Date of Award
10-11-2024
Publication Type
Dissertation
Degree Name
Ph.D.
Department
Civil and Environmental Engineering
Keywords
Comfort;Connected Adaptive Cruise Control (CACC);Connected and Automated Vehicles;Safety;Traffic Efficiency;Vehicle Control Mechanism
Supervisor
Chris Lee
Supervisor
Yong Hoon Kim
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Abstract
Connected and Automated Vehicles (CAVs) will transform drivers into passengers, offering the significant advantage of saving the time typically spent on driving. This should allow passengers to engage in non-driving related tasks like reading, using handheld devices, or working on laptops, which would necessitate a requirement for greater comfort. A vehicle control mechanism of CAVs would hence be expected to provide comfort to enhance the passengers riding experience while ensuring the basic requirements of safety and traffic efficiency. This requirement considers two contradictory objectives - comfort necessitates greater following distances to achieve smooth deceleration while higher traffic efficiency requires a shorter spacing which decreases passenger comfort. This research aims to develop a collision-free vehicle control mechanism for CAVs that ensures passengers their desired comfort based on deceleration (rate of change of speed) and jerk (rate of change of deceleration) rates and enhances traffic efficiency when required without exceeding the threshold that makes them uncomfortable. The Gipps car-following model was chosen as the base model for developing a comfort-based proactive Connected Adaptive Cruise Control (CACC) algorithm because of its look-ahead projection strategy, which maintains a spacing between vehicles such that the subject vehicle (SV) could decelerate with its maximum desired deceleration rate, if the lead vehicle (LV) decelerated as per SV’s estimation. This research has three objectives: 1) to investigate the conditions when the Gipps car-following model produces unrealistic collisions and propose a solution to address this, ensuring the model to be collision-free under all conditions, 2) to develop a comfort-based proactive CACC algorithm for CAVs, which can ensure passengers their desired deceleration and jerk rates; and 3) to develop a “vehicle control mechanism” that can balance comfort and traffic efficiency when required without exceeding the threshold that can make the passengers uncomfortable. The CACC algorithm serves as the foundational algorithm that makes car-following decisions for the vehicle control mechanism. The CACC algorithm proposes to use long-term deceleration rate predictions of downstream traffic based on real-time and historical data (which could capture the effect of road geometric conditions based on recurrent traffic patterns). It uses the look-ahead projection strategy to proactively create a space from the LV such that if the LV decelerated as per the long-term predictions, the SV could decelerate with their desired deceleration and jerk rate. The CACC algorithm maintains a spacing between the vehicles based on the long-term deceleration rate predictions, and the SV’s desired deceleration and jerk parameters. This spacing is maintained according to the speed of the vehicles, i.e. higher speed requires higher spacing. Given the lack of SV’s control over the speed and deceleration rate predictions of downstream vehicles, if there is a need to increase traffic efficiency, the spacing between vehicles can be reduced by adjusting the SV’s desired deceleration rate. The need for how much spacing should be reduced depends on the number of vehicles that need to be accommodated, which is determined based on upstream traffic conditions. The reduction in spacing can be achieved by using efficiency deceleration rate whose value is variable and is calculated based on the number of vehicles to be accommodated, the average speed and the long-term deceleration rate predictions of downstream vehicles. A limit is set on the efficiency deceleration rate value which ensures that the passengers do not feel uncomfortable/ motion sick if the vehicle needs to decelerate. The limit on the subject vehicle's deceleration rate, which can vary, will determine the road capacity (a higher need for comfort results in lower capacity). The road capacity will also vary based on downstream traffic conditions which will increase with smoother downstream traffic flow but decrease with higher deceleration rates used by downstream vehicles. The vehicle control mechanism proactively makes decisions to use the desired comfortable deceleration and jerk rate until there is a need to use efficiency deceleration rate to reduce spacing between the vehicles to enhance the traffic efficiency. The simulation results show that the mechanism was effective in reducing the total travel time in congested situations while assuring that the deceleration rate did not exceed the maximum comfortable deceleration rate. The desired comfort was compromised in terms of increased initial jerk only when the LV decelerated harder than the long-term deceleration rate predictions. Safety was ensured under all conditions.
Recommended Citation
Shah, Dhwani Kamlesh, "Control Mechanism for Connected and Automated Vehicles: Enhancing Ride Safety, Comfort and Traffic Flow Efficiency" (2024). Electronic Theses and Dissertations. 9388.
https://scholar.uwindsor.ca/etd/9388