Bhargava Rama Chilukuri

The paper presents a model-based demand-responsive traffic control system for mixed traffic conditions using sample travel time data. The model incorporates mixed traffic characteristics such as heterogeneity, limited lane discipline of varied vehicle types, and spatio-temporal traffic dynamics across the width of the road. The methodology includes optimization of intersection performance by accommodating the varying traffic demand through signal timing variables. On validation, the model yielded reliable queue estimates within a close proximity of the actual, ranging from 20 to 40 meters. Upon optimization, the proposed model reduced total intersection delay by 15.42% on an average across 14 cycles, for near-saturated traffic conditions. The optimal green splits are found to be responsive to the varying traffic demand. The proposed system is simple and can be easily implemented in the mixed traffic conditions.

Departure Time Planner (DTP) helps to efficiently manage the commute plan by providing smart travel assistance which suggests a departure from a given origin to a destination, given the desired arrival time at the destination. Towards this end, a DTP system is developed using a quasi-connected vehicle system where traffic data is collected from sparse sensor infrastructure. Novel methods and algorithms were developed accounting for the heterogeneous traffic conditions found in India. The traffic state prediction methodology based on the second-order traffic flow model shows that the system can reliably estimate the departure time for Indian conditions.

In the absence of pharmaceutical interventions for the Novel Coronavirus (COVID-19), countries have taken drastic steps like quarantine, prohibit large-scale gatherings, limited transport, social distancing, curfews, and lockdowns to curtail the spread of the virus. In light of these events, the current study attempts to understand the short-term changes in road traffic patterns, using data from two Wi-Fi MAC Scanners deployed at strategic locations in Chennai, India. The results indicate that the road traffic activities significantly reduced due to the restrictions in non-essential trips, workplace suspensions, and strict surveillance during lockdowns. However, as the lockdown rules eased, the road traffic activities began to recover. It is found that complete closedown is most effective in reducing road travel activity, but ad-hoc short duration complete closedowns may only yield temporary benefits. Also, extended lockdowns without proper enforcement may be ineffective since the public appeared to ignore the advisory after a while.

Increased travel times are often observed on urban roads, with signalized intersections being the major bottlenecks. The inability of existing static signal timings in accommodating the actual demand fluctuations could be one of the contributing factors. A traffic-responsive signal control system that changes signal timings according to traffic volume fluctuations may alleviate this problem. However, such problems are conventionally formulated based on the data collected from location-based sensors, which are infrastructure intensive and costly and fail to capture mixed and disordered traffic conditions. Considering these limitations, this paper presents an optimal signal design using sample travel time information collected from mobile data sources such as GPS/Bluetooth/Wi-Fi sensors that work independently of the traffic conditions and are relatively cost-effective. The proposed adaptive signal design minimizes total intersection delay at isolated intersections for every cycle based on the traffic conditions observed in the previous cycle. The mathematical programming-based formulation uses shock waves formed during the red and green phases to estimate optimal-phase durations. Results revealed that the proposed design is capable of handling traffic flow fluctuations without requiring the entire traffic stream data. The system demonstrated that sample data from four probe vehicles per phase is adequate for real-time optimal signal design. Results showed that the proposed model outperformed the existing Webster's signal design procedure with a delay reduction of 11.78% when compared theoretically and 10.41% when implemented in VISSIM.

Among the different strategies adopted to improve the efficiency and reliability of the bus services, bus signal priority is a low cost and less infrastructure- demanding solution that has the potential to reduce bus travel times in urban arterials. This paper develops analytical models for finding the thresholds for Green Extension (GE) and Red Truncation (RT) for a four-phase signal system with buses on conflicting phases. The thresholds are developed based on reducing the total person delay after considering buses from the current cycle and unserved buses from the previous cycle for priority decisions. The proposed models aim for zero-delay service for the buses from the current cycle and reducing delay for the unserved buses from the previous cycle. The models reveal that at multi-phase signals, several bus priority alternatives are possible to reduce total person delay and agencies can choose alternatives based on their requirements and constraints. These models are evaluated in VISSIM microscopic simulation environment. The evaluation results indicate a 16.7 to 42.8% reduction in total person intersection delay due to the implemented bus priority.

Recent digitalization has led to a significant increase in Data usage and WiFi penetration rates across the globe. WiFi Media Access Control (MAC) data, allows for unannounced and non-participatory tracking of electronic devices. This feature has attracted several transport researchers to use it in the estimation of spatial traffic parameters such as travel time. However, the commercial sensors available for WiFi MAC scanning are not affordable to be installed widely in a city.This paper talks about the development of a portable, low-cost Wireless Media Access Control Scanner and its evaluation for traffic applications. Control and field tests were done to identify the performance of the developed sensor. The developed sensor was found to work comparable or even better in urban traffic scenario when tested against a commercial counterpart.

Bus signal priority (BSP) is an active traffic management measure to reduce bus travel delay at signalized intersections and to improve the bus service reliability. In this paper, we present a real-time BSP system with a primary focus on its practical implementation. We tackle two inter-related issues of existing priority systems, namely, real-time computation and solution optimality, using an analytical approach. The core of the proposed priority system involves two signal controller actions–red truncation (RT) and green extension (GE), which determine the priority timings based on the objective of minimizing total person delay incurring at the subject intersection. We demonstrate the analytical approach by deriving closed-form expressions for optimal RT and GE for a two-phase signal using cumulative count curves. The inputs required for these priority models are based on average traffic and bus conditions limited to the current signal cycle alone. Solutions for the RT and GE models indicate that three dimensionless variables–ratio of bus-arrival time to traffic queuing time, ratio of bus passenger occupancy to other vehicles’ average passenger occupancy, and ratio of traffic demand to saturation flow ratio–govern the priority decisions. Simulation results showed significant delay reduction for buses (≈22%) with a negligible impact on other traffic users during low to medium traffic conditions and high bus frequencies (3 min headway).

This study evaluates and compares two major solutions used to mitigate the problem of delay of public transport buses at signalized intersections in urban arterials. The solutions considered are to implement bus signal priority (BSP) at intersections and to provide dedicated bus lanes (DBL). Comparison of performance is done in terms of travel time. Study site selected is a 5 km stretch in the IT corridor in Chennai for the DBL and with four intersections in that corridor for the BSP. Only the southbound movement is considered for the analysis. To evaluate the selected strategies, the study site was simulated in VISSIM, which is a micro-simulation software. Road, traffic, and control details from field were used as input, and a calibrated network was created. Using that, four scenarios were studied: 1. base condition with fixed time signals and no dedicated lane, 2. fixed time signal with DBL, 3. BSP without dedicated lane, and 4. BSP and DBL. Conditional Green Extension and Red Truncation priority strategies using Visual Vehicle Actuated Programming (VisVAP) from VISSIM were used for the BSP implementation. For dedicated bus lane condition, the mode preference was altered for the southbound movement links and the bus movement was allowed only in the left-most lane, which was kept as DBL. Results showed the bus signal priority having maximum impact in terms of reduction in total travel time. In the case of dedicated bus lane condition, travel time reduced effectively for bus mode, but with an increase in travel time of other modes.

One of the major reasons for frequent bottlenecks at intersections is the operation of poorly designed signals with static timings, irrespective of the variations in traffic flow. The fixed signal timings are calculated using conventional design methodologies such as Webster’s and HCM signal design methodologies that are primarily valid for lane disciplined homogenous traffic conditions. Implementation of such design procedures under mixed traffic conditions may not yield the best performance. Therefore, the present study aims to develop a simulation-based optimization that optimizes the performance of the intersection. Spatial performance measure such as travel time is perceived by the users and operators alike and therefore considered for minimization. A simulation-based optimization is performed by implementing various derivative-free optimization algorithms such as Nelder–Mead simplex algorithm and COBYLA using a microsimulation software, VISSIM. The obtained results are better when compared with that of traditional Webster’s design.

Efficient and reliable public transportation system has the potential to ease traffic congestion and improve overall transportation system performance. Out of the various measures for improving the public transportation performance, bus priority at the signalized intersection has the maximum potential to reduce bus travel times in urban areas. This study develops a solution for bus priority based on the objective of the total person delay reduction at signalized intersections under heterogeneous and lane undisciplined Indian traffic.