility of the framework by applying it to a diverge junction with complex junction dynamics.

Solving the user equilibrium departure time problem at an off-ramp with incentive compatible cost functions

We consider the equilibrium departure time problem for a set of vehicles that travel through a network with capacity restrictions and need to reach a destination at a fixed time. The vehicles incur a penalty for both any queuing delays and arriving at the destination early or late. In particular, we consider the case of a congested off-ramp, which is a common occurrence next to commercial hubs during the morning commute, and has the added negative effect of reducing the capacity on the freeway for through traffic. We study the use of incentives and tolls to manipulate the equilibrium departure times of the exiting vehicles and thereby mitigate the impact on through traffic. Our main result is to show the existence and uniqueness properties of the departure time equilibrium for a general class of delay and arrival time cost functions, which allows for discontinuities in the arrival cost function. This enables the use of step incentives or tolls, which are the mostly common strategies used in practice. Our results also apply to the Vickrey single bottleneck equilibrium, which is a special case of our network.